TradeTale OscillatorThis script explains how Oscillator can be used to catch market moves within a Range.
What is an Oscillator:-
An oscillator is a technical analysis tool that constructs high and low bands between two extreme values and then builds a trend indicator that fluctuates within these bounds. Traders use the trend indicator to discover short-term overbought or oversold conditions. RSI with MA is used along with minor calculations (maths) in this Oscillator for generating Long and Short signals.
RSI:-
RSI is a momentum oscillator which measures the speed and change of price movements. RSI moves up and down (oscillates) between ZERO and 100. Generally RSI above 70 is considered overbought and below 30 is considered oversold. Some traders may use a setting of 20 and 80 for oversold and overbought conditions respectively. Some traders may use a setting of 10 and 90 for oversold and overbought conditions respectively. However this may reduce the number of signals. 10 to 30 is shown as bullish zone and 70 to 90 is shown as bearish zone in this Oscillator.
Calculation:-
There are three basic components in the RSI - Avg Gain, Avg Loss & RS.
Avg Gain = Average of Upward Price Change
Avg Loss = Average of Downward Price Change
RS = (Avg Gain)/(Avg Loss)
RSI = 100 – (100 / (1 +RS ))
First Calculation:-
RSI calculation is based on default 14 periods.
Average gain and Average loss are simple 14 period averages.
Average Loss equals the sum of the losses divided by 14 for the first calculation.
Average Gain equals the sum of the Gains divided by 14 for the first calculation.
First Average Gain = Sum of Gains over the past 14 periods / 14.
First Average Loss = Sum of Losses over the past 14 periods / 14.
The formula uses a positive value for the average loss.
RS values are smoothed after the first calculation.
Second Calculation:-
Subsequent calculations multiply the prior value by 13, add the most recent value, and divide the total by 14.
Average Gain = / 14.
Average Loss = / 14.
if
Average Loss = 0, RSI = 100 (means there were no losses to measure).
Average Gain = 0, RSI = 0 (means there were no gains to measure).
Moving Average (MA):-
A moving average (MA) is used in technical analysis, used to help smooth out price data by creating a constantly updated average price. A rising moving average indicates that the security is in an uptrend, while a declining moving average indicates a downtrend.
Logic of this indicator:-
RSI is an oscillator that fluctuates between zero and 100 which makes it easy to use for many traders.
Its easy to identify extremes because RSI is range-bound.
RSI and MA calculations along with maths is used to generate signals.
Rocket signal in white colour is Long Signal and also exit Short signal. (Bullish Entry/Exit)
Scissor signal in orange colour is Short Signal and also exit long signal. (Bearish Entry/Exit)
Green colour band shows bullish momentum & Red colour band shows bearish momentum.
But remember that RSI works best in range bound market and is less trustworthy in trending markets. (caution)
A new trader need to be cautious because during strong trends in the market/security, RSI may remain in overbought (70 to 90) or oversold (10 to 30) for extended periods.
Chart Timeframe:-
This Oscillator works on all timeframes.
Traders should set stop loss and take profit levels as per risk reward ratio.
Note:
Don't confuse RSI and relative strength. RSI is changes in the price momentum of a security.
whereas relative strength compares the price performance of two or more securities.
Like other technical indicators, This Oscillator also is not a holy grail. It can only assist you in building a good strategy. You can only succeed with proper position sizing, risk management and following correct trading Psychology (No overtrade, No greed, No revenge trade etc).
THIS OSCILLATOR IS FOR EDUCATIONAL PURPOSE AND PAPER TRADING ONLY. YOU MAY PAPER TRADE TO GAIN CONFIDENCE AND BUILD FURTHER ON THESE. PLEASE CONSULT YOUR FINANCIAL ADVISOR BEFORE INVESTING. WE ARE NOT SEBI REGISTERED.
Hope you all like it
happy learning.
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RSI 11 IndicatorThis script explains how RSI can be used to catch market moves in trend, reversal or sideways market.
What is RSI indicator:-
RSI is a momentum oscillator which measures the speed and change of price movements. RSI moves up and down (oscillates) between ZERO and 100. Generally RSI above 70 is considered overbought and below 30 is considered oversold. Some traders may use a setting of 20 and 80 for oversold and overbought conditions respectively. However this may reduce the number of signals. You can also use RSI to identify divergences, strength, reversals, general trend etc.
Calculation:-
There are three basic components in the RSI - Avg Gain, Avg Loss & RS.
Avg Gain = Average of Upward Price Change
Avg Loss = Average of Downward Price Change
RS = (Avg Gain)/(Avg Loss)
RSI = 100 – (100 / (1 +RS ))
First Calculation:-
RSI calculation is based on default 14 periods.
Average gain and Average loss are simple 14 period averages.
Average Loss equals the sum of the losses divided by 14 for the first calculation.
Average Gain equals the sum of the Gains divided by 14 for the first calculation.
First Average Gain = Sum of Gains over the past 14 periods / 14.
First Average Loss = Sum of Losses over the past 14 periods / 14.
The formula uses a positive value for the average loss.
RS values are smoothed after the first calculation.
Second Calculation:-
Subsequent calculations multiply the prior value by 13, add the most recent value, and divide the total by 14.
Average Gain = / 14.
Average Loss = / 14.
if
Average Loss = 0, RSI = 100 (means there were no losses to measure).
Average Gain = 0, RSI = 0 (means there were no gains to measure).
Logic of this indicator:-
RSI is an oscillator that fluctuates between zero and 100 which makes it easy to use for many traders.
Its easy to identify extremes because RSI is range-bound.
But remember that RSI works best in range bound market and is less trustworthy in trending markets.
A new trader need to be cautious because during strong trends in the market/security, RSI may remain in overbought or oversold for extended periods.
Chart Timeframe:-
RSI indicator works well on all timeframes.
Timeframe depends on which strategy or settings are you using.
Generally a lower timeframe like 1 min, 3 min, 5 min, 15 min, 30 min, 1 Hr etc is used for intraday trades or short duration trades
and higher timeframes like 1 day, 1 week, 1 month are used for positional or long term trades.
Please Read the Idea "Mastering RSI with 11 Strategies" to understand this indicator better.
Indicator 1
Basis Strategy of Overbought and Oversold
Usually an asset with RSI reading of 70 or above indicates a bullish and an overbought situation.
overbought can be seen as trading at a higher price than it should.
traders may expect a price correction or trend reversal and sell the security.
but RSI indicator can stay in the overbought for a long time when the stock is in uptrend - This may trap an immature trader.
an Immature trader will enter a sell position when RSI become overbought (70), whereas a mature trader will enter sell position when RSI line crosses below the overbought line (70).
An asset with RSI reading of 30 or below indicates a bearish and an oversold condition.
oversold can be seen as trading at a lower price than it should.
traders may expect a price correction or trend reversal and buy the security.
but RSI indicator can stay in the oversold for a long time when the stock is in downtrend - This may trap an immature trader.
an Immature trader will enter a buy position when RSI become oversold (30), whereas a mature trader will enter buy position when RSI line crosses above the oversold line (30).
Center dotted Mid line is RSI 50.
Chart RSI is shown in yellow colour.
Red shaded area above the red horizontal line shows the stock or security has entered overbought condition. "R" signal in red shows a likely downside reversal, means it may be a likely Selling opportunity.
Green shaded area below the green horizontal line shows the stock or security has entered oversold condition. "R" signal in green shows a likely upside reversal, means it may be a likely Buying opportunity.
Note:-
so its better to wait for reversal signal.
traders may use 20 instead of 30 as oversold level and 80 instead of 70 as overbought level.
new traders may learn to use the indicator as per the prevailing trend to get better results.
false signals may be avoided by using bullish signals in bullish trend and bearish signals in bearish trend.
Indicator 2
RSI Strength Crossing 50
RSI crossing centreline 50 in the below chart showing strength and buy/sell signal.
Centre line is at RSI 50.
if RSI is above 50 its considered bullish trend. (increasing strength)
if RSI is below 50 its considered bearish trend. (decreasing strength)
RSI crossing centre line (50) upside may be a buy signal.
RSI crossing centre line (50) downside may be a sell signal.
"B" signal in green colour shows that RSI is crossing above Mid 50 horizontal line, which may be a likely Buy signal.
"S" signal in red colour shows that RSI is crossing below Mid 50 horizontal line, which may be a likely Sell signal.
Indicator 3
RSI 40 and RSI 60 Support and Resistance
RSI 40 acting as support in the below chart
In an uptrend RSI tends to remain in the 40 to 90 range with 40 as support (buying opportunity at support).
RSI 60 acting as resistance in the below chart
In a downtrend RSI tends to remain in 10 to 60 range with 60 as resistance (selling opportunity at resistance).
"40" signal in green colour shows that RSI is crossing above 40 horizontal line, which may be a likely Support in making and a Buy signal.
"60" signal in red colour shows that RSI is crossing below 60 horizontal line, which may be a likely Resistance in making and a Sell signal.
Note:-
These ranges may change depending on RSI settings and change in the market trend.
Indicator 4
RSI Divergence
Below chart shows a simple example of Bullish Divergence and Bearish Divergence.
An RSI divergence occurs when price moves in the opposite direction of the RSI.
A bullish divergence is when price is falling but RSI is rising. which means RSI making higher lows and price making lower lows (buy signal).
A bearish divergence is when price is rising but RSI is falling. which means RSI making lower high and price making higher highs (sell signal).
Divergences are more strong when appear in an overbought or oversold condition.
There may be many false signals during a strong uptrend or strong downtrend.
In a strong uptrend, RSI may show many false bearish divergences before finally reversing down.
same way in a strong downtrend, RSI may show many false bullish divergences before finally reversing up.
"Bull Div" signal along with divergence line in green colour shows Bullish Divergence, which may be a likely Buy signal.
"Bear Div" signal along with divergence line in red colour shows Bearish Divergence, which may be a likely Sell signal.
Indicator 5
Double Top & Double Bottom
Double Bottom = RSI goes below oversold (30). RSI comes back above 30. RSI falls back again towards 30 and again rise making a Double bottom. its a signal of buying and likely upside reversal.
Double Top = RSI goes above overbought (70). RSI comes back below 70. RSI rises back again towards 70 and again fall making a Double top. its a signal of selling and likely downside reversal.
Double Bottom is shown with Green Dashed line joining two low's of RSI indicating a likely Buy Signal.
Double Top is shown with Red Dashed line joining two High's of RSI indicating a likely Sell Signal.
Indicator 6
Trendline Support and Resistance
Below chart shows RSI Trendline Resistance and Support
RSI resistance trendline = Connect three or more points on the RSI line as it falls to draw a RSI downtrend line (RSI resistance trendline).
Everytime it takes resistance from a RSI downtrend line its a selling opportunity.
RSI support trendline = Connect three or more points on the RSI line as it rises to draw a RSI uptrend line (RSI support trendline).
Everytime it takes support on a RSI uptrend line its a buying opportunity.
RSI Resistance trendline shown in Red colour indicating a likely fall again after rejection from this Red trendline till the time RSI breaks above it to change the trend from Bearsih to Bullish.
RSI support trendline shown in Green colour indicating a likely Rise again after support from this Green trendline till the time RSI breaks below it to change the trend from Bullish to Bearish.
Indicator 7
Trendline Breakout and Breakdown
Below chart shows RSI Trendline Breakout and Breakdown
RSI resistance trendline Breakout = Connect three or more points on the RSI line as it falls to draw a RSI downtrend line (RSI resistance trendline).
Whenever it breakout above RSI resistance trendline its a buying opportunity.
RSI support trendline Breakdown = Connect three or more points on the RSI line as it rises to draw a RSI uptrend line (RSI support trendline).
Whenever it breakdown below RSI support trendline its a selling opportunity.
Note:-
Correlate both the RSI and the closing price to ensure proper breakout or breakdown.
Challenge is to correctly identify if a breakout or breakdown is sustainable or its a false signal.
Indicator 8
RSI Crossover same timeframe
RSI with two different RSI length crossing each other on same timeframe.
when lower RSI length crossing above higher RSI length its a buy signal.
when lower RSI length crossing below higher RSI length its a sell signal.
for example RSI with length 7 & length 14 on 15 Minutes timeframe.
Green Cross shows that Fast RSI is crossing above Slow RSI on the same timeframe with different RSI length Settings, which means it may be a likely Buy Signal.
Red Cross shows that Fast RSI is crossing below Slow RSI on the same timeframe with different RSI length Settings, which means it may be a likely Sell Signal.
Indicator 9
RSI Crossover Multi timeframe
RSI with same RSI length but on two different timeframes crossing each.
when lower timeframe RSI crossing above higher timeframe RSI its a buy signal.
when lower timeframe RSI crossing below higher timeframe RSI its a sell signal.
for example RSI with length 14 on 5 Minutes and 1 Hr timeframes.
Green Cross shows that Lower Timeframe RSI is crossing above Higher Timeframe RSI with same RSI length Settings, which means it may be a likely Buy Signal.
Red Cross shows that Lower Timeframe RSI is crossing below Higher Timeframe RSI with same RSI length Settings, which means it may be a likely Sell Signal.
Indicator 10
RSI EMA/WMA/SMA Crossover
when RSI crossing above EMA/WMA/SMA its a buy signal.
when RSI crossing below EMA/WMA/SMA its a sell signal.
Green Circle shows that RSI is crossing above EMA/WMA/SMA etc, which means it may be a likely Buy Signal.
Red Circle shows that RSI is crossing below EMA/WMA/SMA etc, which means it may be a likely Sell Signal.
Indicator 11
RSI with Bollinger bands
Bollinger bands and RSI complimenting each other and giving a Buy and Sell signal in below chart
if a security price reaches upper band of a Bollinger Band channel and also the RSI is above 70 (overbought), a trader can look for selling opportunities (reversal) (sell).
but in case price reaches upper band of a Bollinger Band channel but RSI is not above 70 (overbought), there may be chance that security remains in an uptrend, so a trader may wait before entering a sell position.
if a security price reaches lower band of a Bollinger Band channel and also the RSI is below 30 (oversold), a trader can look for buying opportunities (reversal) (buy).
but in case price reaches lower band of a Bollinger Band channel but RSI is not below 30 (oversold), there may be chance that security remains in an downtrend, so a trader may wait before entering a buy position.
so bollinger band with RSI can give a double confirmation on a reversal.
Buy Signal = If the RSI is below Green Horizontal line (Oversold zone) and also below Lower Bollinger Band it indicates that an upside reversal may come, which means that it may be a likely Buy Signal.
Sell Signal = If the RSI is above Red Horizontal line (Overbought zone) and also above Upper Bollinger Band it indicates that an Downside reversal may come, which means that it may be a likely Sell Signal.
Special Thanks to //© HoanGhetti for RSI Trendlines.
Limitations of the RSI:-
RSI works best in range bound market and is less trustworthy in trending markets.
So new traders may get trapped in an uptrend or a downtrend if they forget to see the overall long term trend of that security.
Traders should set stop loss and take profit levels as per risk reward ratio.
Note:
Don't confuse RSI and relative strength. RSI is changes in the price momentum of a security.
whereas relative strength compares the price performance of two or more securities.
Like other technical indicators, RSI also is not a holy grail. It can only assist you in building a good strategy. You can only succeed with proper position sizing, risk management and following correct trading Psychology (No overtrade, No greed, No revenge trade etc).
THIS INDICATOR OF RSI IS FOR EDUCATIONAL PURPOSE AND PAPER TRADING ONLY. YOU MAY PAPER TRADE TO GAIN CONFIDENCE AND BUILD FURTHER ON THESE. PLEASE CONSULT YOUR FINANCIAL ADVISOR BEFORE INVESTING. WE ARE NOT SEBI REGISTERED.
Hope you all like it
happy learning.
Moving Average Rainbow (Stormer)This strategy is based and shown by trader and investor Alexandre Wolwacz "Stormer".
Overview
The strategy uses 12 moving averages (default EMA) to identify trends and generate trading signals opening positions.
Allowing to select the type of moving average and length to be used.
The conditions includes relationship between moving averages, the position of the current price relative to the moving averages, and the occurrence of certain price patterns.
Calculation
The mean moving averages is calculated by adding all the 12 moving averages and dividing by 12, the value is used to help to identify trend and possible condition to open position.
The 12 moving averages is spliced by 3 ranges, initial range (moving average lines 1 to 4), middle range (moving average lines 5 to 8) and end range (moving average lines 9 to 12). These ranges helps to identify potential trend and market turn over.
The moving average touch price is a relationship between the low price (uptrend) or high price (downtrend) with the moving average lines, it identifies where the price (low/high) has reached the the moving average line. Fetching the value to help for opening position, set stop loss and take profit.
Since the stop loss is based and set from the previous moving average touch price value, when position is about to be open and setting the stop loss value, there is a verification to check both current and previous moving average touch price to recalculate the stop loss value.
The turnover trend checks for a possible market turnover event, setting up a new profit target, this setting when enabled is to be helpful when a turnover occurs against the position to exit position with some profit based on highest high price if long or lowest low price if short.
The turnover signal is similar to turnover trend. The difference is that when this setting is enabled and it triggers, it simply exit the current position and opens up a reverse position, long goes short and short goes long. And there is an complement optional that checks current price exit profitable.
Entry Position
Long Position:
Price is higher than the mean moving averages. Meaning possible uptrend.
The lines of the middle range from the moving averages are in increasing order. Meaning possible uptrend.
The current high pierced up previous high.
Fetch the previous value of the moving average touch price. Meaning the low price has touched one of the moving average lines, which that value is conditioning to open position.
Short Position:
Price is lower than the mean moving averages. Meaning possible downtrend.
The lines of the middle range from the moving averages are in decreasing order. Meaning possible downtrend.
The current low pierced down previous low.
Fetch the previous value of the moving average touch price. Meaning the high price has touched one of the moving average lines, which that value is conditioning to open position.
Risk Management
Stop Loss:
The stop loss is based from the previous moving average touch price value, high price for short and low price for long or occurs an verification to check for both current and previous moving average touch price value and a recalculation is done to set the stop loss.
Take Profit:
According to the author, the profit target should be at least 1:1.6 the risk, so to have the strategy mathematically positive.
The profit target is configured input, can be increased or decreased.
It calculates the take profit based on the price of the stop loss with the profit target input.
Turnover Trend
Long Position:
The moving averages initial range lines signals a possible market turnover. Meaning long might be going short.
Fetches the highest high hit since the opening of the position, setting that value to the new profit target.
Short Position:
The moving averages initial range lines signals a possible market turnover. Meaning short might be going long.
Fetches the lowest low hit since the opening of the position, setting that value to the new profit target.
GKD-M Baseline Optimizer [Loxx]Giga Kaleidoscope GKD-M Baseline Optimizer is a Metamorphosis module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
The Baseline Optimizer enables traders to backtest over 60 moving averages using variable period inputs. It then exports the baseline with the highest cumulative win rate per candle to any baseline-enabled GKD backtest. To perform the backtesting, the trader selects an initial period input (default is 60) and a skip value that increments the initial period input up to seven times. For instance, if a skip value of 5 is chosen, the Baseline Optimizer will run the backtest for the selected moving average on periods such as 60, 65, 70, 75, and so on, up to 90. If the user selects an initial period input of 45 and a skip value of 2, the Baseline Optimizer will conduct backtests for the chosen moving average on periods like 45, 47, 49, 51, and so forth, up to 57.
The Baseline Optimizer provides a table displaying the output of the backtests for a specified date range. The table output represents the cumulative win rate for the given date range.
On the Metamorphosis side of the Baseline Optimizer, a cumulative backtest is calculated for each candle within the date range. This means that each candle may exhibit a different distribution of period inputs with the highest win rate for a particular moving average. The Baseline Optimizer identifies the period input combination with the highest win rates for long and short positions and creates a win-rate adaptive long and short moving average chart. The moving average used for shorts differs from the moving average used for longs, and the moving average for each candle may vary from any other candle. This customized baseline can then be exported to all baseline-enabled GKD backtests.
The backtest employed in the Baseline Optimizer is a Solo Confirmation Simple, allowing only one take profit and one stop loss to be set.
Lastly, the Baseline Optimizer incorporates Goldie Locks Zone filtering, which can be utilized for signal generation in advanced GKD backtests.
█ Moving Averages included in the Baseline Optimizer
Adaptive Moving Average - AMA
ADXvma - Average Directional Volatility Moving Average
Ahrens Moving Average
Alexander Moving Average - ALXMA
Deviation Scaled Moving Average - DSMA
Donchian
Double Exponential Moving Average - DEMA
Double Smoothed Exponential Moving Average - DSEMA
Double Smoothed FEMA - DSFEMA
Double Smoothed Range Weighted EMA - DSRWEMA
Double Smoothed Wilders EMA - DSWEMA
Double Weighted Moving Average - DWMA
Exponential Moving Average - EMA
Fast Exponential Moving Average - FEMA
Fractal Adaptive Moving Average - FRAMA
Generalized DEMA - GDEMA
Generalized Double DEMA - GDDEMA
Hull Moving Average (Type 1) - HMA1
Hull Moving Average (Type 2) - HMA2
Hull Moving Average (Type 3) - HMA3
Hull Moving Average (Type 4) - HMA4
IE /2 - Early T3 by Tim Tilson
Integral of Linear Regression Slope - ILRS
Kaufman Adaptive Moving Average - KAMA
Leader Exponential Moving Average
Linear Regression Value - LSMA ( Least Squares Moving Average )
Linear Weighted Moving Average - LWMA
McGinley Dynamic
McNicholl EMA
Non-Lag Moving Average
Ocean NMA Moving Average - ONMAMA
One More Moving Average - OMA
Parabolic Weighted Moving Average
Probability Density Function Moving Average - PDFMA
Quadratic Regression Moving Average - QRMA
Regularized EMA - REMA
Range Weighted EMA - RWEMA
Recursive Moving Trendline
Simple Decycler - SDEC
Simple Jurik Moving Average - SJMA
Simple Moving Average - SMA
Sine Weighted Moving Average
Smoothed LWMA - SLWMA
Smoothed Moving Average - SMMA
Smoother
Super Smoother
T3
Three-pole Ehlers Butterworth
Three-pole Ehlers Smoother
Triangular Moving Average - TMA
Triple Exponential Moving Average - TEMA
Two-pole Ehlers Butterworth
Two-pole Ehlers smoother
Variable Index Dynamic Average - VIDYA
Variable Moving Average - VMA
Volume Weighted EMA - VEMA
Volume Weighted Moving Average - VWMA
Zero-Lag DEMA - Zero Lag Exponential Moving Average
Zero-Lag Moving Average
Zero Lag TEMA - Zero Lag Triple Exponential Moving Average
Adaptive Moving Average - AMA
The Adaptive Moving Average (AMA) is a moving average that changes its sensitivity to price moves depending on the calculated volatility. It becomes more sensitive during periods when the price is moving smoothly in a certain direction and becomes less sensitive when the price is volatile.
ADXvma - Average Directional Volatility Moving Average
Linnsoft's ADXvma formula is a volatility-based moving average, with the volatility being determined by the value of the ADX indicator.
The ADXvma has the SMA in Chande's CMO replaced with an EMA , it then uses a few more layers of EMA smoothing before the "Volatility Index" is calculated.
A side effect is, those additional layers slow down the ADXvma when you compare it to Chande's Variable Index Dynamic Average VIDYA .
The ADXVMA provides support during uptrends and resistance during downtrends and will stay flat for longer, but will create some of the most accurate market signals when it decides to move.
Ahrens Moving Average
Richard D. Ahrens's Moving Average promises "Smoother Data" that isn't influenced by the occasional price spike. It works by using the Open and the Close in his formula so that the only time the Ahrens Moving Average will change is when the candlestick is either making new highs or new lows.
Alexander Moving Average - ALXMA
This Moving Average uses an elaborate smoothing formula and utilizes a 7 period Moving Average. It corresponds to fitting a second-order polynomial to seven consecutive observations. This moving average is rarely used in trading but is interesting as this Moving Average has been applied to diffusion indexes that tend to be very volatile.
Deviation Scaled Moving Average - DSMA
The Deviation-Scaled Moving Average is a data smoothing technique that acts like an exponential moving average with a dynamic smoothing coefficient. The smoothing coefficient is automatically updated based on the magnitude of price changes. In the Deviation-Scaled Moving Average, the standard deviation from the mean is chosen to be the measure of this magnitude. The resulting indicator provides substantial smoothing of the data even when price changes are small while quickly adapting to these changes.
Donchian
Donchian Channels are three lines generated by moving average calculations that comprise an indicator formed by upper and lower bands around a midrange or median band. The upper band marks the highest price of a security over N periods while the lower band marks the lowest price of a security over N periods.
Double Exponential Moving Average - DEMA
The Double Exponential Moving Average ( DEMA ) combines a smoothed EMA and a single EMA to provide a low-lag indicator. It's primary purpose is to reduce the amount of "lagging entry" opportunities, and like all Moving Averages, the DEMA confirms uptrends whenever price crosses on top of it and closes above it, and confirms downtrends when the price crosses under it and closes below it - but with significantly less lag.
Double Smoothed Exponential Moving Average - DSEMA
The Double Smoothed Exponential Moving Average is a lot less laggy compared to a traditional EMA . It's also considered a leading indicator compared to the EMA , and is best utilized whenever smoothness and speed of reaction to market changes are required.
Double Smoothed FEMA - DSFEMA
Same as the Double Exponential Moving Average (DEMA), but uses a faster version of EMA for its calculation.
Double Smoothed Range Weighted EMA - DSRWEMA
Range weighted exponential moving average (EMA) is, unlike the "regular" range weighted average calculated in a different way. Even though the basis - the range weighting - is the same, the way how it is calculated is completely different. By definition this type of EMA is calculated as a ratio of EMA of price*weight / EMA of weight. And the results are very different and the two should be considered as completely different types of averages. The higher than EMA to price changes responsiveness when the ranges increase remains in this EMA too and in those cases this EMA is clearly leading the "regular" EMA. This version includes double smoothing.
Double Smoothed Wilders EMA - DSWEMA
Welles Wilder was frequently using one "special" case of EMA (Exponential Moving Average) that is due to that fact (that he used it) sometimes called Wilder's EMA. This version is adding double smoothing to Wilder's EMA in order to make it "faster" (it is more responsive to market prices than the original) and is still keeping very smooth values.
Double Weighted Moving Average - DWMA
Double weighted moving average is an LWMA (Linear Weighted Moving Average). Instead of doing one cycle for calculating the LWMA, the indicator is made to cycle the loop 2 times. That produces a smoother values than the original LWMA
Exponential Moving Average - EMA
The EMA places more significance on recent data points and moves closer to price than the SMA ( Simple Moving Average ). It reacts faster to volatility due to its emphasis on recent data and is known for its ability to give greater weight to recent and more relevant data. The EMA is therefore seen as an enhancement over the SMA .
Fast Exponential Moving Average - FEMA
An Exponential Moving Average with a short look-back period.
Fractal Adaptive Moving Average - FRAMA
The Fractal Adaptive Moving Average by John Ehlers is an intelligent adaptive Moving Average which takes the importance of price changes into account and follows price closely enough to display significant moves whilst remaining flat if price ranges. The FRAMA does this by dynamically adjusting the look-back period based on the market's fractal geometry.
Generalized DEMA - GDEMA
The double exponential moving average (DEMA), was developed by Patrick Mulloy in an attempt to reduce the amount of lag time found in traditional moving averages. It was first introduced in the February 1994 issue of the magazine Technical Analysis of Stocks & Commodities in Mulloy's article "Smoothing Data with Faster Moving Averages.". Instead of using fixed multiplication factor in the final DEMA formula, the generalized version allows you to change it. By varying the "volume factor" form 0 to 1 you apply different multiplications and thus producing DEMA with different "speed" - the higher the volume factor is the "faster" the DEMA will be (but also the slope of it will be less smooth). The volume factor is limited in the calculation to 1 since any volume factor that is larger than 1 is increasing the overshooting to the extent that some volume factors usage makes the indicator unusable.
Generalized Double DEMA - GDDEMA
The double exponential moving average (DEMA), was developed by Patrick Mulloy in an attempt to reduce the amount of lag time found in traditional moving averages. It was first introduced in the February 1994 issue of the magazine Technical Analysis of Stocks & Commodities in Mulloy's article "Smoothing Data with Faster Moving Averages''. This is an extension of the Generalized DEMA using Tim Tillsons (the inventor of T3) idea, and is using GDEMA of GDEMA for calculation (which is the "middle step" of T3 calculation). Since there are no versions showing that middle step, this version covers that too. The result is smoother than Generalized DEMA, but is less smooth than T3 - one has to do some experimenting in order to find the optimal way to use it, but in any case, since it is "faster" than the T3 (Tim Tillson T3) and still smooth, it looks like a good compromise between speed and smoothness.
Hull Moving Average (Type 1) - HMA1
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses SMA for smoothing.
Hull Moving Average (Type 2) - HMA2
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses EMA for smoothing.
Hull Moving Average (Type 3) - HMA3
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses LWMA for smoothing.
Hull Moving Average (Type 4) - HMA4
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses SMMA for smoothing.
IE /2 - Early T3 by Tim Tilson and T3 new
The T3 moving average is a type of technical indicator used in financial analysis to identify trends in price movements. It is similar to the Exponential Moving Average (EMA) and the Double Exponential Moving Average (DEMA), but uses a different smoothing algorithm.
The T3 moving average is calculated using a series of exponential moving averages that are designed to filter out noise and smooth the data. The resulting smoothed data is then weighted with a non-linear function to produce a final output that is more responsive to changes in trend direction.
The T3 moving average can be customized by adjusting the length of the moving average, as well as the weighting function used to smooth the data. It is commonly used in conjunction with other technical indicators as part of a larger trading strategy.
Integral of Linear Regression Slope - ILRS
A Moving Average where the slope of a linear regression line is simply integrated as it is fitted in a moving window of length N (natural numbers in maths) across the data. The derivative of ILRS is the linear regression slope. ILRS is not the same as a SMA ( Simple Moving Average ) of length N, which is actually the midpoint of the linear regression line as it moves across the data.
Kaufman Adaptive Moving Average - KAMA
Developed by Perry Kaufman, Kaufman's Adaptive Moving Average (KAMA) is a moving average designed to account for market noise or volatility. KAMA will closely follow prices when the price swings are relatively small and the noise is low.
Leader Exponential Moving Average
The Leader EMA was created by Giorgos E. Siligardos who created a Moving Average which was able to eliminate lag altogether whilst maintaining some smoothness. It was first described during his research paper "MACD Leader" where he applied this to the MACD to improve its signals and remove its lagging issue. This filter uses his leading MACD's "modified EMA" and can be used as a zero lag filter.
Linear Regression Value - LSMA ( Least Squares Moving Average )
LSMA as a Moving Average is based on plotting the end point of the linear regression line. It compares the current value to the prior value and a determination is made of a possible trend, eg. the linear regression line is pointing up or down.
Linear Weighted Moving Average - LWMA
LWMA reacts to price quicker than the SMA and EMA . Although it's similar to the Simple Moving Average , the difference is that a weight coefficient is multiplied to the price which means the most recent price has the highest weighting, and each prior price has progressively less weight. The weights drop in a linear fashion.
McGinley Dynamic
John McGinley created this Moving Average to track prices better than traditional Moving Averages. It does this by incorporating an automatic adjustment factor into its formula, which speeds (or slows) the indicator in trending, or ranging, markets.
McNicholl EMA
Dennis McNicholl developed this Moving Average to use as his center line for his "Better Bollinger Bands" indicator and was successful because it responded better to volatility changes over the standard SMA and managed to avoid common whipsaws.
Non-lag moving average
The Non Lag Moving average follows price closely and gives very quick signals as well as early signals of price change. As a standalone Moving Average, it should not be used on its own, but as an additional confluence tool for early signals.
Ocean NMA Moving Average - ONMAMA
Created by Jim Sloman, the NMA is a moving average that automatically adjusts to volatility without being programmed to do so. For more info, read his guide "Ocean Theory, an Introduction"
One More Moving Average (OMA)
The One More Moving Average (OMA) is a technical indicator that calculates a series of Jurik-style moving averages in order to reduce noise and provide smoother price data. It uses six exponential moving averages to generate the final value, with the length of the moving averages determined by an adaptive algorithm that adjusts to the current market conditions. The algorithm calculates the average period by comparing the signal to noise ratio and using this value to determine the length of the moving averages. The resulting values are used to generate the final value of the OMA, which can be used to identify trends and potential changes in trend direction.
Parabolic Weighted Moving Average
The Parabolic Weighted Moving Average is a variation of the Linear Weighted Moving Average . The Linear Weighted Moving Average calculates the average by assigning different weights to each element in its calculation. The Parabolic Weighted Moving Average is a variation that allows weights to be changed to form a parabolic curve. It is done simply by using the Power parameter of this indicator.
Probability Density Function Moving Average - PDFMA
Probability density function based MA is a sort of weighted moving average that uses probability density function to calculate the weights. By its nature it is similar to a lot of digital filters.
Quadratic Regression Moving Average - QRMA
A quadratic regression is the process of finding the equation of the parabola that best fits a set of data. This moving average is an obscure concept that was posted to Forex forums in around 2008.
Regularized EMA - REMA
The regularized exponential moving average (REMA) by Chris Satchwell is a variation on the EMA (see Exponential Moving Average) designed to be smoother but not introduce too much extra lag.
Range Weighted EMA - RWEMA
This indicator is a variation of the range weighted EMA. The variation comes from a possible need to make that indicator a bit less "noisy" when it comes to slope changes. The method used for calculating this variation is the method described by Lee Leibfarth in his article "Trading With An Adaptive Price Zone".
Recursive Moving Trendline
Dennis Meyers's Recursive Moving Trendline uses a recursive (repeated application of a rule) polynomial fit, a technique that uses a small number of past values estimations of price and today's price to predict tomorrow's price.
Simple Decycler - SDEC
The Ehlers Simple Decycler study is a virtually zero-lag technical indicator proposed by John F. Ehlers. The original idea behind this study (and several others created by John F. Ehlers) is that market data can be considered a continuum of cycle periods with different cycle amplitudes. Thus, trending periods can be considered segments of longer cycles, or, in other words, low-frequency segments. Applying the right filter might help identify these segments.
Simple Loxx Moving Average - SLMA
A three stage moving average combining an adaptive EMA, a Kalman Filter, and a Kauffman adaptive filter.
Simple Moving Average - SMA
The SMA calculates the average of a range of prices by adding recent prices and then dividing that figure by the number of time periods in the calculation average. It is the most basic Moving Average which is seen as a reliable tool for starting off with Moving Average studies. As reliable as it may be, the basic moving average will work better when it's enhanced into an EMA .
Sine Weighted Moving Average
The Sine Weighted Moving Average assigns the most weight at the middle of the data set. It does this by weighting from the first half of a Sine Wave Cycle and the most weighting is given to the data in the middle of that data set. The Sine WMA closely resembles the TMA (Triangular Moving Average).
Smoothed LWMA - SLWMA
A smoothed version of the LWMA
Smoothed Moving Average - SMMA
The Smoothed Moving Average is similar to the Simple Moving Average ( SMA ), but aims to reduce noise rather than reduce lag. SMMA takes all prices into account and uses a long lookback period. Due to this, it's seen as an accurate yet laggy Moving Average.
Smoother
The Smoother filter is a faster-reacting smoothing technique which generates considerably less lag than the SMMA ( Smoothed Moving Average ). It gives earlier signals but can also create false signals due to its earlier reactions. This filter is sometimes wrongly mistaken for the superior Jurik Smoothing algorithm.
Super Smoother
The Super Smoother filter uses John Ehlers’s “Super Smoother” which consists of a Two pole Butterworth filter combined with a 2-bar SMA ( Simple Moving Average ) that suppresses the 22050 Hz Nyquist frequency: A characteristic of a sampler, which converts a continuous function or signal into a discrete sequence.
Three-pole Ehlers Butterworth
The 3 pole Ehlers Butterworth (as well as the Two pole Butterworth) are both superior alternatives to the EMA and SMA . They aim at producing less lag whilst maintaining accuracy. The 2 pole filter will give you a better approximation for price, whereas the 3 pole filter has superior smoothing.
Three-pole Ehlers smoother
The 3 pole Ehlers smoother works almost as close to price as the above mentioned 3 Pole Ehlers Butterworth. It acts as a strong baseline for signals but removes some noise. Side by side, it hardly differs from the Three Pole Ehlers Butterworth but when examined closely, it has better overshoot reduction compared to the 3 pole Ehlers Butterworth.
Triangular Moving Average - TMA
The TMA is similar to the EMA but uses a different weighting scheme. Exponential and weighted Moving Averages will assign weight to the most recent price data. Simple moving averages will assign the weight equally across all the price data. With a TMA (Triangular Moving Average), it is double smoother (averaged twice) so the majority of the weight is assigned to the middle portion of the data.
Triple Exponential Moving Average - TEMA
The TEMA uses multiple EMA calculations as well as subtracting lag to create a tool which can be used for scalping pullbacks. As it follows price closely, its signals are considered very noisy and should only be used in extremely fast-paced trading conditions.
Two-pole Ehlers Butterworth
The 2 pole Ehlers Butterworth (as well as the three pole Butterworth mentioned above) is another filter that cuts out the noise and follows the price closely. The 2 pole is seen as a faster, leading filter over the 3 pole and follows price a bit more closely. Analysts will utilize both a 2 pole and a 3 pole Butterworth on the same chart using the same period, but having both on chart allows its crosses to be traded.
Two-pole Ehlers smoother
A smoother version of the Two pole Ehlers Butterworth. This filter is the faster version out of the 3 pole Ehlers Butterworth. It does a decent job at cutting out market noise whilst emphasizing a closer following to price over the 3 pole Ehlers .
Variable Index Dynamic Average - VIDYA
Variable Index Dynamic Average Technical Indicator ( VIDYA ) was developed by Tushar Chande. It is an original method of calculating the Exponential Moving Average ( EMA ) with the dynamically changing period of averaging.
Variable Moving Average - VMA
The Variable Moving Average (VMA) is a study that uses an Exponential Moving Average being able to automatically adjust its smoothing factor according to the market volatility.
Volume Weighted EMA - VEMA
An EMA that uses a volume and price weighted calculation instead of the standard price input.
Volume Weighted Moving Average - VWMA
A Volume Weighted Moving Average is a moving average where more weight is given to bars with heavy volume than with light volume. Thus the value of the moving average will be closer to where most trading actually happened than it otherwise would be without being volume weighted.
Zero-Lag DEMA - Zero Lag Double Exponential Moving Average
John Ehlers's Zero Lag DEMA's aim is to eliminate the inherent lag associated with all trend following indicators which average a price over time. Because this is a Double Exponential Moving Average with Zero Lag, it has a tendency to overshoot and create a lot of false signals for swing trading. It can however be used for quick scalping or as a secondary indicator for confluence.
Zero-Lag Moving Average
The Zero Lag Moving Average is described by its creator, John Ehlers , as a Moving Average with absolutely no delay. And it's for this reason that this filter will cause a lot of abrupt signals which will not be ideal for medium to long-term traders. This filter is designed to follow price as close as possible whilst de-lagging data instead of basing it on regular data. The way this is done is by attempting to remove the cumulative effect of the Moving Average.
Zero-Lag TEMA - Zero Lag Triple Exponential Moving Average
Just like the Zero Lag DEMA , this filter will give you the fastest signals out of all the Zero Lag Moving Averages. This is useful for scalping but dangerous for medium to long-term traders, especially during market Volatility and news events. Having no lag, this filter also has no smoothing in its signals and can cause some very bizarre behavior when applied to certain indicators.
█ Volatility Goldie Locks Zone
The Goldie Locks Zone volatility filter is the standard first-pass filter used in all advanced GKD backtests (Complex, Super Complex, and Full GKd). This filter requires the price to fall within a range determined by multiples of volatility. The Goldie Locks Zone is separate from the core Baseline and utilizes its own moving average with Loxx's Exotic Source Types you can read about below.
On the chart, you will find green and red dots positioned at the top, indicating whether a candle qualifies for a long or short trade respectively. Additionally, green and red triangles are located at the bottom of the chart, signifying whether the trigger has crossed up or down and qualifies within the Goldie Locks zone. The Goldie Locks zone is represented by a white color on the mean line, indicating low volatility levels that are not suitable for trading.
█ Volatility Types Included in the Baseline Optimizer
The GKD system utilizes volatility-based take profits and stop losses. Each take profit and stop loss is calculated as a multiple of volatility. Users can also adjust the multiplier values in the settings.
This module includes 17 types of volatility:
Close-to-Close
Parkinson
Garman-Klass
Rogers-Satchell
Yang-Zhang
Garman-Klass-Yang-Zhang
Exponential Weighted Moving Average
Standard Deviation of Log Returns
Pseudo GARCH(2,2)
Average True Range
True Range Double
Standard Deviation
Adaptive Deviation
Median Absolute Deviation
Efficiency-Ratio Adaptive ATR
Mean Absolute Deviation
Static Percent
Various volatility estimators and indicators that investors and traders can use to measure the dispersion or volatility of a financial instrument's price. Each estimator has its strengths and weaknesses, and the choice of estimator should depend on the specific needs and circumstances of the user.
Close-to-Close
Close-to-Close volatility is a classic and widely used volatility measure, sometimes referred to as historical volatility.
Volatility is an indicator of the speed of a stock price change. A stock with high volatility is one where the price changes rapidly and with a larger amplitude. The more volatile a stock is, the riskier it is.
Close-to-close historical volatility is calculated using only a stock's closing prices. It is the simplest volatility estimator. However, in many cases, it is not precise enough. Stock prices could jump significantly during a trading session and return to the opening value at the end. That means that a considerable amount of price information is not taken into account by close-to-close volatility.
Despite its drawbacks, Close-to-Close volatility is still useful in cases where the instrument doesn't have intraday prices. For example, mutual funds calculate their net asset values daily or weekly, and thus their prices are not suitable for more sophisticated volatility estimators.
Parkinson
Parkinson volatility is a volatility measure that uses the stock’s high and low price of the day.
The main difference between regular volatility and Parkinson volatility is that the latter uses high and low prices for a day, rather than only the closing price. This is useful as close-to-close prices could show little difference while large price movements could have occurred during the day. Thus, Parkinson's volatility is considered more precise and requires less data for calculation than close-to-close volatility.
One drawback of this estimator is that it doesn't take into account price movements after the market closes. Hence, it systematically undervalues volatility. This drawback is addressed in the Garman-Klass volatility estimator.
Garman-Klass
Garman-Klass is a volatility estimator that incorporates open, low, high, and close prices of a security.
Garman-Klass volatility extends Parkinson's volatility by taking into account the opening and closing prices. As markets are most active during the opening and closing of a trading session, it makes volatility estimation more accurate.
Garman and Klass also assumed that the process of price change follows a continuous diffusion process (Geometric Brownian motion). However, this assumption has several drawbacks. The method is not robust for opening jumps in price and trend movements.
Despite its drawbacks, the Garman-Klass estimator is still more effective than the basic formula since it takes into account not only the price at the beginning and end of the time interval but also intraday price extremes.
Researchers Rogers and Satchell have proposed a more efficient method for assessing historical volatility that takes into account price trends. See Rogers-Satchell Volatility for more detail.
Rogers-Satchell
Rogers-Satchell is an estimator for measuring the volatility of securities with an average return not equal to zero.
Unlike Parkinson and Garman-Klass estimators, Rogers-Satchell incorporates a drift term (mean return not equal to zero). As a result, it provides better volatility estimation when the underlying is trending.
The main disadvantage of this method is that it does not take into account price movements between trading sessions. This leads to an underestimation of volatility since price jumps periodically occur in the market precisely at the moments between sessions.
A more comprehensive estimator that also considers the gaps between sessions was developed based on the Rogers-Satchel formula in the 2000s by Yang-Zhang. See Yang Zhang Volatility for more detail.
Yang-Zhang
Yang Zhang is a historical volatility estimator that handles both opening jumps and the drift and has a minimum estimation error.
Yang-Zhang volatility can be thought of as a combination of the overnight (close-to-open volatility) and a weighted average of the Rogers-Satchell volatility and the day’s open-to-close volatility. It is considered to be 14 times more efficient than the close-to-close estimator.
Garman-Klass-Yang-Zhang
Garman-Klass-Yang-Zhang (GKYZ) volatility estimator incorporates the returns of open, high, low, and closing prices in its calculation.
GKYZ volatility estimator takes into account overnight jumps but not the trend, i.e., it assumes that the underlying asset follows a Geometric Brownian Motion (GBM) process with zero drift. Therefore, the GKYZ volatility estimator tends to overestimate the volatility when the drift is different from zero. However, for a GBM process, this estimator is eight times more efficient than the close-to-close volatility estimator.
Exponential Weighted Moving Average
The Exponentially Weighted Moving Average (EWMA) is a quantitative or statistical measure used to model or describe a time series. The EWMA is widely used in finance, with the main applications being technical analysis and volatility modeling.
The moving average is designed such that older observations are given lower weights. The weights decrease exponentially as the data point gets older – hence the name exponentially weighted.
The only decision a user of the EWMA must make is the parameter lambda. The parameter decides how important the current observation is in the calculation of the EWMA. The higher the value of lambda, the more closely the EWMA tracks the original time series.
Standard Deviation of Log Returns
This is the simplest calculation of volatility. It's the standard deviation of ln(close/close(1)).
Pseudo GARCH(2,2)
This is calculated using a short- and long-run mean of variance multiplied by ?.
?avg(var;M) + (1 ? ?) avg(var;N) = 2?var/(M+1-(M-1)L) + 2(1-?)var/(M+1-(M-1)L)
Solving for ? can be done by minimizing the mean squared error of estimation; that is, regressing L^-1var - avg(var; N) against avg(var; M) - avg(var; N) and using the resulting beta estimate as ?.
Average True Range
The average true range (ATR) is a technical analysis indicator, introduced by market technician J. Welles Wilder Jr. in his book New Concepts in Technical Trading Systems, that measures market volatility by decomposing the entire range of an asset price for that period.
The true range indicator is taken as the greatest of the following: current high less the current low; the absolute value of the current high less the previous close; and the absolute value of the current low less the previous close. The ATR is then a moving average, generally using 14 days, of the true ranges.
True Range Double
A special case of ATR that attempts to correct for volatility skew.
Standard Deviation
Standard deviation is a statistic that measures the dispersion of a dataset relative to its mean and is calculated as the square root of the variance. The standard deviation is calculated as the square root of variance by determining each data point's deviation relative to the mean. If the data points are further from the mean, there is a higher deviation within the data set; thus, the more spread out the data, the higher the standard deviation.
Adaptive Deviation
By definition, the Standard Deviation (STD, also represented by the Greek letter sigma ? or the Latin letter s) is a measure that is used to quantify the amount of variation or dispersion of a set of data values. In technical analysis, we usually use it to measure the level of current volatility.
Standard Deviation is based on Simple Moving Average calculation for mean value. This version of standard deviation uses the properties of EMA to calculate what can be called a new type of deviation, and since it is based on EMA, we can call it EMA deviation. Additionally, Perry Kaufman's efficiency ratio is used to make it adaptive (since all EMA type calculations are nearly perfect for adapting).
The difference when compared to the standard is significant--not just because of EMA usage, but the efficiency ratio makes it a "bit more logical" in very volatile market conditions.
Median Absolute Deviation
The median absolute deviation is a measure of statistical dispersion. Moreover, the MAD is a robust statistic, being more resilient to outliers in a data set than the standard deviation. In the standard deviation, the distances from the mean are squared, so large deviations are weighted more heavily, and thus outliers can heavily influence it. In the MAD, the deviations of a small number of outliers are irrelevant.
Because the MAD is a more robust estimator of scale than the sample variance or standard deviation, it works better with distributions without a mean or variance, such as the Cauchy distribution.
For this indicator, a manual recreation of the quantile function in Pine Script is used. This is so users have a full inside view into how this is calculated.
Efficiency-Ratio Adaptive ATR
Average True Range (ATR) is a widely used indicator for many occasions in technical analysis. It is calculated as the RMA of the true range. This version adds a "twist": it uses Perry Kaufman's Efficiency Ratio to calculate adaptive true range.
Mean Absolute Deviation
The mean absolute deviation (MAD) is a measure of variability that indicates the average distance between observations and their mean. MAD uses the original units of the data, which simplifies interpretation. Larger values signify that the data points spread out further from the average. Conversely, lower values correspond to data points bunching closer to it. The mean absolute deviation is also known as the mean deviation and average absolute deviation.
This definition of the mean absolute deviation sounds similar to the standard deviation (SD). While both measure variability, they have different calculations. In recent years, some proponents of MAD have suggested that it replace the SD as the primary measure because it is a simpler concept that better fits real life.
█ Loxx's Expanded Source Types Included in Baseline Optimizer
This indicator allows you to select from 33 source types. They are as follows:
Close
Open
High
Low
Median
Typical
Weighted
Average
Average Median Body
Trend Biased
Trend Biased (Extreme)
HA Close
HA Open
HA High
HA Low
HA Median
HA Typical
HA Weighted
HA Average
HA Average Median Body
HA Trend Biased
HA Trend Biased (Extreme)
HAB Close
HAB Open
HAB High
HAB Low
HAB Median
HAB Typical
HAB Weighted
HAB Average
HAB Average Median Body
HAB Trend Biased
HAB Trend Biased (Extreme)
What are Heiken Ashi "better" candles?
Heiken Ashi "better" candles are a modified version of the standard Heiken Ashi candles, which are a popular charting technique used in technical analysis. Heiken Ashi candles help traders identify trends and potential reversal points by smoothing out price data and reducing market noise. The "better formula" was proposed by Sebastian Schmidt in an article published by BNP Paribas in Warrants & Zertifikate, a German magazine, in August 2004. The aim of this formula is to further improve the smoothing of the Heiken Ashi chart and enhance its effectiveness in identifying trends and reversals.
Standard Heiken Ashi candles are calculated using the following formulas:
Heiken Ashi Close = (Open + High + Low + Close) / 4
Heiken Ashi Open = (Previous Heiken Ashi Open + Previous Heiken Ashi Close) / 2
Heiken Ashi High = Max (High, Heiken Ashi Open, Heiken Ashi Close)
Heiken Ashi Low = Min (Low, Heiken Ashi Open, Heiken Ashi Close)
The "better formula" modifies the standard Heiken Ashi calculation by incorporating additional smoothing, which can help reduce noise and make it easier to identify trends and reversals. The modified formulas for Heiken Ashi "better" candles are as follows:
Better Heiken Ashi Close = (Open + High + Low + Close) / 4
Better Heiken Ashi Open = (Previous Better Heiken Ashi Open + Previous Better Heiken Ashi Close) / 2
Better Heiken Ashi High = Max (High, Better Heiken Ashi Open, Better Heiken Ashi Close)
Better Heiken Ashi Low = Min (Low, Better Heiken Ashi Open, Better Heiken Ashi Close)
Smoothing Factor = 2 / (N + 1), where N is the chosen period for smoothing
Smoothed Better Heiken Ashi Open = (Better Heiken Ashi Open * Smoothing Factor) + (Previous Smoothed Better Heiken Ashi Open * (1 - Smoothing Factor))
Smoothed Better Heiken Ashi Close = (Better Heiken Ashi Close * Smoothing Factor) + (Previous Smoothed Better Heiken Ashi Close * (1 - Smoothing Factor))
The smoothed Better Heiken Ashi Open and Close values are then used to calculate the smoothed Better Heiken Ashi High and Low values, resulting in "better" candles that provide a clearer representation of the market trend and potential reversal points.
Heiken Ashi "better" candles, as mentioned previously, provide a clearer representation of market trends and potential reversal points by reducing noise and smoothing out price data. When using these candles in conjunction with other technical analysis tools and indicators, traders can gain valuable insights into market behavior and make more informed decisions.
To effectively use Heiken Ashi "better" candles in your trading strategy, consider the following tips:
-Trend Identification: Heiken Ashi "better" candles can help you identify the prevailing trend in the market. When the majority of the candles are green (or another color, depending on your chart settings) and there are no or few lower wicks, it may indicate a strong uptrend. Conversely, when the majority of the candles are red (or another color) and there are no or few upper wicks, it may signal a strong downtrend.
-Trend Reversals: Look for potential trend reversals when a change in the color of the candles occurs, especially when accompanied by longer wicks. For example, if a green candle with a long lower wick is followed by a red candle, it could indicate a bearish reversal. Similarly, a red candle with a long upper wick followed by a green candle may suggest a bullish reversal.
-Support and Resistance: You can use Heiken Ashi "better" candles to identify potential support and resistance levels. When the candles are consistently moving in one direction and then suddenly change color with longer wicks, it could indicate the presence of a support or resistance level.
-Stop-Loss and Take-Profit: Using Heiken Ashi "better" candles can help you manage risk by determining optimal stop-loss and take-profit levels. For instance, you can place your stop-loss below the low of the most recent green candle in an uptrend or above the high of the most recent red candle in a downtrend.
-Confirming Signals: Heiken Ashi "better" candles should be used in conjunction with other technical indicators, such as moving averages, oscillators, or chart patterns, to confirm signals and improve the accuracy of your analysis.
In this implementation, you have the choice of AMA, KAMA, or T3 smoothing. These are as follows:
Kaufman Adaptive Moving Average (KAMA)
The Kaufman Adaptive Moving Average (KAMA) is a type of adaptive moving average used in technical analysis to smooth out price fluctuations and identify trends. The KAMA adjusts its smoothing factor based on the market's volatility, making it more responsive in volatile markets and smoother in calm markets. The KAMA is calculated using three different efficiency ratios that determine the appropriate smoothing factor for the current market conditions. These ratios are based on the noise level of the market, the speed at which the market is moving, and the length of the moving average. The KAMA is a popular choice among traders who prefer to use adaptive indicators to identify trends and potential reversals.
Adaptive Moving Average
The Adaptive Moving Average (AMA) is a type of moving average that adjusts its sensitivity to price movements based on market conditions. It uses a ratio between the current price and the highest and lowest prices over a certain lookback period to determine its level of smoothing. The AMA can help reduce lag and increase responsiveness to changes in trend direction, making it useful for traders who want to follow trends while avoiding false signals. The AMA is calculated by multiplying a smoothing constant with the difference between the current price and the previous AMA value, then adding the result to the previous AMA value.
T3
The T3 moving average is a type of technical indicator used in financial analysis to identify trends in price movements. It is similar to the Exponential Moving Average (EMA) and the Double Exponential Moving Average (DEMA), but uses a different smoothing algorithm.
The T3 moving average is calculated using a series of exponential moving averages that are designed to filter out noise and smooth the data. The resulting smoothed data is then weighted with a non-linear function to produce a final output that is more responsive to changes in trend direction.
The T3 moving average can be customized by adjusting the length of the moving average, as well as the weighting function used to smooth the data. It is commonly used in conjunction with other technical indicators as part of a larger trading strategy.
█ Giga Kaleidoscope Modularized Trading System
Core components of an NNFX algorithmic trading strategy
The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend
3. Confirmation 1 - a technical indicator used to identify trends
4. Confirmation 2 - a technical indicator used to identify trends
5. Continuation - a technical indicator used to identify trends
6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown
7. Exit - a technical indicator used to determine when a trend is exhausted
8. Metamorphosis - a technical indicator that produces a compound signal from the combination of other GKD indicators*
*(not part of the NNFX algorithm)
What is Volatility in the NNFX trading system?
In the NNFX (No Nonsense Forex) trading system, ATR (Average True Range) is typically used to measure the volatility of an asset. It is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. ATR is calculated by taking the average of the true range values over a specified period.
True range is calculated as the maximum of the following values:
-Current high minus the current low
-Absolute value of the current high minus the previous close
-Absolute value of the current low minus the previous close
ATR is a dynamic indicator that changes with changes in volatility. As volatility increases, the value of ATR increases, and as volatility decreases, the value of ATR decreases. By using ATR in NNFX system, traders can adjust their stop loss and take profit levels according to the volatility of the asset being traded. This helps to ensure that the trade is given enough room to move, while also minimizing potential losses.
Other types of volatility include True Range Double (TRD), Close-to-Close, and Garman-Klass
What is a Baseline indicator?
The baseline is essentially a moving average, and is used to determine the overall direction of the market.
The baseline in the NNFX system is used to filter out trades that are not in line with the long-term trend of the market. The baseline is plotted on the chart along with other indicators, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR).
Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards, only long trades are taken, and if the baseline is sloping downwards, only short trades are taken. This approach helps to ensure that trades are in line with the overall trend of the market, and reduces the risk of entering trades that are likely to fail.
By using a baseline in the NNFX system, traders can have a clear reference point for determining the overall trend of the market, and can make more informed trading decisions. The baseline helps to filter out noise and false signals, and ensures that trades are taken in the direction of the long-term trend.
What is a Confirmation indicator?
Confirmation indicators are technical indicators that are used to confirm the signals generated by primary indicators. Primary indicators are the core indicators used in the NNFX system, such as the Average True Range (ATR), the Moving Average (MA), and the Relative Strength Index (RSI).
The purpose of the confirmation indicators is to reduce false signals and improve the accuracy of the trading system. They are designed to confirm the signals generated by the primary indicators by providing additional information about the strength and direction of the trend.
Some examples of confirmation indicators that may be used in the NNFX system include the Bollinger Bands, the MACD (Moving Average Convergence Divergence), and the MACD Oscillator. These indicators can provide information about the volatility, momentum, and trend strength of the market, and can be used to confirm the signals generated by the primary indicators.
In the NNFX system, confirmation indicators are used in combination with primary indicators and other filters to create a trading system that is robust and reliable. By using multiple indicators to confirm trading signals, the system aims to reduce the risk of false signals and improve the overall profitability of the trades.
What is a Continuation indicator?
In the NNFX (No Nonsense Forex) trading system, a continuation indicator is a technical indicator that is used to confirm a current trend and predict that the trend is likely to continue in the same direction. A continuation indicator is typically used in conjunction with other indicators in the system, such as a baseline indicator, to provide a comprehensive trading strategy.
What is a Volatility/Volume indicator?
Volume indicators, such as the On Balance Volume (OBV), the Chaikin Money Flow (CMF), or the Volume Price Trend (VPT), are used to measure the amount of buying and selling activity in a market. They are based on the trading volume of the market, and can provide information about the strength of the trend. In the NNFX system, volume indicators are used to confirm trading signals generated by the Moving Average and the Relative Strength Index. Volatility indicators include Average Direction Index, Waddah Attar, and Volatility Ratio. In the NNFX trading system, volatility is a proxy for volume and vice versa.
By using volume indicators as confirmation tools, the NNFX trading system aims to reduce the risk of false signals and improve the overall profitability of trades. These indicators can provide additional information about the market that is not captured by the primary indicators, and can help traders to make more informed trading decisions. In addition, volume indicators can be used to identify potential changes in market trends and to confirm the strength of price movements.
What is an Exit indicator?
The exit indicator is used in conjunction with other indicators in the system, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR), to provide a comprehensive trading strategy.
The exit indicator in the NNFX system can be any technical indicator that is deemed effective at identifying optimal exit points. Examples of exit indicators that are commonly used include the Parabolic SAR, the Average Directional Index (ADX), and the Chandelier Exit.
The purpose of the exit indicator is to identify when a trend is likely to reverse or when the market conditions have changed, signaling the need to exit a trade. By using an exit indicator, traders can manage their risk and prevent significant losses.
In the NNFX system, the exit indicator is used in conjunction with a stop loss and a take profit order to maximize profits and minimize losses. The stop loss order is used to limit the amount of loss that can be incurred if the trade goes against the trader, while the take profit order is used to lock in profits when the trade is moving in the trader's favor.
Overall, the use of an exit indicator in the NNFX trading system is an important component of a comprehensive trading strategy. It allows traders to manage their risk effectively and improve the profitability of their trades by exiting at the right time.
What is an Metamorphosis indicator?
The concept of a metamorphosis indicator involves the integration of two or more GKD indicators to generate a compound signal. This is achieved by evaluating the accuracy of each indicator and selecting the signal from the indicator with the highest accuracy. As an illustration, let's consider a scenario where we calculate the accuracy of 10 indicators and choose the signal from the indicator that demonstrates the highest accuracy.
The resulting output from the metamorphosis indicator can then be utilized in a GKD-BT backtest by occupying a slot that aligns with the purpose of the metamorphosis indicator. The slot can be a GKD-B, GKD-C, or GKD-E slot, depending on the specific requirements and objectives of the indicator. This allows for seamless integration and utilization of the compound signal within the GKD-BT framework.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v2.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
6. GKD-M - Metamorphosis module (Metamorphosis, Number 8 in the NNFX algorithm, but not part of the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data to A backtest module wherein the various components of the GKD system are combined to create a trading signal.
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Full GKD Backtest
Baseline: Hull Moving Average
Volatility/Volume: Hurst Exponent
Confirmation 1: Kase Peak Oscillator
Confirmation 2: uf2018
Continuation: Vortex
Exit: Rex Oscillator
Metamorphosis: Baseline Optimizer as shown on the chart above
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, GKD-M, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD system.
█ Giga Kaleidoscope Modularized Trading System Signals
Standard Entry
1. GKD-C Confirmation gives signal
2. Baseline agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Volatility/Volume agrees
1-Candle Standard Entry
1a. GKD-C Confirmation gives signal
2a. Baseline agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
Next Candle
1b. Price retraced
2b. Baseline agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Baseline Entry
1. GKD-B Basline gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Volatility/Volume agrees
7. Confirmation 1 signal was less than 'Maximum Allowable PSBC Bars Back' prior
1-Candle Baseline Entry
1a. GKD-B Baseline gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSBC Bars Back' prior
Next Candle
1b. Price retraced
2b. Baseline agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Volatility/Volume Entry
1. GKD-V Volatility/Volume gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Baseline agrees
7. Confirmation 1 signal was less than 7 candles prior
1-Candle Volatility/Volume Entry
1a. GKD-V Volatility/Volume gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSVVC Bars Back' prior
Next Candle
1b. Price retraced
2b. Volatility/Volume agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Baseline agrees
Confirmation 2 Entry
1. GKD-C Confirmation 2 gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Volatility/Volume agrees
6. Baseline agrees
7. Confirmation 1 signal was less than 7 candles prior
1-Candle Confirmation 2 Entry
1a. GKD-C Confirmation 2 gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSC2C Bars Back' prior
Next Candle
1b. Price retraced
2b. Confirmation 2 agrees
3b. Confirmation 1 agrees
4b. Volatility/Volume agrees
5b. Baseline agrees
PullBack Entry
1a. GKD-B Baseline gives signal
2a. Confirmation 1 agrees
3a. Price is beyond 1.0x Volatility of Baseline
Next Candle
1b. Price inside Goldie Locks Zone Minimum
2b. Price inside Goldie Locks Zone Maximum
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Continuation Entry
1. Standard Entry, 1-Candle Standard Entry, Baseline Entry, 1-Candle Baseline Entry, Volatility/Volume Entry, 1-Candle Volatility/Volume Entry, Confirmation 2 Entry, 1-Candle Confirmation 2 Entry, or Pullback entry triggered previously
2. Baseline hasn't crossed since entry signal trigger
4. Confirmation 1 agrees
5. Baseline agrees
6. Confirmation 2 agrees
█ Connecting to Backtests
All GKD indicators are chained indicators meaning you export the value of the indicators to specialized backtest to creat your GKD trading system. Each indicator contains a proprietary signal generation algo that will only work with GKD backtests. You can find these backtests using the links below.
GKD-BT Giga Confirmation Stack Backtest:
GKD-BT Giga Stacks Backtest:
GKD-BT Full Giga Kaleidoscope Backtest:
GKD-BT Solo Confirmation Super Complex Backtest:
GKD-BT Solo Confirmation Complex Backtest:
GKD-BT Solo Confirmation Simple Backtest:
NoanFam IndicatorNoan Indicator: A Simple Manual for Beginners
Welcome to the Noan Indicator manual!
This guide will help you understand how to use the Noan Indicator for your trading needs, even if you have little to no knowledge of trading.
The Noan Indicator is a versatile tool that can be applied to different trading strategies, such as 123 patterns, trend breaks, or sudden large price movements.
How to Start the Indicator:
1. Determine 2% risk:
The first step is to determine the risk you're willing to take for a particular trade.
We recommend a 2% risk, meaning you should not risk more than 2% of your account balance on any single trade.
a. Enter Portfolio Size: Enter the total value of your trading portfolio. This value will be used to calculate the trade size based on the percentage risk you're willing to take.
b. Enter Leverage Multiplier: Enter the leverage multiplier you are using for your trades. This value will be used to adjust the trade size accordingly.
c. Split amount to trade (Entry-DCA): Select the desired percentage split for your initial trade entry and dollar-cost averaging (DCA) trade. You can choose between 60/40, 50/50, or 100% (no DCA).
2. Identify a trade opportunity:
Analyze the market, using technical and/or fundamental analysis, to identify potential trade opportunities. Look for patterns, trends, support and resistance levels, and other indicators that signal the right time to enter a trade. Remember that the Noan Indicator is designed to assist you in managing risk, and it is not a standalone trading strategy. Always use your own research and judgement when making trading decisions.
After conducting your research and finding a good point to enter, input the trade type (long or short) into the indicator.
3. Set entry price:
The entry price should be based on your analysis and represents the price at which you would like to enter the market.
It is essential to set a realistic entry price, taking into consideration the current market conditions and price action.
After conducting your own research and identifying a good entry point for a long or short trade, input the Entry Price into the Noan Indicator.
4. Preferences:
The Noan indicator is set default with a Dollar Cost Averaging (DCA) area.
You can choose to disable this feature if desired.
Also an option to choose whether you want to see the values ($) or percentages (%) for the different levels in the indicator.
5. Select a predefined Trail Stop Loss:
If a trailing stop loss option is selected in the settings, a line will be displayed on the chart, showing the level where the stop loss will be moved based on the chosen option.
Protect your investment and help manage risk during the trade.
It allows you to limit your losses while allowing your profits to run.
Move Stop Loss to Average Entry: The stop loss moves to your average entry price (considering DCA) once the market reaches a specific level.
Move Stop Loss to Entry: The stop loss moves to your initial entry price.
Move Stop Loss to TP1 after DCA: The stop loss moves to the first Take Profit level after executing the DCA.
Move Stop Loss to TP1, TP2, TP3, or LTPR: The stop loss moves to the specified Take Profit level or Last Trailing Profit Range.
6. Set alerts:
Set up alerts for when the indicator reaches specific levels or when other conditions are met.
This will help you stay informed about potential trading opportunities.
To set up alerts using the Noan Indicator v2.7.0:
a. Right-click on the chart and select "Add Alert" or click the "Alerts" tab in the left sidebar and click the "+" button.
b. In the "Condition" dropdown menu, select the "Noan Indicator v2.7.0" script.
c. Choose the alert type by selecting a condition from the available options (e.g., crossing, greater than, less than, etc.).
d. Specify the alert settings, such as the alert name, message, and frequency.
e. Click "Create" to create the alert.
What Makes This Indicator Unique?
The Noan Indicator is designed to suit various trading strategies and can help confirm a setup after thorough research or upon reaching a Point of Interest (POI). By inputting a pre-examined entry price, the indicator will display different potential levels for Take Profits (TPs), Dollar-Cost Averaging (DCA), and Stop Loss (SL) areas. These levels are based on fixed percentages derived from data collected from thousands of trades.
If the different levels correspond well with past price levels, this can provide an extra point of confirmation for your trading decision. The TPs, DCA, and SL areas at these levels are structured according to the Noan Theory, further enhancing the effectiveness of the indicator.
In summary, the Noan Indicator is a versatile and powerful tool that can help traders of all levels make more informed decisions, regardless of their trading strategy. By following this simple manual, you can start using the Noan Indicator to improve your trading performance.
*Backtesting System ⚉ ＯＶＥＲＶＩＥＷ ⚉
One of the best Systems for Backtesting your Strategies.
Incredibly flexible, simple, fast and feature-rich system — will solve most of your queries without much effort.
Many systems for setting StopLoss, TakeProfit, Risk Management and advanced Filters.
All you need to do is plug in your indicator and start Backtesting .
I intentionally left the option to use my System on Full Power before you load your indicator into it.
The system uses the built-in simple and popular moving average crossover signal for this purpose. (EMA 50 & 200).
Also Highly Recommend that you Fully use ALL of the features of this system so that you understand how they work before you ask questions.
Also tried to leave TIPS for each feature everywhere, read Tips, activate them and see how they work.
But before you use this system, I Recommend you to read the following description in Full.
—————— How to connect your indicator in 2 steps:
Adapt your indicator by adding only 2 lines of code and then connect it to this Backtesting System.
Step 1 — Create your connector, For doing so:
• 1 — Find or create in your indicator where are the conditions printing the Long-Buy and Short-Sell signals.
• 2 — Create an additional plot as below
I'm giving an example with a Two moving averages cross.
Please replicate the same methodology for your indicator wether it's a MACD, RSI , Pivots, or whatever indicator with Clear Buy and Sell conditions.
//@version=5
indicator('Moving Average Cross', overlay = true)
MA200 = ta.𝚎𝚖𝚊(close, 200)
MA50 = ta.𝚎𝚖𝚊(close, 50)
// Generate Buy and Sell conditions
buy = ta.crossover (MA200, MA50)
sell = ta.crossunder (MA200, MA50)
plot(MA200, color=color.green)
plot(MA50 , color=color.red )
bgcolor(color = buy ? color.green : sell ? color.red : na, title='SIGNALS')
// ———————————————— SIGNAL FOR SYSTEM ————————————————
Signal = buy ? +1 : sell ? -1 : 0
plot(Signal, title='🔌Connector🔌', display = display.none)
// —————— 🔥 The Backtesting System expects the value to be exactly +1 for the 𝚋𝚞𝚕𝚕𝚒𝚜𝚑 signal, and -1 for the 𝚋𝚎𝚊𝚛𝚒𝚜𝚑 signal
Basically, I identified my Buy & Sell conditions in the code and added this at the bottom of my indicator code
Now you can connect your indicator to the Backtesting System using the Step 2
Step 2 — Connect the connector
• 1 — Add your updated indicator to a TradingView chart and Add the Backtesting System as well to the SAME chart
• 2 — Open the Backtesting System settings and in the External Source field select your 🔌Connector🔌 (which comes from your indicator)
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𝐄𝐱𝐭𝐞𝐫𝐧𝐚𝐥 𝐒𝐨𝐮𝐫𝐜𝐞 — Select your indicator. Add your indicator by following the 2 steps described above and select it in the menu. To familiarize yourself with the system until you select your indicator, you will have an in-built strategy of crossing the two moving EMA's of 50 and 200.
Long Deals — Enable/Disable Long Deals.
Short Deals — Enable/Disable Short Deals.
Wait End Deal — Enable/Disable waiting for a trade to close at Stop Loss/Take Profit. Until the trade closes on the Stop Loss or Take Profit, no new trade will open.
Reverse Deals — To force the opening of a trade in the opposite direction.
ReEntry Deal — Automatically open the same new deal after the deal is closed.
ReOpen Deal — Reopen the trade if the same signal is received. For example, if you are already in the long and a new signal is received in the long, the trade will reopen. * Does not work if Wait End Deal is enabled.
𝐓𝐚𝐤𝐞 𝐏𝐫𝐨𝐟𝐢𝐭:
None — Disables take profit. Useful if you only want to use dynamic stoplosses such as MA, Fast-Trailing, ATR Trail.
FIXED ％ — Fixed take profit in percent.
FIXED ＄ — Fixed Take in Money.
ATR — Fixed Take based on ATR.
R:R — Fixed Take based on the size of your stop loss. For example, if your stop is 10% and R:R=1, then the Take would be 10%. R:R=3 Take would be 30%, etc.
HH / LL — Fixed Take based on the previous maximum/minimum (extremum).
𝐒𝐭𝐨𝐩 𝐋𝐨𝐬𝐬:
None — Disables Stop Loss. Useful if you want to work without a stop loss. *Be careful if Wait End Deal is enabled, the trade may not close for a long time until it reaches the Take.
FIXED ％ — Fixed Stop in percent.
FIXED ＄ — Fixed Stop in Money.
TRAILING — Dynamic Trailing Stop like on the stock exchanges.
FAST TRAIL — Dynamic Fast Trailing Stop moves immediately in profit and stays in place if the price stands still or the price moves in loss.
ATR — Fixed Stop based on the ATR.
ATR TRAIL — Dynamic Trailing Stop based on the ATR.
LO / HI — A Fixed Stop based on the last Maximum/Minimum extemum. Allows you to place a stop just behind or above the low/high candle.
MA — Dynamic Stop based on selected Moving Average. * You will have 8 types of MA (EMA, SMA, HMA, etc.) to choose from, but you can easily add dozens of other MAs, which makes this type of stop incredibly flexible.
Add ％ — If true, then with the "𝗦𝘁𝗼𝗽 ％" parameter you can add percentages to any of the current SL. Can be especially useful when using Stop - 𝗔𝗧𝗥 or 𝗠𝗔 or 𝗟𝗢/𝗛𝗜. For example with 𝗟𝗢/𝗛𝗜 to put a stop for the last High/Low and add 0.5% additional Stoploss.
Fixed R:R — If the stop loss is Dynamic (Trailing or MA) then if R:R true can also be made Dynamic * Use it carefully, the function is experimental.
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A unique method of constructing intermediate Take Profit Levels will allow you to select up to 5 intermediate Take Profit Levels and one intermediate Stop Loss.
Intermediate Take Profit Levels are perfectly calculated into 5 equal parts in the form of levels from the entry point to the final Take Profit target.
All you need to do is to choose the necessary levels for fixing and how much you want to fix at each level as a percentage. For example, TP 3 will always be exactly between the entry point and the Take Profit target. And the value of TP 3 = 50 will close 50% of the amount of the remaining size of the position.
Note: all intermediate SL/TP are closed from the remaining position amount and not from the initial position size, as TV does by default.
SL 0 Position — works in the same way as TP 1-5 but it's Stop. With this parameter you can set the position where the intermediate stop will be set.
Breakeven on TP — When activated, it allows you to put the stop loss at Breakeven after the selected TP is reached. For this function to work as it should - you need to activate an intermediate Take. For example, if TP 3 is activated and Breakeven on TP = 3, then after the price reaches this level, the Stop loss will go to Breakeven.
* This function will not work with Dynamic Stoplosses, because it simply does not make sense.
CoolDown # Bars — When activated, allows you to add a delay before a new trade is opened. A new trade after CoolDown will not be opened until # bars pass and a new signal appears.
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Powerful time filter code that allows you to filter data based on specific time zones, dates, and session days. This code is ideal for those who need to analyze data from different time zones and weed out irrelevant data.
With Time Filter, you can easily set the starting and ending time zones by which you want to filter the data.
You can also set a start and end date for your data and choose which days of the week to include in the analysis. In addition, you can specify start and end times for a specific session, allowing you to focus your analysis on specific time periods.
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Signal Filters — allows you to easily customize and optimize your trading strategies based on 10 filters.
Each filter is designed to help you weed out inaccurate signals to minimize your risks.
Let's take a look at their features:
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Risk management tools that allow you to set the maximum number of losing trades in a row, a limit on the number of trades per day or week and other filters.
Loss Streak — Set Max number of consecutive loss trades.
Win Streak — Max Winning Streak Length.
Row Loss InDay — Max of consecutive days with a loss in a row.
DrawDown ％ — Max DrawDown (in % of strategy equity).
InDay Loss ％ — Set Max Intraday Loss.
Daily Trades — Limit the number of MAX trades per day.
Weekly Trades — Limit the number of MAX trades per week.
* 🡅 I would Not Recommend using these functions without understanding how they work.
Order Size — Position Size
• NONE — Use the default position size settings in Tab "Properties".
• EQUITY — The amount of the allowed position as a percentage of the initial capital.
• Use Net Profit — On/Off the use of profit in the following trades. *Only works if the type is EQUITY.
• SIZE — The size of the allowed position in monetary terms.
• Contracts — The size of the allowed position in the contracts. 1 Сontract = Сurrent price.
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It is important to note that I have never worked with Backtesting and the functions associated with them before.
It took me about a month of slow work to build this system.
I want to say Big Thanks:
• The PineScripters🌲 group, the guys suggested how to implement some features. Especially @allanster
• Thanks to all those people who share their developments for free on TV and not only.
• I also thank myself for not giving up and finishing the project, and not trying to monetize the system by selling it. * Although I really want the money :)
I tried hard to make it as fast and convenient as possible for everyone who will use my code.
That's why I didn't use any libraries and dozens of heavy functions, and I managed to fit in 8+-functions for the whole code.
Absolutely every block of code I tried to make full-fledged modular, that it was easy to import/edit for myself (you).
I have abused the Ternary Pine operator a little (a lot) so that the code was as compact as possible.
Nevertheless, I tried very hard to keep my code very understandable even for beginners.
At last I managed to write 500 lines of code, making it one of the fastest and most feature-rich systems out there.
I hope everyone enjoys my work.
Put comments and write likes.
Kioseff Trading - AI-Optimized RSIAI-Optimized RSI
Introducing AI-Optimized RSI: a streamlined solution for traders of any skill level seeking to rapidly test and optimize RSI. Capable of analyzing thousands of strategies, this tool cuts through the complexity to identify the most profitable, reliable, or efficient approaches.
Paired with TradingView's native backtesting capabilities, the AI-Optimized RSI learns from historical performance data. Set up is easy for all skill levels, and it makes fine-tuning trading alerts and RSI straightforward.
Features
Purpose : Uncover optimal RSI settings and entry levels with precision. Say goodbye to random guesses and arbitrary indicator use—this tool provides clear direction based on data.
Target Performance : You set the goal, and AI-RSI seeks it out, whether it's maximizing profits, efficient trading, or achieving the highest win rate.
AI-Powered : With intelligent AI recommendations, the tool dynamically fine-tunes your RSI approach, steering you towards ideal strategy performance.
Rapid Testing : Evaluate thousands of RSI strategies.
Dual Direction : Perfect both long and short RSI strategies with equal finesse.
Deep Insights : Access detailed metrics including profit factor, PnL, win rate, trade counts, and more, all within a comprehensive strategy script.
Instant Alerts : Set alerts and trade.
Full Customization : Test and optimize all RSI settings, including cross levels, profit targets and stop losses.
Simulated Execution : Explore the impact of limit orders and other trade types through simulation.
Integrative Capability : Combine your own custom indicators or others from the TradingView community for a personalized optimization experience.
Flexible Timeframes : Set your optimization and backtesting to any date range.
Key Settings
The image above shows explanations for a list of key settings for the optimizer.
Direction : This setting controls trade direction: Long or Short.
Entry Condition : Define RSI entry: Select whether to trigger trades on RSI crossunders or crossovers.
RSI Lengths Range : Choose the range of RSI periods to test and find the best one.The AI will find the best RSI period for you.
RSI Cross Range : Set the range for RSI levels where crosses trigger trade signals. The AI will find the best level for you.
Combinations : Select how many RSI strategies to compare.
Optimization Type : Choose the goal for optimization and the AI: profit, win rate, or efficiency.
Profit Target : Set your profit target with this setting.
Stop Loss : Decide your maximum allowable loss (stop loss) per trade.
Limit Order : Specify whether to include limit orders in the strategy.
Stop Type : Choose your stop strategy: a fixed stop loss or a trailing stop.
How to: Find the best RSI for trading
It's important to remember that merely having the AI-Optimized RSI on your chart doesn't automatically provide you with the best strategy. You need to follow the AI's guidance through an iterative process to discover the optimal RSI settings and strategy.
1.Starting Your Strategy Setup
Begin by deciding your goals for each trade: your profit target and stop loss. You'll also choose how to manage your stops – whether they stay put (fixed) or move with the price (trailing), and whether you want to exit trades at a specific price (limit orders). Keep the initial settings for RSI lengths and cross ranges at their default to give the tool a broad testing field. The AI's guidance will refine these settings to pinpoint the most effective ones through a process of comprehensive testing.
The image above shows our chart prior to any optimization efforts.
Note: the settings shown above in the key settings section will be used to start our demonstration.
2. Follow AI’s suggestions
Optimization Prompt: After loading your strategy, the indicator will prompt you to change the RSI length range and RSI level range to a better performing range.
Continue changing the RSI length range and RSI level range to match the indicator's suggestions until "Best Found" is displayed!
The image above shows results after we applied the tool’s suggestions. New suggestions have appeared, and we will continue to apply them.
Continue to adjust settings as recommended by the optimizer. If no better options are found, the optimizer will suggest increasing the number of combinations. Repeat this process until the optimizer indicates that the optimal setting has been identified.
Success! With the "Best Found" notification, an optimized RSI is now active. The AI will keep refining the strategy based on ongoing performance, ensuring continuous optimization.
AI Mode
AI Mode incorporates Heuristic-Based Adaptive Learning to fine-tune trading strategies in a continuous manner. This feature consists of two main components:
Heuristic-Based Decision Making: The algorithm evaluates multiple RSI-based trading strategies using specific metrics such as Profit and Loss (PNL), Win Rate, and Most Efficient Profit. These metrics act as heuristics to assist the algorithm in identifying suitable strategies for trade execution.
Online Learning: The algorithm updates the performance evaluations of each strategy based on incoming market data. This enables the system to adapt to current market conditions.
Incorporating both heuristic-based decision-making and online learning, this feature aims to provide a framework for trading strategy optimization.
Settings
AI Mode Aggressiveness:
Description: The "AI Mode Aggressiveness" setting allows you to fine-tune the AI's trading behavior. This setting ranges from “Low” to “High”, with “High” indicating a more assertive trading approach.
Functionality: This feature filters trading strategies based on a proprietary evaluation method. A higher setting narrows down the strategies that the AI will consider, leaning towards more aggressive trading. Conversely, a lower setting allows for a more conservative approach by broadening the pool of potential strategies.
Adaptive Learning Aggressiveness:
Description: When Adaptive Learning is enabled, the "Adaptive Learning Aggressiveness" setting controls how dynamically the AI adapts to market conditions using selected performance metrics.
Functionality: This setting impacts the AI's responsiveness to shifts in strategy performance. By adjusting this setting, you can control how quickly the AI moves away from strategies that may have been historically successful but are currently underperforming, towards strategies that are showing current promise.
Optimization
Trading system optimization is immensely advantageous when executed with prudence.
Technical-oriented, mechanical trading systems work when a valid correlation is methodical to the extent that an objective, precisely-defined ruleset can consistently exploit it. If no such correlation exists, or a technical-oriented system is erroneously designed to exploit an illusory correlation (absent predictive utility), the trading system will fail.
Evaluate results practically and test parameters rigorously after discovery. Simply mining the best-performing parameters and immediately trading them is unlikely a winning strategy. Put as much effort into testing strong-performing parameters and building an accompanying system as you would any other trading strategy. Automated optimization involves curve fitting - it's the responsibility of the trader to validate a replicable sequence or correlation and the trading system that exploits it.
Ichi-Price WaveWelcome to the Ichi-Price Wave. This indicator is designed for day trading options contracts for any ticker, using a number of indicators — Ichimoku Cloud, Volume-Weighted Average Price, Stochastic Relative Strength Index, Exponential Moving Average (13/48) — and calculating how they interact with each other to provide entry and exit signals for both Calls and Puts on normal days. ****Read the Important Information section before opening any positions based on this indicator. (Also *NFA)
The general concept is that you, the trader, are a Surfer 🏄🏾 who rides the best waves in deep water until it gets dangerous.
Emoji storyline: The 🏄🏾 emoji (Call or Put, depending on the color of its Green or Red label, respectively) indicates an upcoming *potential* entry that, for a number of reasons, may be disregarded. (See: Important Information section below). And just as there are no certainties in the stock market itself, the tiered exit signals are ranked by low 🐬, medium 🦈 and high risk 🦑 tolerance. (In other words, it's relatively safe to surf with dolphins around, but there's the off chance they even strike trainers and become aggressive. It's more dangerous to swim with sharks. And on the unlikely, rare occasion you see a literal, giant, mythical, ship destroying Kraken 😬 ... you definitely need to get out of the water.
Surfing for as long as possible reaps the greatest rewards — but risk/reward are to be considered for entries and exits. Exiting every time you see a 🐬 (E1) should secure profits nearly 100% of the time, but they'll be very minimal. Whereas surfing til you reach a Kraken 🦑 (which will not even appear on most Price Wave cycles) would reap the most rewards. (NFA: I recommend considering sharks 🦈 as an exit point for the majority of positions, and perhaps only keeping a few runners open with the hopes of finding that shiny Kraken. (On the non-Emoji chart, the low, medium and high risk exits are named E1, E2 and E3, respectively. Got to the indicator's Settings > Inputs > then toggle EMOJIs ON/OFF)
Boring stuff: The entry 🏄🏾 signals are triggered by multiple conditions that must be all true. For Call entries, one of the necessary conditions is that the RSI's K must be maximum 10 (this can be changed in default). This, along with another condition where current price must be below the VWAP Lower Bound 1, serves as a great reference point showing the stock price is currently uncomfortable where it is and may likely soon snap back closer to the VWAP, perhaps even to the other side due to a pendulum effect.
Important information
Relying on those two factors for setting entry and exit points are great for normal days. (Normal, as in the ticker price bounces within a channel (e.g., ≤3% + or -) that's trending slightly bullish or bearish depending on greater market trend). But there are abnormal days where news catalysts (e.g., CPI data, CEO scandals, unexpected company data release, etc.) trigger FOMO and FUD, ultimately rendering the logic behind most indicators non applicable (e.g., RSI's "buy when oversold"). On the chart, this indicator accounts for this with two measures:
One, you should only "Surf" in the water. That is, there are two bands — Shallow and Deep Water. Any "Surf" emojis where price action is outside of the water should be ignored**. Two, there are additional EMOJIs that show you "Bearish trend" ⛈ and "Bullish trend ☀️. (Story time again: You obviously shouldn't surf in thunder and lightning. But also, surfing in the blistering sun with no clouds in the sky during a heatwave is also dangerous to your health.)
You can use these two measures to disregard the "surfers" suggesting you join them in opening a position in the suggested direction. And surfers followed by Cloud EMOJIs — 🌤️ (Put) or 🌧️ (Call) — can be used as "perfect entry" points. (The clouds represent weather being less extreme and better for surfing).
(**While these should mostly be ignored, these have not been muted because there is the possibility of a very strong turn around if you happen to catch the last one (which is not ideal for risk-averse traders). Use other indicators, such as the MACD and trend lines, to find potential bottoms (or tops) as price action plunges (or soars) due to abnormal news circumstances.)
Entry and exit buffers
At the beginning of each day, most indicators usually are not immediately calibrated correctly due to premarket trading and open market (at least to the degree that the day's sentiment can be best read from them due to the amount of volatility). What I recommend when using this indicator is disregarding signals during the first 15 minutes (or possibly 30 minutes) of market open to get the best results. And also, considering this indicator is meant for day trading (i.e., not holding positions overnight), disregarding ENTRY signals for the last 45 minutes of the trading day could give yourself enough buffer on the back end for exiting comfortably.
RSI entry
Preparing for an entry when you see a surfer is recommended, but actually opening the position when you see a 🌤️ (Put) or 🌧️ (Call) would yield best results and avoid misfires — particularly when those two cloud EMOJIs are signaled when the RSI is overbought and K is at least 95 (Puts), or oversold and K at maximum 5 (Calls). (Story time logic: The cloud eclipsing the Sun means it's cooling off and better for surfing. And the rain cloud no longer having lightning means the "bearish" storm is possibly soon over).
Delta and the Greeks
You should experiment yourself, but keep in mind that this is for capitalizing off of a day's minor price swings (≤3% + or -). Entering a same day expiry contract that's deep OTM is not going to work with this indicator (even if you enter at a surfer 🏄🏾 and exit at a Kraken 🦑) because the price wave from one end to the other won't be enough to compensate for the other Greeks working against you. Use another indicator (or insider knowledge ... Just kidding, that's illegal, don't do that) if you want to buy those kind of contracts.
I personally purchase contracts w/ minimum 80% Implied Volatility and somewhere between 20-40 Delta. Having a nice range for yourself with these factors, depending also on the size of your own portfolio and the risk tolerance you have, will determine how much you're able to capitalize off successful entry and exits.
Tips
• I set stop losses 5-10% depending on the ticker. (e.g., $TSLA's volatility may require SL closer to 10% whereas using it on $SPY, a 5% could suffice). This is in addition to ignoring entry signals that don't meet the aforementioned two requirements (i.e., it's risky to Surf in shallow water, and you shouldn't try to Surf at all outside of the water, ref. Band 2 and outside of Band 2). Remember, this is the stock market — not the casino. We rely on strategy and risk management — not hope.
• It's recommended you use time intervals ≤ 5 min. (I use 1 minute and 5 min)
• Liquidity . Using these signals on a ticker with low liquidity (particularly if you enter on the Ask side), can reduce your profits to 0% or even to a loss even if you have a perfect entry and exit. I always point to SPY as the optimal bid-ask spread, but keep that in mind.
What's with the name "Ichi-Price Wave"?
The "Ichi" gives credit to Japanese journalist Goichi Hosoda, whose indicator I used in conjunction with the 13/48 Exponential Moving Averages to create some of the exit signal conditions (e.g., E2🦈). That E2 condition is: Signal the first time the price intersects the Ichimoku conversion line *after* it has entered the VWAP UB/LB channel on one end and has exited on the opposite end). And it's named "Price Wave" because it's a literal price wave, which is where the fun surf narrative comes in. Also, "Price" doubles as me naming it after myself (in a less pretentious way). It's actually convenient that my last name is literally Price. Almost as if I was born for this. Nonetheless, this indicator is far more accurate in spotting directional changes than the free 13/48 cross, which oddly enough, influencers are charging for access. It's free, but the code is protected, for now at least.
Try it out on any ticker and look at how accurately it catches the tops and bottoms (keeping in mind to ignore misfires according to the two measures and also setting ~5-10% stop losses). And of course, use this in conjunction with other indicators. Ignoring all of my other emojis and simply setting surfer 🏄🏾 alerts could serve as additional confirmations for your personal strategy. Or you could simply enter at a surfer 🏄🏾 and exit when it reaches VWAP (or at least increase your Stop Loss to sell at break even if it doesn't reach). That strategy is the most conservative and would secure consistent gains). AND AGAIN, use your stop losses. Either it makes a move or it doesn't. Simply re-enter at a better point if necessary.
ONWAY Indicator PV6The ONWAY indicator is a comprehensive and earnestly designed tool aimed to increase confidence in a traders market bias. ONWAY analyzes market trends, market strength, and price action near key pivot levels to form a bias on future price action. Of course, it is fundamentally impossible to predict the future, but we all try it now don't we. Gain an edge in the markets and add ONWAY to your tool box.
ONWAY Functionality
Confirmation Signals: ONWAY provides real-time, non-repaint BUY and SELL signals upon the active timeframes candle close.
Targets and Stops: ONWAY will, upon signal confirmation, set a target and stop loss.
Position Management: ONWAY will monitor its current position, if one exists, and attempt to tighten the stop loss if possible.
ONWAY Details
Symbols and Timeframes: ONWAY is restricted to approved symbols and timeframes indicated by the 🟢 icon next to "Optimized:" and "ONWAY Timeframe:" on the dashboard. If an unapproved combination of symbol and timeframe is in use, ONWAY will be disabled (no signals will be visible). See author's instructions for the current ONWAY watchlist or to submit a symbol/timeframe request.
Position Details: Apart from the on chart signals and position plot, the ONWAY dashboard will indicate the current position, entry price, target price, and stop price.
Stop Loss: ONWAY has a unique stop loss/exit strategy that has proved, based on our calculations, to be advantageous. If price reaches or exceeds the stop loss, ONWAY will not close the position unless there is a candle close on the active timeframe exceeding the stop level. This is known as a soft stop loss and identified on the dashboard as "(Soft)" next to the stop price. Additionally, the stop loss will change throughout the position, following the low, for a long position or high, for a short position, within a given period, but the soft stop loss will not exceed beyond a 1:1 risk to reward ratio (the risk will always be equal to or less than the potential reward). It is importance to be aware that the soft stop is utilized at this 1:1 threshold as well. On the plus side, the changing stop loss will impose a risk free position if it finds itself between the entry price and target price. At this stage the soft stop is no longer utilized, the stop loss can only approach the target price, and profit is uhhh.....certain (I don't think the mods will like that word 😉). If the soft stop is no longer in use, the dashboard will indicate this with "(Hard)" next to the stop price.
Position Sizing: The position sizing used for the backtested results is displayed on the dashboard next to "Strategy Lot Size:". This position size is provided solely as a reference for the backtest results. The choice of a position size is left to the users discretion.
Backtest Results: With any strategy, backtesting is an excellent way to judge performance and viability, but it is important to recognize that past performance does not confirm repeatability in future market conditions.
Updates: ONWAY updates its acceptable symbols frequently to account for everchanging market conditions. This includes adding new symbols, rejecting previously compatible symbols, and modifying the optimal window for current symbols.
Acceptability Criteria: The criteria for a symbol to be deemed acceptable requires that its backtested results deliver a win rate greater than 70%, profit factor greater than 1.2, and its equity chart appear favorable. These metrics are available to users by clicking on "Strategy Tester" located on the bottom panel of the chart view.
Accessibility: To gain access to ONWAY, see the author's instructions below.
Use of this script implies that you acknowledge that past performance does not necessarily indicate future results and that guarantees are not possible in this trading realm.
[Joy] Aladdin (1.0.0 Alpha)Explanation of the markers in the indicator
* Bearish / Sell sign: On the candle's close, I open a short position
* Bullish sign: On the candle's close, I open a long position
* Red circle: On the candle's close, I take at least 50% unrealized profit into a realized profit of any running long leverage position. I might even convert some portion of the position into stable coins.
* Green circle: On the candle's close, I take at least 50% unrealized profit into a realized profit of any running short leverage position. I might even convert some portion of the position into stable coins.
* Down Arrows: When the down arrow finishes and the candle close, I put a tighter stop loss of any running long leverage position. It sometimes indicates the local top.
* Up Arrows: When the up arrow finishes and the candle close, I put a tighter stop loss of any running short leverage position. It sometimes indicates the local bottom.
* Purple candle: Weakly bullish.
* Green candle: Strongly bullish
* Red candle: Strongly bearish
* Yellow candle: Weakly bearish
FAQ
Q: Does it use some EMA /MA/etc.? Does it use any indicator with tweaked settings?
Answer: No.
Q: What does it mostly depend on?
Answer: Volume and gradual flow of non-interrupted data. The logic depends purely on volume, price bars and the wicks.
Q: Does it work with all coins, stocks, futures, instruments?
Answer: I prefer to use the exchange with the best possible data. Then backtest out to find the best possible timeframe, stop loss and target all derived from this script data.
Q: Can you make it free or make it open source?
Answer: There is no free lunch in this world. I will never reveal or share the source code!
Q: Do you provide ongoing support for the indicator?
Answer: Yes, as long as I can, I will continue updating the indicator
Q: Are the bullish /buy & the bearish /sell markers automatic?
Answer: I have no control over the markers. It is driven purely by logic from the script.
Q: Is this financial advice?
Answer: This is not financial advice. I do not guarantee any profit or loss. I am not responsible for any of your losses or profits. My indicators do not assure profit or loss. It also does not auto-open or auto-close a trade.
Note:
The Aladdin has been derived from the Super Algorithm Indicator. I have depreciated the Super Algorithm Indicator I have automatically migrated every user to Aladdin, who had Super Algorithm Indicator. One should not use the SA indicator. One should start using this indicator instead.
Version 1
A derived version of Super Algorithm Indicator with optimized code (uses arrays, removes few warnings in the code, makes code more reusable) so that I can add further features in the future. A few new coding features in the pine script encouraged me to go for this version. Since the codebase has been revamped, it made sense for me to make it a new indicator. have also changed a small parameter that is configurable at the moment. Previously it was valued at 26. Now I am putting value at 21.
BNBUSD 1 Minute Chart / 1 Hour BBand Day Trading 3Commas*** As always, this is provided for educational purposes only and I am not an investment advisor; I'm just a guy who likes to come up with novel ideas and share them with other traders so they can learn. ***
This strategy is a fun one. I took parts of 'Bollinger Awesome Alert R1 by JustUncleL' () and modified it to have enhanced day trading functionality. This version does not show source and that is by design - I want the alerts to be visible to the public and if you want to get set up with a version that integrates with 3commas, drop me a message - there's a lot more that goes into setting up automated 3commas trading but this script was written specifically with 3commas in mind.
It's possible this is one of the more interesting strategy indicators I've made. The setup I used for this is as such and you will need to set it up the same way:
One minute chart for the BNB/USD(T) pair on Binance.us (other exchanges will likely work, other coin pairs or other time frames will likely not)
This script watches the one minute chart and when price golden crosses the lower Bollinger band, a buy order is placed.
There are two sell conditions; one I set up to take profit and one I designed as a kind of stop loss. I went with a flat 7.5% for the take profit as this showed the best results in the backtester. I had planned for it to be closer to 3% but for this strategy to work it needs to be higher. According to the backtest it offers around double the return of buying and holding BNB over the sample timeframe.
The 'stop loss' condition is where the fun lies. I transposed Bollinger bands from a one hour BNBUSD Binance.us chart on top of the 1 minute chart and those are the blue lines you see. The stop loss condition happens when the current price death crosses the bottom one hour Bollinger band. Ironically, often this doesn't result in any losses as you will see in the chart and instead results in a small win. This definitely was not my intention when I created it but it's a lot better than the earlier version where I set up a variable percentage-based stop loss. Even with me optimizing the regular stop loss for this coin pair, my 1 hour bband method nets an extra 2% profit over the same two week time period, even with Binance fees factored in!
Have fun and like I said, hmu via message if you want access to the customizable indicator for 3commas!
(IK) Base Break BuyThis strategy first calculates areas of support (bases), and then enters trades if that support is broken. The idea is to profit off of retracement. Dollar-cost-averaging safety orders are key here. This strategy takes into account a .1% commission, and tests are done with an initial capital of 100.00 USD. This only goes long.
The strategy is highly customizable. I've set the default values to suit ETH/USD 15m. If you're trading this on another ticker or timeframe, make sure to play around with the settings. There is an explanation of each input in the script comments. I found this to be profitable across most 'common sense' values for settings, but tweaking led to some pretty promising results. I leaned more towards high risk/high trade volume.
Always remember though: historical performance is no guarantee of future behavior . Keep settings within your personal risk tolerance, even if it promises better profit. Anyone can write a 100% profitable script if they assume price always eventually goes up.
Check the script comments for more details, but, briefly, you can customize:
-How many bases to keep track of at once
-How those bases are calculated
-What defines a 'base break'
-Order amounts
-Safety order count
-Stop loss
Here's the basic algorithm:
-Identify support.
--Have previous candles found bottoms in the same area of the current candle bottom?
--Is this support unique enough from other areas of support?
-Determine if support is broken.
--Has the price crossed under support quickly and with certainty?
-Enter trade with a percentage of initial capital.
-Execute safety orders if price continues to drop.
-Exit trade at profit target or stop loss.
Take profit is dynamic and calculated on order entry. The bigger the 'break', the higher your take profit percentage. This target percentage is based on average position size, so as safety orders are filled, and average position size comes down, the target profit becomes easier to reach.
Stop loss can be calculated one of two ways, either a static level based on initial entry, or a dynamic level based on average position size. If you use the latter (default), be aware, your real losses will be greater than your stated stop loss percentage . For example:
-stop loss = 15%, capital = 100.00, safety order threshold = 10%
-you buy $50 worth of shares at $1 - price average is $1
-you safety $25 worth of shares at $0.9 - price average is $0.966
-you safety $25 worth of shares at $0.8. - price average is $0.925
-you get stopped out at 0.925 * (1-.15) = $0.78625, and you're left with $78.62.
This is a realized loss of ~21.4% with a stop loss set to 15%. The larger your safety order threshold, the larger your real loss in comparison to your stop loss percentage, and vice versa.
Indicator plots show the calculated bases in white. The closest base below price is yellow. If that base is broken, it turns purple. Once a trade is entered, profit target is shown in silver and stop loss in red.
TFi Pivot Reversal V3The Pivot Reversal Study uses pivot points to create a support and resistance level; based on this levels the script creates virtual stop-market orders to catch the trend if the price is crossing the pivot lines.
A "Pyramiding" input allows to configure up to 3 entries; the script enters an additional position if the price falls by a configurable percentage amount (long), the reverse to short orders.
A configurable profit-target and stop-loss is being used to exit an open position.
An optional Moving Average filter can be used to enable only long or short positions.
The script renders a status box at the last bar, which shows the current position status and result of the built-in trading simulation results.
It shows the following statistic values:
current position PnL - also background turns green if position is in profit and red if in loss
the percentage distance to the profit-target and stop-loss level
the overall number of wins and losses and the win/loss ratio
the overall profit and loss amount (assuming a quantity of 1)
the net-profit and profit-ratio
For the correct simulation of entry/exit prices, the script contains inputs for a percentage entry and exit slippage.
The study also creates configurable alerts, which follow the exact position of the entry/exit markers. The default alert messages contain trading instruction to execute orders via Alertatron; but the message content can be replaced if configuring the alert in the Tradingview environment.
The script was mainly backtested with crypto-coins, e.g. XBTUSD at 15min timeframe. But the script also works with any other type of security and timeframe.
How to access
This strategy is a "Invite Only" script. You can can subscribe or purchase the strategy; please use the link below or send me a message via Tradingview to obtain access to the strategy and study script.
For enabling the script in your Tradingview chart window, click on "Indicators" and select "Invite-Only Scripts".
Full list of alerts
'Alertatron Exit' ... Exit all open positions.
'Alertatron Enter Long' ... Enter long position, w/o stop-loss being used.
'Alertatron Enter Short' ... Enter short position, w/o stop-loss being used.
'Alertatron Enter Long SL' ... Enter long position, w/ stop-loss being used.
'Alertatron Enter Short SL' ... Enter short position, w/ stop-loss being used.
Full list of parameters
"Pivot Left Bars" ... Number of bars on the left of the pivot point - used for pivot /peak detection.
"Pivot Right Bars" ... Number of bars on the right of the pivot point - used for pivot /peak detection.
"MA Filter Fast" ... Moving Average filter fast period.
"MA Filter Slow" ... Moving Average filter slow period.
"Profit Target Option" ... Configure the profit-target either as a fix percentage value or an ATR.
"Profit Target " ... Fix percentage profit-target.
"Profit ATR Period" ... ATR profit-target period.
"Profit ATR Factor" ... ATR profit-target factor/multiplier.
"Stop Loss Option" ... Configure the stop-loss either as a fix percentage value or disable the stop-loss completely.
"Stop Loss " ... Fix percentage stop-loss.
"Rebuy Loss " ... Percentage loss of the initial position before script enter a nw position in the same direction.
"Pyramiding" ... Maximum number of positions.
"Show MA Plots" ... Show/hide Moving average plots.
"Slippage Entry " ... Percentage slippage for entering a position.
"Slippage Exit " ... Percentage slippage for exiting a position.
"Statistic Label" ... Defines the position of the statistic label relatively to the last bar in the chart.
"Backtest Start" ... Backtest start time; area outside this timeframe will be grayed out.
"Backtest Stop" ... Backtest stop time; area outside this timeframe will be grayed out.
"Backtest Mode" ... Closes the currently opened position if chart switches to last bar; please only enable if backtesting, otherwise it leads to unwanted alerts.
Backtest PREMIUM Suite+ (Plug & Play)Hello traders
I. 💎 SCRIPTS ACCESS AND TRIALS 💎
1. For the trial request access, they have to be done through my website .
2. My website URL is in this script signature at the very bottom (you'll have to scroll down a bit and going past the long description) and in my profile status available here : Daveatt
Due to the new scripts publishing house rules, I won't mention the URL here directly. As I value my partnership with TradingView very much, I prefer showing you the way for finding them :)
3. Many video tutorials explaining clearly how all our indicators work are available on our website > guides section.
4. You may also contact me directly for more information
II. 🔎 Backtest PREMIUM Suite+ (Plug & Play) 🔎
2.1 Forewords
This indicator is available only to our PREMIUM 12 months users. YES! I said indicator, and not strategy or backtest for an excellent reason.
We wanted to make it as generic as possible and allow anyone to connect any indicator of his/her choice in a few clicks only.
This is NOT possible (in TradingView) with a strategy/backtest, but only with an indicator - that's why we worked on recoding the whole backtest logic as an indicator.
The PRO edition does not handle any pyramiding/re-entry - as such enters only once per trend by design. This feature is reserved for our PREMIUM users.
2.2 Concept
This is an indicator that I saw on TradingView and was introduced by the @Pinecoders account on TradingView.
I inspired myself from his Backtest Engine to offer a version more adapted to my vision - The benefits of connecting yourself any indicator to our Backtest engine are amazing and huge.
The concept can't be more simple. Imagine using any indicator and connecting to a backtest system in a single click.
You may connect your Algorithm Builder also to this complete backtesting system in a single click.
What's better between paying thousands for each backtest, or connecting yourself your indicators to your backtest with a click?
That was a rhetoric question, but you can still share your answer with me if you want to :)
III. The amazing benefits of our🔌&🕹️ (Plug&Play) system
Issue #1 💲 A BACKTEST SYSTEM IS COSTLY 💲
Hiring a developer to code a custom indicator is costly. For a custom backtest it's even more expensive as those scripts are very often way more complicated.
Now imagine, that now that you see your idea live on a chart, you'll realize you'll have to finance another backtest system, as the one you have is not compatible with your new idea.
Solution #1 💲💲 YOU COULD BE SAVING SOME MONEY 💲💲
just because it won't be needed to hire someone else for each of your trading idea.
We will never guarantee your success on the market, but THIS I stand by it any day any hour.
You can connect any indicator or your choice by updating your indicator slightly and connecting it to our Backtest engine. We send the tutorial for doing it to all our customers.
Issue #2 🕔 IT'S TIME-CONSUMING 🕔
Even if someone is doing all the coding for you, it might require days/weeks depending on your overall trading strategy/idea.
Without even counting the time for you to test/validate the work done and all the back-and-forth to fix all the issues.
Solution #2 SAVING TIME MIGHT EQUATES TO SAVING MONEY : 🕔 = 💲💲💲
I wish it could be as easy as going from weeks of coding to "1 single click" :)
I did the heavy-lifting, but you'll have to make the last effort the cross the finishing line. I made it easy for you to play with it and find a configuration that makes sense to YOU and for your strategy/asset/timeframe
Issue #3 ❌ IT'S COMPLICATED ❌
Someone did a backtest code for you, but... you can't update it because you either :
- don't know anything in programming
- ... and don't have time to learn (most of us have a job/family/...life)
- The system you have is way too specific for one of your previous idea, but can't be updated easily for your next trading ideas. I see a lot of traders nodding right now thinking "that's soooooo true !!!!"
Solution #3 🎉 WE MADE IT EASY AND FUN 🎉
Our goal is to externalize the technical stuff that you don't want to take care of - so that you can finally focus on your trading and optimizing your ideas. #bold #statement
In case you're wondering, no we're not reading your mind :), but we're also traders who didn't know how to code before and had to hire external programmers to do the heavy work for us.
You can be sure that most of the frustrations (trading, technical, ...) you have/had, we had them also and that's why we created this backtest indicator.
III. 🔌&🕹️
Hope you're ready to be impressed. Because, what I'm about to introduce, is my best-seller feature - and available across many of my indicators.
In TradingView, there is a feature called "Indicator on Indicator" meaning you can use an external indicator as a data source for another indicator.
I'm using that feature to connect any external indicator to our Backtest PREMIUM Suite+ (Plug & Play) - hence the plug and play name. Please don't make it a plug and pray :) it's supposed to help you out, not to stress you even more
Let's assume you want to connect your Algorithm Builder Multiple Trends+ to your Backtest PREMIUM Suite+
I mentioned an Algorithm Builder but you may connect any oscillator (MACD, On balance volume, stochastic RSI, True Strenght index, and many more..) or non-oscillator (divergence, trendline break, higher highs/lower lows, candlesticks pattern, price action, harmonic patterns, ...) indicators.
THE SKY IS (or more likely your imagination) is the limit :)
Fear no more. The Plug&Play technology allows you to connect it and use it the backtest calculations.
This is not magic, neither is sorcery, but certainly is way beyond the most awesome thing I've ever developed on TradingView (even across all brokers I know). #bolder #statement
TradingView is the best trading platform by far and I'm very grateful to offer my indicators on their website.
To connect your external indicator to ours, we're using a native TradingView feature, which is not available for all users.
It depends on your TradingView subscription plan ( More info here )
If you intend to use our Algorithm Plug&Play indicator, and/or our Backtest Plug&Play suites, then you must upgrade your TradingView account to enjoy those features.
We value our relationship with our customers seriously, and that's why we're warning you that a compatible TradingView account type is required - at least PRO+ or PREMIUM to add more than 1 Plug&Play indicator per account.
We go in-depth on our website why the Plug&Play is an untapped opportunity for many traders out there - URL available on my profile status and signature
IV. 📊 Make it nice! 📊
Now we're getting right into the fun stuff.
Let's explore briefly each display option (symbolized by an 👁️🗨️ in the Backtest UI) :
- Color Traded Background : Color the chart background is green when in a BUY trade, in red when in a SELL trade. If the Backtest is not in a trade, then the background won't be colored.
- Show Entry/Exit Markers : Displays the entries (Enter Long/Enter Short), and exits (Exit Long/Exit Short) labels.
- Show Entry Level : Displays a blue level line to easily identify the entry price of a trade.
- Show Take Profit Level : Display a purple line to visualize where the Take Profit level is (we'll explain below how to set it up).
- Show In-Trade Stops : Display the stop-loss
V. Backtesting filters
A backtest should have some filters helping the traders testing a few hypotheses. Well.... we included a ton of them.
Once again, thank you @Pinecoders for the help and support you gave me
5.1 ↑ Trade Direction ↓
- Both: The backtest takes the BUY, and SELL trades.
- Longs only/Short only: To be used if the trader wants to take the trades in a unique direction only
5.2 ▲🔷Pyramiding🔷▼
The Backtest PRO allows 1 entry per identified trend
Pyramiding has many names such as Re-entry, secondary trend, Additional entry, ...
Basically, it refers to entering multiple times in the same trend.
Maximum Number of Pyramiding Entries: Literally the max number of re-entries in the same trend.
For instance, if set to 2, then depending on the signals, you'll get at most 2 re-entries in the same trade direction.
- Position Size Multiple of Original Entry Position: Option to add X multiples of the original position size for the re-entries.
Example: Position size multiple = 2, and First entry size is $100. Then, the re-entries position sizes will be ($100 X 2 = $200).
5.3 ▄ █ Position sizing █ ▄
- 1. % of Equity: If selected, the position size used is the input to the right of 1. % of Equity.
Example: The trader starts with a capital of 100K. After a winning trade, your total capital is $103K - for the next trade the position size will be 3% of $103K
- 2. % of Capital: If selected, the position size used is the input to the right of 2. % of Capital.
In other words, the position size will always be the same position size as calculated on the initial capital.
Example: The trader starts with a capital of 100K. After a winning trade, your total capital is $103K - for the next trade the position size will be 5% of $100K. (As 100K is the initial capital used in our dummy example)
5.4⛔ Entry Stops and In-Trade Stops ⛔
We didn't reinvent the wheel here. Any good backtest should offer an entry stop-loss and an in-trade stop-loss.
Giving only here also an example among all the use cases. For instance, the trader sets a stop-loss 2% at the time of entry on your trade, but once the trade moves in the desired direction, the trader might want a trailing stop-loss using a 4% input.
Example: A trader goes LONG on only 1 "ABC" stock evaluated $10 per share.
1) The entry-stop loss will be 2% away so set at $8
2) A candle
3) The trailing stop will activate, and move the stop-loss from the entry stop-loss level (=$8) to $8.32 (=4% move up from $8) - and so on, and so forth for each time the price moves 4% up
The entry and in-trade stop losses can absolutely be identicals. There is no universal rule, and as always you know the drill - all depends on your backtest, and trading strategy as a whole.
5.5 ❌ Hard Exits ❌
⚠️The Backtest PRO Suite offers the hard exit on MACD only.
Our Backtest PREMIUM Suite offers 2 more indicators to invalidate your trades on :
1. MACD
2. Trend Direction
3. RSI divergence (Regular, and Hidden)
The hard exit (or invalidation) is a fundamental part of my trading method.
I explained numerous times on TradingView, our website, and social media channels why I "love" this concept so much, and how it saved my trading account numerous times from getting savagely wrecked by the market.
5.6 💲💲 Take Profit 💲💲
We only included 1 level of Take Profit so far. We'll work on adding at least one more soon.
You can set your Take Profit level based on either a:
1- Fixed value
2 - Percentage value
5.7 📆 Date Range Filtering 📆
If enabled, the backtest only uses the data between the starting and the ending dates of the defined range.
5.8 ⏱️ Hourly Range Filtering ⏱️
Please note that the hours filtering is based on the broker time - not on your chart time.
In other words, if your chart is UTC+1, but you're trading an asset from a US EAST COAST broker, then the timezone used is the UTC-4 timezone.
You'll must be wary of this when filtering and probably do a quick (but simple) calculation before setting up this option.
The easiest would be to set your chart timezone on the broker local timezone (and no math is needed).
Let's add a quick note that the hourly filter is also included in our Algorithm Builders PRO/PREMIUM 12 months. #shameless #self #advertising
5.9 ❗❗ Fees and Slippage ❗❗
Too often completely ignored by many traders, the fees can eat gains out quickly/deepen one's capital faster than expected.
⚠️The fees vary between brokers, and asset traded - it could be recommended to check on your broker page what are the fees for the asset on your chart, and insert that percentage number.
Another cost ignored, even more, is the Slippage.
i.e. think about a Stop-Loss being hit, and we're so confused because we see on the chart that NEVER the price came even close to your SL level, but... it got hit anyway.
Yes! we know how frustrating it is, but that's the game we're playing, and trading should never be about blaming the game, but only blaming the players/traders/ourselves.
Blaming the game constantly is likely to not end with good performance results, but accounting for this "risk", and being able to quantify it is an incredible hedge. #bold #statement #level #10000
5.10 🔔 Alerts 🔔
By design, the alerts aren't available for strategy scripts. But this script is an... indicator so why should we not enjoy all the cards in our hands the fullest.
We enabled the alerts on the:
1. Main BUY/SELL Entry
2. Pyramiding BUY/SELL Entries
3. Exit Signals such as stop-loss, take-profit, hard-exits
You're welcome :)
VI. 📝 Where are the backtest results? 📝
Answer: in the Data Window section of your TradingView
Now the cherry on the cake if we might say so. A backtest is cool, but visualizing results is actually the end goal here.
Our PREMIUM users benefit from way more analytics than the PRO users.
More info available on our website.
The Data Window is dynamic - it means whenever you'll mouseover at a give time on your chart, the data on that panel automatically updates.
Let's assume you're backtesting your idea between Sept 1st, 2019, and Oct 1st, 2019.
If your mouse cursor is located (or hovered) at a candle on Sept 14th, 2019 (data chosen randomly for this example), then the data displayed only includes the results between Sept 1st, and Sept 14th.
More info available on our website with a nice tutorial video. Data window metrics and filters explained on our website
Here's what the data window looks like: imgur.com
If you have any doubt or question, please hit me up directly or ask in the comments section of this script.
I'll never claim I have the best trading methodology or the best indicators.
You only will judge and I'll appreciate all the questions and feedback you're sending my way.
They help me a ton to develop indicators based on all the requests I received.
Kind regards,
Dave
Backtest PRO Suite+ (Plug & Play)Hello traders
I. SCRIPTS ACCESS AND TRIALS
1. For the trial request access, they have to be done through my website .
2. My website URL is in this script signature at the very bottom (you'll have to scroll down a bit and going past the long description) and in my profile status available here : Daveatt
Due to the new scripts publishing house rules, I won't mention the URL here directly. As I value my partnership with TradingView very much, I prefer showing you the way for finding them :)
3. Many video tutorials explaining clearly how all our indicators work are available on your website > guides section.
4. You may also contact me directly for more information
II. Backtest PRO Suite+ (Plug & Play)
2.1 Forewords
This indicator is available only to our PRO 12 months users. YES! I said indicator, and not strategy or backtest for an excellent reason.
We wanted to make it as generic as possible and allow anyone to connect any indicator of his/her choice in a few clicks only.
This is NOT possible (in TradingView) with a strategy/backtest, but only with an indicator - that's why we worked on recoding the whole backtest logic as an indicator.
The PRO edition does not handle any pyramiding/re-entry - as such enters only once per trend by design. This feature is reserved for our PREMIUM users.
2.2 🔎 Concept 🔎
This is an indicator that I saw on TradingView and was introduced by the @Pinecoders account on TradingView.
I inspired myself from his Backtest Engine to offer a version more adapted to my vision - The benefits of connecting yourself any indicator to our Backtest engine are amazing and huge.
The concept can't be more simple. Imagine using any indicator and connecting to a backtest system in a single click.
You may connect your Algorithm Builder also to this complete backtesting system in a single click.
What's better between paying thousands for a backtest, or connecting yourself your indicator to your backtest with a click?
That was a rhetoric question, but you can still share your answer with me if you want to :)
III. The amazing benefits of our🔌&🕹️ (Plug&Play) system
Issue #1 💲 A BACKTEST SYSTEM IS COSTLY 💲
Hiring a developer to code a custom indicator is costly. For a custom backtest it's even more expensive as those scripts are very often way more complicated.
Now imagine, that now that you see your idea live on a chart, you'll realize you'll have to finance another backtest system, as the one you have is not compatible with your new idea.
Solution #1 💲💲 YOU COULD BE SAVING SOME MONEY 💲💲
just because it won't be needed to hire someone else for each of your trading idea.
We will never guarantee your success on the market, but THIS I stand by it any day any hour.
You can connect any indicator or your choice by updating your indicator slightly and connecting it to our Backtest engine. We send the tutorial for doing it to all our customers.
Issue #2 🕔 IT'S TIME-CONSUMING 🕔
Even if someone is doing all the coding for you, it might require days/weeks depending on your overall trading strategy/idea.
Without even counting the time for you to test/validate the work done and all the back-and-forth to fix all the issues.
Solution #2 SAVING TIME MIGHT EQUATES TO SAVING MONEY : 🕔 = 💲💲💲
I wish it could be as easy as going from weeks of coding to "1 single click" :)
I did the heavy-lifting, but you'll have to make the last effort the cross the finishing line. I made it easy for you to play with it and find a configuration that makes sense to YOU and for your strategy/asset/timeframe
Issue #3 ❌ IT'S COMPLICATED ❌
Someone did a backtest code for you, but... you can't update it because you either :
- don't know anything in programming
- ... and don't have time to learn (most of us have a job/family/...life)
- The system you have is way too specific for one of your previous idea, but can't be updated easily for your next trading ideas. I see a lot of traders nodding right now thinking "that's soooooo true !!!!"
Solution #3 🎉 WE MADE IT EASY AND FUN 🎉
Our goal is to externalize the technical stuff that you don't want to take care of - so that you can finally focus on your trading and optimizing your ideas. #bold #statement
In case you're wondering, no we're not reading your mind :), but we're also traders who didn't know how to code before and had to hire external programmers to do the heavy work for us.
You can be sure that most of the frustrations (trading, technical, ...) you have/had, we had them also and that's why we created this backtest indicator.
III. 🔌&🕹️
Hope you're ready to be impressed. Because, what I'm about to introduce, is my best-seller feature - and available across many of my indicators.
In TradingView, there is a feature called "Indicator on Indicator" meaning you can use an external indicator as a data source for another indicator.
I'm using that feature to connect any external indicator to our Backtest PRO Suite+ (Plug & Play) - hence the plug and play name. Please don't make it a plug and pray :) it's supposed to help you out, not to stress you even more
Let's assume you want to connect your Algorithm Builder Single Trend+ to your Backtest PRO Suite+
I mentioned an Algorithm Builder but you may connect any oscillator (MACD, On balance volume, stochastic RSI, True Strenght index, and many more..) or non-oscillator (divergence, trendline break, higher highs/lower lows, candlesticks pattern, price action, harmonic patterns, ...) indicators.
THE SKY IS (or more likely your imagination) is the limit :)
Fear no more. The Plug&Play technology allows you to connect it and use it the backtest calculations.
This is not magic, neither is sorcery, but certainly is way beyond the most awesome thing I've ever developed on TradingView (even across all brokers I know). #bolder #statement
TradingView is the best trading platform by far and I'm very grateful to offer my indicators on their website.
To connect your external indicator to ours, we're using a native TradingView feature, which is not available for all users.
It depends on your TradingView subscription plan ( More info here )
If you intend to use our Algorithm Plug&Play indicator, and/or our Backtest Plug&Play suites, then you must upgrade your TradingView account to enjoy those features.
We value our relationship with our customers seriously, and that's why we're warning you that a compatible TradingView account type is required - at least PRO+ or PREMIUM to add more than 1 Plug&Play indicator per account.
We go in-depth on our website why the Plug&Play is an untapped opportunity for many traders out there - URL available on my profile status and signature
IV. 📊 Make it nice! 📊
Now we're getting right into the fun stuff.
Let's explore briefly each display option (symbolized by a 👁️🗨️ in the Backtest UI) :
- Color Traded Background : Color the chart background is green when in a BUY trade, in red when in a SELL trade. If the Backtest is not in a trade, then the background won't be colored.
- Show Entry/Exit Markers : Displays the entries (Enter Long/Enter Short), and exits (Exit Long/Exit Short) labels.
- Show Entry Level :Displays a blue level line to easily identify the entry price of a trade.
- Show Take Profit Level : Display a purple line to visualize where the Take Profit level is (we'll explain below how to set it up).
- Show In-Trade Stops : Display the stop-loss
V. Backtesting filters
A backtest should have some filters helping the traders testing a few hypotheses. Well.... we included a ton of them - even for the PRO version
Once again, thank you @Pinecoders for the help and support you gave me
5.1 ▄ █ Position sizing █ ▄
- 1. % of Equity: If selected, the position size used is the input to the right of 1. % of Equity.
Example: The trader starts with a capital of 100K. After a winning trade, your total capital is $103K - for the next trade the position size will be 3% of $103K
- 2. % of Capital: If selected, the position size used is the input to the right of 2. % of Capital.
In other words, the position size will always be the same position size as calculated on the initial capital.
Example: The trader starts with a capital of 100K. After a winning trade, your total capital is $103K - for the next trade the position size will be 5% of $100K. (As 100K is the initial capital used in our dummy example)
5.2⛔ Entry Stops and In-Trade Stops ⛔
We didn't reinvent the wheel here. Any good backtest should offer an entry stop-loss and an in-trade stop-loss.
Giving only here also an example among all the use cases. For instance, the trader sets a stop-loss 2% at the time of entry on your trade, but once the trade moves in the desired direction, the trader might want a trailing stop-loss using a 4% input.
Example: A trader goes LONG on only 1 "ABC" stock evaluated $10 per share.
1) The entry-stop loss will be 2% away so set at $8
2) A candle
3) The trailing stop will activate, and move the stop-loss from the entry stop-loss level (=$8) to $8.32 (=4% move up from $8) - and so on, and so forth for each time the price moves 4% up
The entry and in-trade stop losses can absolutely be identicals. There is no universal rule, and as always you know the drill - all depends on your backtest, and indicator configurations as a whole.
Last, but not the least, selecting an Entry stop-loss is mandatory, but the in-trade stop-loss is not. Up to you to decide if the in-trade SL is needed for your Backtest strategy.
5.3 ❌ Hard Exits ❌
We included the MACD hard exit indicator in the backtest - as we did also for the Algorithm Builders.
The hard exit (or invalidation) is a fundamental part of my trading method.
I explained numerous times on TradingView, our website, and social media channels why I "love" this concept so much, and how it saved my trading account numerous times from getting savagely wrecked by the market.
5.4 💲💲 Take Profit 💲💲
We only included 1 level of Take Profit so far. We'll work on adding at least one more soon.
You can set your Take Profit level based on either a:
1- Fixed value
2 - Percentage value
5.5 📆 Date Range Filtering 📆
If enabled, the backtest only uses the data between the starting and the ending dates of the defined range.
5.6 ❗❗ Fees and Slippage ❗❗
Too often completely ignored by many traders, the fees can eat gains out quickly/deepen one's capital faster than expected.
⚠️The fees vary between brokers, and asset traded - it could be recommended to check on your broker page what are the fees for the asset on your chart, and insert that percentage number.
Another cost ignored, even more, is the Slippage.
i.e. think about a Stop-Loss being hit, and we're so confused because we see on the chart that NEVER the price came even close to your SL level, but... it got hit anyway.
Yes! we know how frustrating it is, but that's the game we're playing, and trading should never be about blaming the game, but only blaming the players/traders/ourselves.
Blaming the game constantly is likely to not end with good performance results, but accounting for this "risk", and being able to quantify it is an incredible hedge. #bold #statement #level #10000
5.7 🔔 Alerts 🔔
By design, the alerts aren't available for strategy scripts. But this script is an... indicator so why should we not enjoy all the cards in our hands the fullest.
We enabled the alerts on those Backtest Entry/Exit signals. You're welcome :)
VI. 📝 Where are the backtest results? 📝
Answer: in the Data Window section of your TradingView
Now the cherry on the cake if we might say so. A backtest is cool, but visualizing results is actually the end goal here.
The Data Window is dynamic - it means whenever you'll mouseover at a give time on your chart, the data on that panel automatically updates.
Let's assume you're backtesting your idea between Sept 1st, 2019, and Oct 1st, 2019.
If your mouse cursor is located (or hovered) at a candle on Sept 14th, 2019 (data chosen randomly for this example), then the data displayed only includes the results between Sept 1st, and Sept 14th.
More info available on our website with a nice tutorial video. Data window metrics and filters explained on our website
Here's what the data window looks like: imgur.com
If you have any doubt or question, please hit me up directly or ask in the comments section of this script.
I'll never claim I have the best trading methodology or the best indicators.
You only will judge and I'll appreciate all the questions and feedback you're sending my way.
They help me a ton to develop indicators based on all the requests I received.
Kind regards,
Dave
Strategy Builder Crypto V6Hello everyone
This indicator is the result of 7 years of trading (including 3 years of analyzing day and night how crypto assets behave).
I made it fully customizable but I wouldn't recommend changing the default values as they're the most optimal ones for now. Might change in the future but I'm very happy with the signals so far and I hope you'll be as well :)
Without further due, let's dig into it...
0 - Algo trading and Why
In the crypto trading, there is a lot of useless noise (we can probably thank Crypto Twitter for that :p) and a lot of useless data with the sole purpose is to lure you (who said Bitfinex Long/Short ratio or CME gaps ??)
I wanted to remove all the useless and only focus on Technical Analysis (TA) because I was deeply convinced that TA includes by design Fundamental Analysis (FA) and Pumponomics Analysis (PA) - PA being for instance when your favorite twitter guru will pump and dump on you
I heard that so many people got REKT from the previous bear market and I wanted to give back to the community - who helped me so much a few years back.
I worked hard to design the method and make it simple for the public and for FREE (so far as I want to collect feedbacks from the community and improving the indicator)
THIS IS MY GIFT TO YOU
1 - Input values
I'll explain later on through a medium article what each parameter means and how to set them up. For now, please used the optimized and recommended values already set in the indicator
2 - The method
This method works for intraday trading for timeframes between m5 and H1. Any timeframe above could work but would give signals too late - in this case, I would recommend changing the inputs with smaller values to adjust
I see a trend being composed of a main trend, and mini sub trends. In other words, for instance, a weekly bullish trend is made of smaller H4 bullish trends. Hope it makes sense so far
Let's call the weekly trend the MAIN trend and the H4 smaller trends the SECONDARY trends
That's exactly what this indicator is about
It will catch the best MAIN trend and all the SECONDARY trends in the same direction of the MAIN trend.
It's up to you if you want to take all the SECONDARY trends or only the first one in the sequence.
3 - Invalidation signal
A signal invalidation is used to make you exiting your position with a small loss before your stop loss will get hit. Very powerful way to save your capital and limit your losses.
You'll find the indicator here on tradingview for free under the name Trend signal with Alert (made by myself)
Trend signal with Alert
to invalidate entries. You'll need to request an invite
Briefly, let's assume we get a BUY signal. I would exit the position either if I'm getting a DOWN trend signal. It means, if the oblique/logarithmic trendline is broken, then it's better to exit the position and wait for the indicator to give another BUY signal later hopefully
Best case, it will limit your loss in case the asset will dump.
Worst case, this strict management strategy will make you exiting your position for no reason and you'll re-enter later (with a signal) at almost the same price or a bit higher
In the long run, this method will prevent you from having big losses
4 - Stop Loss and Take profits levels
It's really up to you. It depends of your capital and psychology
This indicator is made to give big moves but that's not 100% guaranteed. You can draw some trendlines or use moving averages in big timeframes to set your take profit and stop loss levels.
I personally use this also, along with fibonacci on the weekly/monthly timeframes for my take profit levels
As I'm a nice person, I'm linking the Fibonacci indicator that I use here
Automatic Multi-timeframes fibonacci zones
. You'll also need to request an invite for that one
4-bis - Trailing stop
Not financial advice but I use a supertrend and I have a software that will trail my stop according to that supertrend level
For LONG positions, we could set the trailing below the supertrend.
For SHORT positions, we could set the trailing above the supertrend.
You'll find the indicator here on tradingview for free under the name Supertrend V1.0 - Buy or Sell Signal
5 - Which assets
It's working with the default values on major/mid/small caps and for ALTS/BTC, ALTS/USD and ALTS/ETH pairing
YES, THIS IS MOST AWESOME THING OF THE ENTIRE UNIVERSE !!!
6 - Best setup
m15 timeframe is my preferred one for this method. Best Risk/Reward/Invalidations ratio among all other timeframes
I strongly recommend to use the Trend Signal with the input value 14 for the invalidations
If you enter on a BUY signal, and get a RED trend signal, exit immediately the position without waiting for any other confirmation/pullback or anything else
If you enter on a SELL signal, and get a BLUE trend signal, exit immediately the position without waiting for any other confirmation/pullback or anything else
For the trailing stop/Supertrend value, it depends of your capital and how big your stop loss should be. I personally use the settings in the Supertrend indicator
7 - Alerts
You can setup alerts for the primary and secondary signals in Tradingview so that you won't have to stare at the charts all day long. You mental healthy is my priority above everything else :)
8 - More to come
I personally use the alerts from this indicator coupled with a system to take the trades given by the tradingview alerts. I'll publish it later on if I feel the indicator collects enough interest from you guys
GZ Indicator✍️ Description:
GZ Indicator is an advanced indicator that automatically detects Golden Zones, optimal market entry zones based on the latest significant pivots. The system uses Fibonacci extensions to project precise price targets, while providing a dynamic, visual stop-loss.
Main features:
- Pivot Detection: Automatic identification of significant pivots (high/low).
- Optimal Entry Zones (OTE): Automatically calculates ideal entry zones based on Fibonacci retracements.
- Precise Targets: Displays price targets with Fibonacci extensions.
- Dynamic Stop-Loss: Visual stop-loss zone adjusted to market conditions.
- RSI and MACD display: Add an RSI and MACD chart to facilitate trend analysis and confirm your entries.
- Intelligent refresh: Automatic deletion of the active zone as soon as the stop-loss is reached.
🔥 Key features:
Automatic detection of significant pivots (highs and lows)
Dynamic calculation of the OTE (Optimal Trade Entry) zone on retracements 0.618 - 0. 705
Clear display of price targets based on extensions
Intelligent updating: old zones are retained for historical analysis
Automatic deletion of current zone if Stop-Loss is reached
Contextual RSI and MACD chart for improved trend analysis
Code optimized for minimum recalculations, fluid even on fast time units.
⚡ How to use it:
Spot the appearance of a Golden Zone.
Enter a position in the zone with RSI/MACD or price action confirmation.
Use the targets displayed to set your progressive Take-Profits.
Respect the Stop-Loss zone automatically drawn.
🛠️ Available parameters:
Activate/deactivate RSI/MACD chart
Choose number of pivots for detection
Display old targets
[⚠️ Disclaimer:
This indicator is a decision-making tool. It is not intended to be used as financial advice. Please always perform your own analysis and manage your risks properly.
🔥 Bon trading ! 🚀
Multi-Timeframe Liquidity Zones V6 (Table)Multi-Timeframe Liquidity Zones V6 (Table) Indicator: Functionality and Uses
Overview: The Multi-Timeframe Liquidity Zones V6 (Table) indicator is a technical analysis tool that highlights key volume-based support and resistance levels across multiple timeframes. It leverages volume profile concepts – specifically the Point of Control (POC) and Value Area High/Low (VAH/VAL) – to identify “liquidity zones” where trading activity was heaviest . Unlike a standard single-timeframe volume profile, this indicator compiles data from several timeframes (e.g. monthly, weekly, daily, intraday) and displays the results in a convenient table format on the chart. The goal is to give traders a consolidated view of important price levels (derived from volume concentrations) across different horizons, helping them plan trades with a broader market perspective.
Purpose and Functionality of the Indicator
Multi-Timeframe Analysis: The primary objective of this indicator is to simplify multi-timeframe analysis of volume distribution. Rather than manually checking volume profiles on separate charts for each timeframe, the tool automatically calculates the key levels for each selected timeframe and presents them together. This includes higher-level perspectives (like monthly or weekly volume hotspots) alongside shorter-term levels (daily or hourly), ensuring that traders don’t miss significant zones from any timeframe . By offering a broader perspective on support and resistance levels, multi-timeframe tools help improve risk management and signal confirmation , and this indicator is designed to provide that volume-based perspective at a glance.
Table Format Display: Multi-Timeframe Liquidity Zones V6 (Table) specifically presents the information as a table (as opposed to plotting lines on the chart). Each row in the table typically corresponds to a timeframe (for example, Monthly, Weekly, Daily, 4H, 1H, 30M, 15M), and the columns list the calculated POC, VAH, VAL, and possibly the average volume for that timeframe’s look-back period. By structuring the data in a table, traders can quickly read off the exact price levels of these liquidity zones without having to visually trace lines. This format makes it easy to compare levels across timeframes or note where multiple timeframes’ levels cluster near the same price – a sign of especially strong support/resistance. The indicator uses a user-defined number of bars or length of history for each timeframe to calculate these values (so you can adjust how far back it looks to define the volume profile for each period).
Objective: In summary, the functionality is geared toward identifying high-liquidity price zones across multiple time scales and presenting them clearly. These high-liquidity zones often coincide with areas where price reacts (stalls, reverses, or accelerates) because a lot of trading activity (hence, orders and volume) took place there in the past. The indicator’s objective is to alert the trader to those areas in advance. It effectively answers questions like: “Where are the major volume concentration levels on the 1-hour, daily, and weekly charts right now?” and “Are there overlapping volume-based support/resistance levels from different timeframes around the current price?” By compiling this information, the indicator helps traders incorporate context from multiple timeframes in their decision-making, without needing to flip through numerous charts.
Identifying Liquidity Zones with POC, VAH, and VAL
Liquidity Zones Defined: In market terms, a “liquidity zone” is an area of the chart where a significant amount of trading occurred, meaning high liquidity (many buyers and sellers exchanged volume there). These zones often act as support or resistance because past heavy trading indicates consensus or interest around those price levels. This indicator identifies liquidity zones through volume profile analysis on each timeframe’s recent price action. Essentially, it looks at the distribution of trading volume at different prices over the specified period and finds the value area – the range of prices that encompassed the majority of that volume (commonly around 70% of the total volume ). Within that value area, it pinpoints the Point of Control (POC), which is the single price level that had the highest traded volume (the peak of the volume profile) . The upper and lower boundaries of that high-volume range are marked as Value Area High (VAH) and Value Area Low (VAL) respectively . Together, the VAH and VAL define the liquidity zone where the market spent most of its time and volume, and POC highlights the most traded price in that zone.
• Point of Control (POC): The POC is the price level with the greatest volume traded for the given period. It represents the price at which the most liquidity was exchanged – effectively the market’s “center of gravity” for that timeframe’s trading activity . The indicator calculates the POC for each selected timeframe by scanning the volume at each price; the price with maximum volume is flagged as that timeframe’s POC. In the table, the POC might be highlighted or listed as a key level (sometimes traders color-code it or mark it for emphasis). Because so many positions were opened or closed at the POC, it often serves as a strong support/resistance. For example, if price falls to a major POC from above, traders expect buyers may step in there (since it was a popular buy/sell level historically), potentially causing a bounce. Conversely, if price breaks through a POC decisively, it may signal a significant shift in market acceptance.
• Value Area High (VAH) and Low (VAL): The VAH and VAL are the price boundaries of the value area, which is typically defined to contain about 70% of the total traded volume for the period . In other words, between VAH and VAL is where the “bulk” of trading occurred, and outside this range is where relatively less volume traded. The indicator derives VAH/VAL by accumulating volume from the highest-volume price (POC) outward until ~70% of volume is covered (this is a common method for volume profile value area). VAH is the top of this high-volume region and VAL is the bottom. These levels are important because they often act like support/resistance boundaries: when price is inside the value area, it’s in a high-liquidity zone and tends to oscillate between VAH and VAL; when price moves above VAH or below VAL, it’s leaving the high-volume zone, which can indicate a potential trend or imbalance (price entering a lower-liquidity area where it might move faster until finding the next liquidity zone). Traders watch VAH/VAL for signs of rejection or acceptance: for instance, a price rally that falters at VAH suggests that level is acting as resistance (sellers defending that high-volume area), whereas if price pushes above VAH, it may continue until the next timeframe’s zone or until it finds new interest. The Multi-Timeframe Liquidity Zones V6 indicator gives the VAH and VAL for each timeframe, essentially mapping out the upper and lower bounds of key liquidity zones at those scales.
How the Indicator Identifies These: Under the hood, the indicator likely uses historical price and volume data for each timeframe’s lookback window. For each timeframe (say the last 20 weekly bars for a weekly profile, last 100 daily bars for a daily profile, etc.), it constructs a volume profile (a histogram of volume at each price). From that distribution, it finds the POC (highest volume bin) and calculates VAH/VAL around it. The output is a set of numbers (price levels) that mark where those zones lie. In practice, if using the Lines version of this indicator, those levels are drawn as horizontal lines on the chart and labeled by timeframe (e.g., a line at 1.2345 labeled “D POC” for Daily POC) . In the Table version, those values are instead listed in text form. Either way, the identification process is the same – it’s finding the high-volume price regions on each timeframe and calling them out. By doing this for multiple timeframes concurrently, the indicator reveals how these liquidity zones from different periods relate to each other. For example, you might discover that a daily-chart value area overlaps with a weekly-chart POC, creating a particularly strong zone of interest. This kind of insight is hard to get from a single timeframe analysis alone.
Volume Profile Data Across Multiple Timeframes
Multiple Timeframes in One View: One of the biggest advantages of this indicator is the ability to see volume profile information from various timeframes side by side. Traders often perform multiple timeframe analysis to get a fuller picture — for instance, checking monthly or weekly levels for long-term context while planning a trade on a 4-hour chart. This indicator automates that process for volume-based levels. The table will typically list each chosen timeframe (which could be preset or user-selected). For each timeframe, you get the POC, VAH, VAL, and possibly an average volume metric. The “average volume” likely refers to the average volume per bar or the average volume traded over the profile’s duration for that timeframe, which gives a sense of how significant that period’s activity is. For example, a weekly profile might show an average volume of say 500k per week, versus a daily profile average of 80k per day – indicating the scale of trading on weekly vs daily. High average volume on a timeframe means its liquidity zones were formed with a lot of participation, possibly making them more reliable support/resistance. By comparing these, traders can gauge which timeframes had unusually high or low activity recently. The table format makes such comparisons straightforward.
Identification of Confluence: Because all the data is presented together, traders can quickly spot confluence or overlaps between timeframes. If two different timeframes show liquidity zones at similar price levels, that price becomes extremely noteworthy. For instance, suppose the indicator shows: a 1-hour POC at 1.1300, a 4-hour VAL at 1.1280, and a daily VAL at 1.1290. These are all in a tight range – effectively indicating a multi-timeframe liquidity zone around 1.1280–1.1300. A trader seeing this cluster in the table will recognize that as a strong support area, since multiple profiles from intraday to daily all suggest heavy trading interest there. Similarly, overlaps of VAH (resistance zone) from different timeframes could signal a strong ceiling. The multi-timeframe view prevents a trader from, say, going long into a major weekly POC above, or shorting when there’s a huge monthly value-area low just below – situations where awareness of higher timeframe volume structure can make the difference between a good and bad trade.
User Customization: The indicator is flexible in that you can typically adjust which timeframes to include and how many bars to use for each timeframe’s calculation. For example, one might configure it to calculate monthly levels using the past 12 monthly bars (1 year of data), weekly levels using the past 20 weeks, daily using 100 days, etc., depending on preference. By tuning the “bars count” or period length , the trader can focus on recent liquidity zones or incorporate more history if desired. Shorter lookback might catch more recent shifts in volume distribution (important if the market structure changed recently), while longer lookback gives more established levels. This customization ensures the indicator’s output can be tailored to different trading styles (short-term vs swing vs long-term investing). Regardless of settings, the multi-timeframe table allows simultaneous visibility of the chosen timeframes’ volume landscape. This comprehensive view is the core strength: it consolidates data that normally requires flipping through multiple charts.
Using the Liquidity Zones Data for Trading Decisions
Traders can use the information from the MTF Liquidity Zones V6 (Table) indicator in several practical ways to enhance their decision-making:
• Identify Support and Resistance: Each liquidity zone acts as a potential support or resistance area. For example, if the table shows a daily VAH at a certain level above the current price, that level might serve as resistance if the price rallies up to it (since it marks the top of a high-volume region where sellers might step in). Conversely, a weekly VAL below current price could act as support on a dip. By noting these levels in the table, a trader planning an entry or exit can anticipate where the price might stall or reverse. Essentially, you get a map of high-interest price levels from different timeframes, which you can mark on your trading chart for guidance.
• Plan Entries and Exits Around Key Levels: Many traders incorporate volume profile levels into their strategies, for instance: buying near VAL (betting that the value area will hold and price will revert upward), or selling/shorting near VAH (expecting the top of value to hold as resistance), or trading breakouts when price moves outside the value area. With the multi-timeframe table, one can refine these tactics by also considering higher timeframe levels. Suppose you see that on the 1-hour chart the price is just above its 1H POC, but the table indicates that just slightly above, there’s also the daily POC. You might delay a long entry until price clears that daily POC, because that could be a stronger intraday barrier. Or if you intend to take profit on a long trade, you might choose a target just below a weekly VAH since price may struggle to climb past that on the first attempt. The indicator thus acts as a guide for precision in entry/exit decisions, aligning them with where liquidity is high.
• Gauge Trend Strength and Directional Bias: By observing where current price is relative to these volume zones, traders can infer certain market conditions. For instance, if price is trading above the VAH of multiple timeframes’ value areas, it suggests the market is in a more bullish or overextended territory (price accepted above prior value), whereas if price is below multiple VALs, it’s in bearish or undervalued territory relative to recent history. If the price stays around a POC, it indicates consolidation or equilibrium (market comfortable at that price). Traders can use this context for bias – e.g., if price is above the weekly VAH, you might lean bullish but watch for potential pullbacks to that VAH level (now a support). If price is below the monthly VAL, you might avoid longs until it re-enters that value area. In essence, the liquidity zones provide context of value vs. price: is price trading within the high-volume areas (implying range-bound behavior) or outside them (implying a breakout or trending move)? This can prevent chasing trades at poor locations.
• Combine with Other Indicators/Analysis: It’s generally advised to not use any single indicator in isolation, and this holds true here. The liquidity zones from this indicator are best used alongside price action or other technical signals for confirmation . For example, if a bullish candlestick reversal pattern forms right at a confluence of a 4H VAL and Daily POC, that’s a stronger buy signal than the pattern alone. Or if an oscillator shows overbought exactly as price hits a weekly VAH, it adds conviction to a possible short. The indicator’s table basically gives you a shortlist of critical price levels; you can then watch how price behaves at those levels (via candlesticks, order flow, etc.) to make the final trade decision. Traders might set alerts for when price approaches one of the listed levels, or they might drop down to a lower timeframe to fine-tune an entry once a key zone is reached. By integrating this volume-based insight with trend analysis, chart patterns, or momentum indicators, one can make more informed and high-probability decisions rather than trading in the dark.
• Risk Management and Stop Placement: High-liquidity zones can also inform stop-loss placement. Ideally, you want your stop on the other side of a strong support/resistance. If you go long near a VAL, you might place your stop just below the VAL (since a move beyond that suggests the high-volume zone didn’t hold). If you short near a VAH, a stop just above the VAH or POC could be logical. Moreover, if multiple timeframes show overlapping zones, a stop beyond all of them could be even safer (albeit at the cost of a wider stop). The indicator helps identify those spots. It also warns you of where not to put a stop – for example, placing a stop-loss right at a POC might be unwise because price could gravitate to that POC repeatedly (due to its magnetic effect as a high-volume price). Instead, a trader might choose a stop beyond the far side of the value area. By using the table’s information, you can align your risk management with areas of high liquidity, reducing the chance of being whipsawed by normal volatility around heavily traded levels .
Benefits of the Multi-Timeframe Liquidity Zones Indicator
Using the Multi-Timeframe Liquidity Zones V6 (Table) indicator offers several key benefits for traders, ultimately aiming to streamline analysis and improve decision quality:
• Consolidated Key Levels: It provides a clear, consolidated view of crucial volume-driven levels from multiple timeframes all at once . This saves time and ensures you always account for major support/resistance zones that come from higher or lower timeframe volume clusters. You won’t accidentally overlook a significant weekly level while focused on a 15-minute chart, for example.
• Enhanced Multi-Timeframe Insight: By aligning information from long-term and short-term periods, the indicator helps traders see the “bigger picture” while still operating on their preferred timeframe. This multi-scale awareness can improve trade timing and confidence. You’re effectively doing multi-timeframe analysis with volume profiles in an efficient manner, which can confirm or caution your trade ideas (e.g., a trend looks strong on the 1H, but the table shows a huge monthly VAH just overhead – a reason to be cautious or take profit early).
• Improved Decision Making and Precision: Knowing where liquidity zones lie allows for more precise entries, exits, and stop placements. Traders can make informed decisions such as waiting for a pullback to a value area before entering, or taking profits before price hits a major POC from a higher timeframe. These decisions are grounded in objectively important price levels, potentially leading to higher probability trades and better risk-reward setups. It essentially enhances your strategy by adding a layer of volume context – you’re trading with an awareness of where the market’s interest is heaviest.
• Volume-Based Confirmation: Price alone can sometimes be deceptive, but volume tells the true story of participation. The liquidity zones indicator provides volume-based confirmation of support/resistance. If a price level is identified by this tool, it’s because significant volume happened there – adding weight to that level’s importance. This can help filter out false support/resistance levels that aren’t backed by volume. In other words, it highlights high-quality levels that many traders (and possibly institutions) have shown interest in.
• Adaptable to Different Trading Styles: Whether one is a scalper looking at intraday (15M, 5M charts) or a swing trader focusing on daily/weekly, the indicator can be configured to those needs. You choose which timeframes and how much data to consider. This means the concept of liquidity zones can be applied universally – from spotting intraday pivot levels with volume, to seeing long-term value zones on an investment. The consistent methodology of POC/VAH/VAL across scales provides a common framework to analyze any market and timeframe.
• Informed Risk Management: As discussed, the knowledge of multi-timeframe volume zones aids in risk management. By placing stops beyond major liquidity areas or avoiding trades that run into strong volume walls, traders can reduce the likelihood of whipsaw losses. It’s an extra layer of defense to ensure your trade plan accounts for where the market has historically found lots of interest (hence likely friction). This level of informed planning can be the difference between a well-managed trade and an avoidable loss.
In conclusion, the Multi-Timeframe Liquidity Zones V6 (Table) indicator serves as a powerful analytical aid, giving traders a structured view of where price is likely to encounter support or resistance based on volume concentrations across timeframes. Its functionality centers on identifying those liquidity zones (via POC, VAH, VAL) and presenting them in an easy-to-read format, while its ultimate purpose is to help traders make more informed decisions. By integrating this tool into their workflow, traders can more confidently navigate price action, knowing the objective volume-based landmarks that lie ahead. Remember that while these volume levels often coincide with strong S/R zones, it’s best to use them in conjunction with other technical or fundamental analysis for confirmation . When used appropriately, the indicator can streamline multi-timeframe analysis and enhance your overall trading strategy , giving you an edge in identifying where the market’s liquidity (and opportunity) resides.
Trend Zone Moving Averages📈 Trend Zone Moving Averages
The Trend Zone Moving Averages indicator helps traders quickly identify market trends using the 50SMA, 100SMA, and 200SMA. With dynamic background colors, customizable settings, and real-time alerts, this tool provides a clear view of bullish, bearish, and extreme trend conditions.
🔹 Features:
Trend Zones with Dynamic Background Colors
Green → Bullish Trend (50SMA > 100SMA > 200SMA, price above 50SMA)
Red → Bearish Trend (50SMA < 100SMA < 200SMA, price below 50SMA)
Yellow → Neutral Trend (Mixed signals)
Dark Green → Extreme Bullish (Price above all three SMAs)
Dark Red → Extreme Bearish (Price below all three SMAs)
Customizable Moving Averages
Toggle 50SMA, 100SMA, and 200SMA on/off from the settings.
Perfect for traders who prefer a cleaner chart.
Real-Time Trend Alerts
Get instant notifications when the trend changes:
🟢 Bullish Zone Alert – When price enters a bullish trend.
🔴 Bearish Zone Alert – When price enters a bearish trend.
🟡 Neutral Zone Alert – When trend shifts to neutral.
🌟 Extreme Bullish Alert – When price moves above all SMAs.
⚠️ Extreme Bearish Alert – When price drops below all SMAs.
✅ Perfect for Any Market
Works on stocks, forex, crypto, and commodities.
Adaptable for day traders, swing traders, and investors.
⚙️ How to Use: Trend Zone Moving Averages Strategy
This strategy helps traders identify and trade with the trend using the Trend Zone Moving Averages indicator. It works across stocks, forex, crypto, and commodities.
🟢 Bullish Trend Strategy (Green Background)
Objective: Look for buying opportunities when the market is in an uptrend.
Entry Conditions:
✅ Background is Green (Bullish Zone).
✅ Price is above the 50SMA (confirming strength).
✅ Price pulls back to the 50SMA and bounces OR breaks above a key resistance level.
Stop Loss:
🔹 Place below the most recent swing low or just under the 50SMA.
Take Profit:
🔹 First target at the next resistance level or recent swing high.
🔹 Second target if price continues higher—trail stops to lock in profits.
🔴 Bearish Trend Strategy (Red Background)
Objective: Look for shorting opportunities when the market is in a downtrend.
Entry Conditions:
✅ Background is Red (Bearish Zone).
✅ Price is below the 50SMA (confirming weakness).
✅ Price pulls back to the 50SMA and rejects OR breaks below a key support level.
Stop Loss:
🔹 Place above the most recent swing high or just above the 50SMA.
Take Profit:
🔹 First target at the next support level or recent swing low.
🔹 Second target if price keeps falling—trail stops to secure profits.
🌟 Extreme Trend Strategy (Dark Green / Dark Red Background)
Objective: Trade with momentum when the market is in a strong trend.
Entry Conditions:
✅ Dark Green Background → Extreme Bullish: Price is above all three SMAs (strong uptrend).
✅ Dark Red Background → Extreme Bearish: Price is below all three SMAs (strong downtrend).
Trade Execution:
🔹 For longs (Dark Green): Look for breakout entries above resistance or pullbacks to the 50SMA.
🔹 For shorts (Dark Red): Look for breakdown entries below support or rejections at the 50SMA.
Risk Management:
🔹 Use tighter stop losses and trail profits aggressively to maximize gains.
🟡 Neutral Trend Strategy (Yellow Background)
Objective: Avoid trading or wait for a breakout.
What to Do:
🔹 Avoid trading in this zone—price is indecisive.
🔹 Wait for confirmation (background turns green/red) before taking a trade.
🔹 Use alerts to notify you when the trend resumes.
📌 Final Tips
Use this strategy with price action for extra confirmation.
Combine with support/resistance levels to improve accuracy.
Set alerts for trend changes so you never miss an opportunity.
Enjoy!
Simple APF Strategy Backtesting [The Quant Science]Simple backtesting strategy for the quantitative indicator Autocorrelation Price Forecasting. This is a Buy & Sell strategy that operates exclusively with long orders. It opens long positions and generates profit based on the future price forecast provided by the indicator. It's particularly suitable for trend-following trading strategies or directional markets with an established trend.
Main functions
1. Cycle Detection: Utilize autocorrelation to identify repetitive market behaviors and cycles.
2. Forecasting for Backtesting: Simulate trades and assess the profitability of various strategies based on future price predictions.
Logic
The strategy works as follow:
Entry Condition: Go long if the hypothetical gain exceeds the threshold gain (configurable by user interface).
Position Management: Sets a take-profit level based on the future price.
Position Sizing: Automatically calculates the order size as a percentage of the equity.
No Stop-Loss: this strategy doesn't includes any stop loss.
Example Use Case
A trader analyzes a dayli period using 7 historical bars for autocorrelation.
Sets a threshold gain of 20 points using a 5% of the equity for each trade.
Evaluates the effectiveness of a long-only strategy in this period to assess its profitability and risk-adjusted performance.
User Interface
Length: Set the length of the data used in the autocorrelation price forecasting model.
Thresold Gain: Minimum value to be considered for opening trades based on future price forecast.
Order Size: percentage size of the equity used for each single trade.
Strategy Limit
This strategy does not use a stop loss. If the price continues to drop and the future price forecast is incorrect, the trader may incur a loss or have their capital locked in the losing trade.
Disclaimer!
This is a simple template. Use the code as a starting point rather than a finished solution. The script does not include important parameters, so use it solely for educational purposes or as a boilerplate.
MangAlgo X-V61. Overview & Purpose
The MangAlgo X-V6 script is a multi-component indicator designed to generate buy and sell signals on TradingView charts by combining several technical analysis techniques. It is tailored for various trading styles – including Scalping, Day Trading, and the custom MangAlgo approach – by automatically adjusting parameters based on the selected preset. The primary goal of the script is to deliver more accurate signals by integrating additional filters and a robust trade management system.
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2. Key Features
• Trading Style Presets
• Three preset options: Scalping, Day Trading, and MangAlgo.
• The selected preset automatically adjusts key parameters such as Moving Average (MA) lengths, additional MA filters, and other settings to suit the trading style.
• SL/TP Settings (Stop Loss / Take Profit)
• Adjustable ATR multiplier for calculating the stop loss (SL).
• Multi-level TP (up to 5 levels) based on a configurable risk-reward ratio.
• Multiple Moving Average Types
• Supports various MA types: SMA, EMA, WMA, or VWMA (default is based on conditions).
• Two sets of MAs:
• Fast and Slow MAs for detecting crossovers as primary signals.
• Additional MA Filters (three additional MAs) used as further confirmation.
• Higher Timeframe Filter (HTF)
• Incorporates a moving average from a higher timeframe to provide broader trend context.
• The HTF MA is smoothed using SMA to ensure a stable trend indication.
• SuperTrend Indicator
• Calculates the SuperTrend level using ATR and a configurable multiplier (“Magic Number Factor”).
• Displays a dynamic trend line that changes color: green for an uptrend and red for a downtrend.
• Momentum & Candle Size Filters
• The momentum filter measures price strength using a momentum function over a set period.
• Optional candle size filtering allows you to disregard signals based on minimum and maximum candle sizes to reduce market noise.
• Session Filters
• Optionally filter signals based on trading sessions (New York, London, Tokyo, Sydney) to avoid low-liquidity periods.
• Directional Movement Index (DI)
• Computes DI+ and DI– using a smoothed True Range.
• Acts as an additional filter: a buy signal is valid if DI+ is greater than DI–, and vice versa for sell signals.
• Trade Signal Execution & Management
• Entry Signals:
• Buy: Triggered when the fast MA crosses above the slow MA, supported by SuperTrend, HTF MA, additional MAs, momentum, and DI confirmation (DI+ > DI–).
• Sell: Triggered when the fast MA crosses below the slow MA with corresponding filter confirmations (DI– > DI+).
• SL and TP Setup:
• The stop loss is computed using ATR and adjusted with a trailing SL as take profit levels are reached.
• TP levels (up to 5) are calculated based on the initial risk and a configurable risk-reward ratio.
• Visual Signal & Trade Outcome Display:
• Displays “𝗕𝗨𝗬” and “𝗦𝗘𝗟𝗟” labels on the chart when signals are active.
• Additional labels indicate SL and TP levels and whether the trade outcome was a win or loss once the SL is hit.
• Logging & Trade Statistics (Optional)
• Internal logging records trade details for each confirmed candle, helping you review strategy performance.
• An optional table display shows a summary of trade counts, win/loss results, and win rate percentages.
• Custom Candle Plotting
• Instead of using the standard barcolor(), the script uses plotcandle() to color the candles based on the active trade status:
• Green: Indicates an active buy position.
• Blue: Indicates an active sell position.
• Default colors: When no trade is active.
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3. How It Works & Component Interaction
1. Preset Trading Style Selection:
• Users choose a trading style preset via the input, which sets the values for key parameters such as the type and length of MAs, additional filters, and more.
2. Core Technical Calculations:
• ATR Calculation: Used for range detection and setting the stop loss.
• Moving Averages: Computed through a custom function (f_ma()) based on the chosen MA type.
• Range Detection: The script identifies price ranges by comparing the price to the MA, visualizing the range with boxes and lines.
3. Trend Filtering & Signal Confirmation:
• SuperTrend: Computed using ATR and a multiplier to dynamically generate support/resistance levels.
• Higher Timeframe MA: Provides macro trend context by analyzing a higher timeframe’s data.
• Additional MA & Momentum Filters: Ensure that the price movement is not mere noise, but confirmed by extra layers of filtering.
• DI (Directional Movement): Validates entry signals by ensuring that the directional momentum (DI+) dominates for buys and DI– for sells.
4. Signal Execution & Trade Management:
• When all conditions are met (including session filtering and non-range conditions), a buy or sell signal is activated.
• Upon signal activation, a trade is initiated with a calculated SL and multiple TP levels based on risk parameters.
• As the price reaches a TP level, the script adjusts the stop loss (trailing SL) to lock in gains.
• Trade outcomes (win or lose) are visually labeled on the chart after the SL is hit.
5. Visualization & Logging:
• Trading signals and SL/TP levels are plotted on the chart.
• Custom candle plotting highlights active trades by altering candle colors.
• Trade logging captures detailed information for each candle, which can be used for performance evaluation.
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4. How to Use the Script
• Initial Setup:
• Select your preferred trading style preset (e.g., Scalping, Day Trading, or MangAlgo).
• Adjust additional input parameters if needed, such as the ATR multiplier, number of TPs, or session filters.
• Interpreting Signals:
• Look for “𝗕𝗨𝗬” and “𝗦𝗘𝗟𝗟” labels on the chart as indicators of entry points.
• Use the plotted SL and TP levels as guides for risk management.
• Utilizing Additional Filters:
• Optionally enable the candle size filter and session filters to reduce false signals.
• Regularly monitor the chart and remember that this indicator is a tool that combines multiple technical methods for better signal accuracy.
• Trade Management:
• Use the provided trade outcome labels and logging information to assess and refine your strategy over time.
• If activated, review the trade summary table to analyze overall performance statistics.
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5. Risk Disclaimer
Trading involves significant risk and may not be suitable for all investors.
The MangAlgo X-V6 script is provided for educational and informational purposes only. Past performance is not indicative of future results. Trading decisions based on this script are at the sole discretion of the user, and the creator or distributor of the script is not responsible for any financial losses incurred. Always perform your own analysis, use proper risk management techniques, and consult with a professional financial advisor if necessary.
Aggressive Strategy for High IV Market### Strategic background
In a volatile high IV market, prices are volatile and market expectations of future uncertainty are high. This environment provides opportunities for aggressive trading strategies, but also comes with a high level of risk. In pursuit of a high Sharpe ratio (i.e., risk-adjusted return), we need to design a strategy that captures the benefits of market volatility while effectively controlling risk. Based on daily line cycles, I choose a combination of trend tracking and volatility filtering for highly volatile assets such as stocks, futures or cryptocurrencies.
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### Strategy framework
#### Data
- Use daily data, including opening, closing, high and low prices.
- Suitable for highly volatile markets such as technology stocks, cryptocurrencies or volatile index futures.
#### Core indicators
1. ** Trend Indicators ** :
Fast Exponential Moving Average (EMA_fast) : 10-day EMA, used to capture short-term trends.
- Slow Exponential Moving Average (EMA_slow) : 30-day EMA, used to determine the long-term trend.
2. ** Volatility Indicators ** :
Average true Volatility (ATR) : 14-day ATR, used to measure market volatility.
- ATR mean (ATR_mean) : A simple moving average of the 20-day ATR that serves as a volatility benchmark.
- ATR standard deviation (ATR_std) : The standard deviation of the 20-day ATR, which is used to judge extreme changes in volatility.
#### Trading logic
The strategy is based on a trend following approach of double moving averages and filters volatility through ATR indicators, ensuring that trading only in a high-volatility environment is in line with aggressive and high sharpe ratio goals.
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### Entry and exit conditions
#### Admission conditions
- ** Multiple entry ** :
- EMA_fast Crosses EMA_slow (gold cross), indicating that the short-term trend is turning upward.
-ATR > ATR_mean + 1 * ATR_std indicates that the current volatility is above average and the market is in a state of high volatility.
- ** Short Entry ** :
- EMA_fast Crosses EMA_slow (dead cross) downward, indicating that the short-term trend turns downward.
-ATR > ATR_mean + 1 * ATR_std, confirming high volatility.
#### Appearance conditions
- ** Long show ** :
- EMA_fast Enters the EMA_slow (dead cross) downward, and the trend reverses.
- or ATR < ATR_mean-1 * ATR_std, volatility decreases significantly and the market calms down.
- ** Bear out ** :
- EMA_fast Crosses the EMA_slow (gold cross) on the top, and the trend reverses.
- or ATR < ATR_mean-1 * ATR_std, the volatility is reduced.
---
### Risk management
To control the high risk associated with aggressive strategies, set up the following mechanisms:
1. ** Stop loss ** :
- Long: Entry price - 2 * ATR.
- Short: Entry price + 2 * ATR.
- Dynamic stop loss based on ATR can adapt to market volatility changes.
2. ** Stop profit ** :
- Fixed profit target can be selected (e.g. entry price ± 4 * ATR).
- Or use trailing stop losses to lock in profits following price movements.
3. ** Location Management ** :
- Reduce positions appropriately in times of high volatility, such as dynamically adjusting position size according to ATR, ensuring that the risk of a single trade does not exceed 1%-2% of the account capital.
---
### Strategy features
- ** Aggressiveness ** : By trading only in a high ATR environment, the strategy takes full advantage of market volatility and pursues greater returns.
- ** High Sharpe ratio potential ** : Trend tracking combined with volatility filtering to avoid ineffective trades during periods of low volatility and improve the ratio of return to risk.
- ** Daily line Cycle ** : Based on daily line data, suitable for traders who operate frequently but are not too complex.
---
### Implementation steps
1. ** Data Preparation ** :
- Get the daily data of the target asset.
- Calculate EMA_fast (10 days), EMA_slow (30 days), ATR (14 days), ATR_mean (20 days), and ATR_std (20 days).
2. ** Signal generation ** :
- Check EMA cross signals and ATR conditions daily to generate long/short signals.
3. ** Execute trades ** :
- Enter according to the signal, set stop loss and profit.
- Monitor exit conditions and close positions in time.
4. ** Backtest and Optimization ** :
- Use historical data to backtest strategies to evaluate Sharpe ratios, maximum retracements, and win rates.
- Optimize parameters such as EMA period and ATR threshold to improve policy performance.
---
### Precautions
- ** Trading costs ** : Highly volatile markets may result in frequent trading, and the impact of fees and slippage on earnings needs to be considered.
- ** Risk Control ** : Aggressive strategies may face large retracements and need to strictly implement stop losses.
- ** Scalability ** : Additional metrics (such as volume or VIX) can be added to enhance strategy robustness, or combined with machine learning to predict trends and volatility.
---
### Summary
This is a trend following strategy based on dual moving averages and ATR, designed for volatile high IV markets. By entering into high volatility and exiting into low volatility, the strategy combines aggressive and risk-adjusted returns for traders seeking a high sharpe ratio. It is recommended to fully backtest before implementation and adjust the parameters according to the specific market.
[3Commas] HA & MAHA & MA
🔷What it does: This tool is designed to test a trend-following strategy using Heikin Ashi candles and moving averages. It enters trades after pullbacks, aiming to let profits run once the risk-to-reward ratio reaches 1:1 while securing the position.
🔷Who is it for: It is ideal for traders looking to compare final results using fixed versus dynamic take profits by adjusting parameters and trade direction—a concept applicable to most trading strategies.
🔷How does it work: We use moving averages to define the market trend, then wait for opposite Heikin Ashi candles to form against it. Once these candles reverse in favor of the trend, we enter the trade, using the last swing created by the pullback as the stop loss. By applying the breakeven ratio, we protect the trade and let it run, using the slower moving average as a trailing stop.
A buy signal is generated when:
The previous candle is bearish (ha_bear ), indicating a pullback.
The fast moving average (ma1) is above the slow moving average (ma2), confirming an uptrend.
The current candle is bullish (ha_bull), showing trend continuation.
The Heikin Ashi close is above the fast moving average (ma1), reinforcing the bullish bias.
The real price close is above the open (close > open), ensuring bullish momentum in actual price data.
The signal is confirmed on the closed candle (barstate.isconfirmed) to avoid premature signals.
dir is undefined (na(dir)), preventing repeated signals in the same direction.
A sell signal is generated when:
The previous candle is bullish (ha_bull ), indicating a temporary upward move before a potential reversal.
The fast moving average (ma1) is below the slow moving average (ma2), confirming a downtrend.
The current candle is bearish (ha_bear), showing trend continuation to the downside.
The Heikin Ashi close is below the fast moving average (ma1), reinforcing bearish pressure.
The real price close is below the open (close < open), confirming bearish momentum in actual price data.
The signal is confirmed after the candle closes (barstate.isconfirmed), avoiding premature entries.
dir is undefined (na(dir)), preventing consecutive signals in the same direction.
In simple terms, this setup looks for trend continuation after a pullback, confirming entries with both Heikin Ashi and real price action, supported by moving average alignment to avoid false signals.
If the price reaches a 1:1 risk-to-reward ratio, the stop will be moved to the entry point. However, if the slow moving average surpasses this level, it will become the new exit point, acting as a trailing stop
🔷Why It’s Unique
Easily visualizes the benefits of using risk-to-reward ratios when trading instead of fixed percentages.
Provides a simple and straightforward approach to trading, embracing the "keep it simple" concept.
Offers clear visualization of DCA Bot entry and exit points based on user preferences.
Includes an option to review the message format before sending signals to bots, with compatibility for multi-pair and futures contract pairs.
🔷 Considerations Before Using the Indicator
⚠️Very important: The indicator must be used on charts with real price data, such as Japanese candlesticks, line charts, etc. Do not use it on Heikin Ashi charts, as this may lead to unrealistic results.
🔸Since this is a trend-following strategy, use it on timeframes above 4 hours, where market noise is reduced and trends are clearer. Also, carefully review the statistics before using it, focusing on pairs that tend to have long periods of well-defined trends.
🔸Disadvantages:
False Signals in Ranges: Consolidating markets can generate unreliable signals.
Lagging Indicator: Being based on moving averages, it may react late to sudden price movements.
🔸Advantages:
Trend Focused: Simplifies the identification of trending markets.
Noise Reduction: Uses Heikin Ashi candles to identify trend continuation after pullbacks.
Broad Applicability: Suitable for forex, crypto, stocks, and commodities.
🔸The strategy provides a systematic way to analyze markets but does not guarantee successful outcomes. Use it as an additional tool rather than relying solely on an automated system.
Trading results depend on various factors, including market conditions, trader discipline, and risk management. Past performance does not ensure future success, so always approach the market cautiously.
🔸Risk Management: Define stop-loss levels, position sizes, and profit targets before entering any trade. Be prepared for potential losses and ensure your approach aligns with your overall trading plan.
🔷 STRATEGY PROPERTIES
Symbol: BINANCE:BTCUSDT (Spot).
Timeframe: 4h.
Test Period: All historical data available.
Initial Capital: 10000 USDT.
Order Size per Trade: 1% of Capital, you can use a higher value e.g. 5%, be cautious that the Max Drawdown does not exceed 10%, as it would indicate a very risky trading approach.
Commission: Binance commission 0.1%, adjust according to the exchange being used, lower numbers will generate unrealistic results. By using low values e.g. 5%, it allows us to adapt over time and check the functioning of the strategy.
Slippage: 5 ticks, for pairs with low liquidity or very large orders, this number should be increased as the order may not be filled at the desired level.
Margin for Long and Short Positions: 100%.
Indicator Settings: Default Configuration.
MA1 Length: 9.
MA2 Length: 18.
MA Calculations: EMA.
Take Profit Ratio: Disable. Ratio 1:4.
Breakeven Ratio: Enable, Ratio 1:1.
Strategy: Long & Short.
🔷 STRATEGY RESULTS
⚠️Remember, past results do not guarantee future performance.
Net Profit: +324.88 USDT (+3.25%).
Max Drawdown: -81.18 USDT (-0.78%).
Total Closed Trades: 672.
Percent Profitable: 35.57%.
Profit Factor: 1.347.
Average Trade: +0.48 USDT (+0.48%).
Average # Bars in Trades: 13.
🔷 HOW TO USE
🔸 Adjust Settings:
The default values—MA1 (9) and MA2 (18) with EMA calculation—generally work well. However, you can increase these values, such as 20 and 40, to better identify stronger trends.
🔸 Choose a Symbol that Typically Trends:
Select an asset that tends to form clear trends. Keep in mind that the Strategy Tester results may show poor performance for certain assets, making them less suitable for sending signals to bots.
🔸 Experiment with Ratios:
Test different take profit and breakeven ratios to compare various scenarios—especially to observe how the strategy performs when only the trade is protected.
🔸This is an example of how protecting the trade works: once the price moves in favor of the position with a 1:1 risk-to-reward ratio, the stop loss is moved to the entry price. If the Slow MA surpasses this level, it will act as a trailing stop, aiming to follow the trend and maximize potential gains.
🔸In contrast, in this example, for the same trade, if we set a take profit at a 1:3 risk-to-reward ratio—which is generally considered a good risk-reward relationship—we can see how a significant portion of the upward move is left on the table.
🔸Results Review:
It is important to check the Max Drawdown. This value should ideally not exceed 10% of your capital. Consider adjusting the trade size to ensure this threshold is not surpassed.
Remember to include the correct values for commission and slippage according to the symbol and exchange where you are conducting the tests. Otherwise, the results will not be realistic.
If you are satisfied with the results, you may consider automating your trades. However, it is strongly recommended to use a small amount of capital or a demo account to test proper execution before committing real funds.
🔸Create alerts to trigger the DCA Bot:
Verify Messages: Ensure the message matches the one specified by the DCA Bot.
Multi-Pair Configuration: For multi-pair setups, enable the option to add the symbol in the correct format.
Signal Settings: Enable whether you want to receive long or short signals (Entry | TP | SL), copy and paste the the messages for the DCA Bots configured.
Alert Setup:
When creating an alert, set the condition to the indicator and choose "alert() function call only.
Enter any desired Alert Name.
Open the Notifications tab, enable Webhook URL, and paste the Webhook URL.
For more details, refer to the section: "How to use TradingView Custom Signals".
Finalize Alerts: Click Create, you're done! Alerts will now be sent automatically in the correct format.
🔷 INDICATOR SETTINGS
MA 1: Fast MA Length
MA 2: Slow MA Length
MA Calc: MA's Calculations (SMA,EMA, RMA,WMA)
TP Ratio: This is the take profit ratio relative to the stop loss, where the trade will be closed in profit.
BE Ratio: This is the breakeven ratio relative to the stop loss, where the stop loss will be updated to breakeven or if the MA2 is greater than this level.
Strategy: Order Type direction in which trades are executed.
Use Custom Test Period: When enabled signals only works in the selected time window. If disabled it will use all historical data available on the chart.
Test Start and End: Once the Custom Test Period is enabled, here you select the start and end date that you want to analyze.
Check Messages: Enable the table to review the messages to be sent to the bot.
Entry | TP | SL: Enable this options to send Buy Entry, Take Profit (TP), and Stop Loss (SL) signals.
Deal Entry and Deal Exit : Copy and paste the message for the deal start signal and close order at Market Price of the DCA Bot. This is the message that will be sent with the alert to the Bot, you must verify that it is the same as the bot so that it can process properly so that it executes and starts the trade.
DCA Bot Multi-Pair: You must activate it if you want to use the signals in a DCA Bot Multi-pair in the text box you must enter (using the correct format) the symbol in which you are creating the alert, you can check the format of each symbol when you create the bot.
👨🏻💻💭 We hope this tool helps enhance your trading. Your feedback is invaluable, so feel free to share any suggestions for improvements or new features you'd like to see implemented.
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The information and publications within the 3Commas TradingView account are not meant to be and do not constitute financial, investment, trading, or other types of advice or recommendations supplied or endorsed by 3Commas and any of the parties acting on behalf of 3Commas, including its employees, contractors, ambassadors, etc.
