888 BOT #backtest█ 888 BOT #backtest (open source)
This is an Expert Advisor 'EA' or Automated trading script for ‘longs’ and ‘shorts’, which uses only a Take Profit or, in the worst case, a Stop Loss to close the trade.
It's a much improved version of the previous ‘Repanocha’. It doesn`t use 'Trailing Stop' or 'security()' functions (although using a security function doesn`t mean that the script repaints) and all signals are confirmed, therefore the script doesn`t repaint in alert mode and is accurate in backtest mode.
Apart from the previous indicators, some more and other functions have been added for Stop-Loss, re-entry and leverage.
It uses 8 indicators, (many of you already know what they are, but in case there is someone new), these are the following:
1. Jurik Moving Average
It's a moving average created by Mark Jurik for professionals which eliminates the 'lag' or delay of the signal. It's better than other moving averages like EMA , DEMA , AMA or T3.
There are two ways to decrease noise using JMA . Increasing the 'LENGTH' parameter will cause JMA to move more slowly and therefore reduce noise at the expense of adding 'lag'
The 'JMA LENGTH', 'PHASE' and 'POWER' parameters offer a way to select the optimal balance between 'lag' and over boost.
Green: Bullish , Red: Bearish .
2. Range filter
Created by Donovan Wall, its function is to filter or eliminate noise and to better determine the price trend in the short term.
First, a uniform average price range 'SAMPLING PERIOD' is calculated for the filter base and multiplied by a specific quantity 'RANGE MULTIPLIER'.
The filter is then calculated by adjusting price movements that do not exceed the specified range.
Finally, the target ranges are plotted to show the prices that will trigger the filter movement.
Green: Bullish , Red: Bearish .
3. Average Directional Index ( ADX Classic) and ( ADX Masanakamura)
It's an indicator designed by Welles Wilder to measure the strength and direction of the market trend. The price movement is strong when the ADX has a positive slope and is above a certain minimum level 'ADX THRESHOLD' and for a given period 'ADX LENGTH'.
The green color of the bars indicates that the trend is bullish and that the ADX is above the level established by the threshold.
The red color of the bars indicates that the trend is down and that the ADX is above the threshold level.
The orange color of the bars indicates that the price is not strong and will surely lateralize.
You can choose between the classic option and the one created by a certain 'Masanakamura'. The main difference between the two is that in the first it uses RMA () and in the second SMA () in its calculation.
4. Parabolic SAR
This indicator, also created by Welles Wilder, places points that help define a trend. The Parabolic SAR can follow the price above or below, the peculiarity that it offers is that when the price touches the indicator, it jumps to the other side of the price (if the Parabolic SAR was below the price it jumps up and vice versa) to a distance predetermined by the indicator. At this time the indicator continues to follow the price, reducing the distance with each candle until it is finally touched again by the price and the process starts again. This procedure explains the name of the indicator: the Parabolic SAR follows the price generating a characteristic parabolic shape, when the price touches it, stops and turns ( SAR is the acronym for 'stop and reverse'), giving rise to a new cycle. When the points are below the price, the trend is up, while the points above the price indicate a downward trend.
5. RSI with Volume
This indicator was created by LazyBear from the popular RSI .
The RSI is an oscillator-type indicator used in technical analysis and also created by Welles Wilder that shows the strength of the price by comparing individual movements up or down in successive closing prices.
LazyBear added a volume parameter that makes it more accurate to the market movement.
A good way to use RSI is by considering the 50 'RSI CENTER LINE' centerline. When the oscillator is above, the trend is bullish and when it is below, the trend is bearish .
6. Moving Average Convergence Divergence ( MACD ) and ( MAC-Z )
It was created by Gerald Appel. Subsequently, the histogram was added to anticipate the crossing of MA. Broadly speaking, we can say that the MACD is an oscillator consisting of two moving averages that rotate around the zero line. The MACD line is the difference between a short moving average 'MACD FAST MA LENGTH' and a long moving average 'MACD SLOW MA LENGTH'. It's an indicator that allows us to have a reference on the trend of the asset on which it is operating, thus generating market entry and exit signals.
We can talk about a bull market when the MACD histogram is above the zero line, along with the signal line, while we are talking about a bear market when the MACD histogram is below the zero line.
There is the option of using the MAC-Z indicator created by LazyBear, which according to its author is more effective, by using the parameter VWAP ( volume weighted average price ) 'Z-VWAP LENGTH' together with a standard deviation 'STDEV LENGTH' in its calculation.
7. Volume Condition
Volume indicates the number of participants in this war between bulls and bears, the more volume the more likely the price will move in favor of the trend. A low trading volume indicates a lower number of participants and interest in the instrument in question. Low volumes may reveal weakness behind a price movement.
With this condition, those signals whose volume is less than the volume SMA for a period 'SMA VOLUME LENGTH' multiplied by a factor 'VOLUME FACTOR' are filtered. In addition, it determines the leverage used, the more volume , the more participants, the more probability that the price will move in our favor, that is, we can use more leverage. The leverage in this script is determined by how many times the volume is above the SMA line.
The maximum leverage is 8.
8. Bollinger Bands
This indicator was created by John Bollinger and consists of three bands that are drawn superimposed on the price evolution graph.
The central band is a moving average, normally a simple moving average calculated with 20 periods is used. ('BB LENGTH' Number of periods of the moving average)
The upper band is calculated by adding the value of the simple moving average X times the standard deviation of the moving average. ('BB MULTIPLIER' Number of times the standard deviation of the moving average)
The lower band is calculated by subtracting the simple moving average X times the standard deviation of the moving average.
the band between the upper and lower bands contains, statistically, almost 90% of the possible price variations, which means that any movement of the price outside the bands has special relevance.
In practical terms, Bollinger bands behave as if they were an elastic band so that, if the price touches them, it has a high probability of bouncing.
Sometimes, after the entry order is filled, the price is returned to the opposite side. If price touch the Bollinger band in the same previous conditions, another order is filled in the same direction of the position to improve the average entry price, (% MINIMUM BETTER PRICE ': Minimum price for the re-entry to be executed and that is better than the price of the previous position in a given %) in this way we give the trade a chance that the Take Profit is executed before. The downside is that the position is doubled in size. 'ACTIVATE DIVIDE TP': Divide the size of the TP in half. More probability of the trade closing but less profit.
█ STOP LOSS and RISK MANAGEMENT.
A good risk management is what can make your equity go up or be liquidated.
The % risk is the percentage of our capital that we are willing to lose by operation. This is recommended to be between 1-5%.
% Risk: (% Stop Loss x % Equity per trade x Leverage) / 100
First the strategy is calculated with Stop Loss, then the risk per operation is determined and from there, the amount per operation is calculated and not vice versa.
In this script you can use a normal Stop Loss or one according to the ATR. Also activate the option to trigger it earlier if the risk percentage is reached. '% RISK ALLOWED'
'STOP LOSS CONFIRMED': The Stop Loss is only activated if the closing of the previous bar is in the loss limit condition. It's useful to prevent the SL from triggering when they do a ‘pump’ to sweep Stops and then return the price to the previous state.
█ BACKTEST
The objective of the Backtest is to evaluate the effectiveness of our strategy. A good Backtest is determined by some parameters such as:
- RECOVERY FACTOR: It consists of dividing the 'net profit' by the 'drawdown’. An excellent trading system has a recovery factor of 10 or more; that is, it generates 10 times more net profit than drawdown.
- PROFIT FACTOR: The ‘Profit Factor’ is another popular measure of system performance. It's as simple as dividing what win trades earn by what loser trades lose. If the strategy is profitable then by definition the 'Profit Factor' is going to be greater than 1. Strategies that are not profitable produce profit factors less than one. A good system has a profit factor of 2 or more. The good thing about the ‘Profit Factor’ is that it tells us what we are going to earn for each dollar we lose. A profit factor of 2.5 tells us that for every dollar we lose operating we will earn 2.5.
- SHARPE: (Return system - Return without risk) / Deviation of returns.
When the variations of gains and losses are very high, the deviation is very high and that leads to a very poor ‘Sharpe’ ratio. If the operations are very close to the average (little deviation) the result is a fairly high 'Sharpe' ratio. If a strategy has a 'Sharpe' ratio greater than 1 it is a good strategy. If it has a 'Sharpe' ratio greater than 2, it is excellent. If it has a ‘Sharpe’ ratio less than 1 then we don't know if it is good or bad, we have to look at other parameters.
- MATHEMATICAL EXPECTATION: (% winning trades X average profit) + (% losing trades X average loss).
To earn money with a Trading system, it is not necessary to win all the operations, what is really important is the final result of the operation. A Trading system has to have positive mathematical expectation as is the case with this script: ME = (0.87 x 30.74$) - (0.13 x 56.16$) = (26.74 - 7.30) = 19.44$ > 0
The game of roulette, for example, has negative mathematical expectation for the player, it can have positive winning streaks, but in the long term, if you continue playing you will end up losing, and casinos know this very well.
PARAMETERS
'BACKTEST DAYS': Number of days back of historical data for the calculation of the Backtest.
'ENTRY TYPE': For '% EQUITY' if you have $ 10,000 of capital and select 7.5%, for example, your entry would be $ 750 without leverage. If you select CONTRACTS for the 'BTCUSDT' pair, for example, it would be the amount in 'Bitcoins' and if you select 'CASH' it would be the amount in $ dollars.
'QUANTITY (LEVERAGE 1X)': The amount for an entry with X1 leverage according to the previous section.
'MAXIMUM LEVERAGE': It's the maximum allowed multiplier of the quantity entered in the previous section according to the volume condition.
The settings are for Bitcoin at Binance Futures (BTC: USDTPERP) in 15 minutes.
For other pairs and other timeframes, the settings have to be adjusted again. And within a month, the settings will be different because we all know the market and the trend are changing.
Cari dalam skrip untuk "rsi"
HFT Fibonacci Bands BacktesterDefault Settings are meant to be used in XBT/USD chart on 15 min time frame. If you want to use for another asset on another time frame YOU MUST CHANGE THE SETTINGS
This is a Fibonacci bands based trading strategy developed by HFT Research. It is a highly customizable strategy and provides endless opportunities to find profitable trades in the market.
Use Fib BB
This is the main decision maker of the strategy. Tuning the settings of this portion of the strategy will change the outcome the most. We have provided default settings. However, they are only good for 15min chart on Bitcoin . Please adjust accordingly.
Fib BB Length: This setting adjusts the middle line of your Fibonacci Bands. It is the moving average that you take it as base for your Fibonacci bands. Default value is currently 20.
Fib Level to Use for Entry: Here, you adjust which one of the Fibonacci Ratio levels you would like to use for your entry. You can only choose one of the following options.
Fibonacci Ratio 1
This is your Fib ratio level 1 and you can put any number here you would like
Fibonacci Ratio 2
This is your Fib ratio level 2 and you can put any number here you would like
Fibonacci Ratio 3
This is your Fib ratio level 3 and you can put any number here you would like
Please keep in mind that Ratio 1 should be higher than Ratio 2 and Ratio 2 should be higher than Ratio 3.
Use RSI
You can also turn on and off the RSI as well. Alternatively, there is an option to use RSI on a different time frame than you are currently on. For example, if you are looking at the 5min chart to use Bollinger bands but you would like to look at the RSI value on the 15min chart. You can do so by selecting the custom RSI timeframe as well as adjusting the Oversold and Overbought value.
Use CCI
Commodity Channel Index is an indicator developed by Donald Lambert. It is a momentum-based oscillator used to help determine when an investment vehicle is reaching conditions of being overbought or oversold. It also used to asses price trend direction and strength. Default settings are usually the safest and the best fit.
Use VWAP
VWAP stands for volume weighted average price . It is an extremely useful indicator when trading intra-day. It does reset every trading session which is at 00:00 UTC . Instead of looking at x number of candles and providing an average price, it will take into consideration volume that’s traded at a certain price and weigh it accordingly.
Use ADX
ADX stands for average directional index . It is an indicator that measures volatility in the market. Unfortunately, the worst market condition for this strategy is sideways market. ADX becomes a useful tool since it can detect trend. If the volatility is low and there is no real price movement, ADX will pick that up and will not let you get in trades during a sideways market. It will allow you to enter trades only when the market is trending.
Use MA Filters
Lookback: It is an option to look back x number of candles to validate the price crossing. If the market is choppy and the price keeps crossing up and down the moving average you have chosen, it will generate a lot of “noisy” signals. This option allows you to confirm the cross by selecting how many candles the price needs to stay above or below the moving average. Setting it 0 will turn it off.
MA Filter Type: There is a selection of moving averages that is available on TradingView currently. You can choose from 14 different moving average types to detect the trend as accurate as possible.
Filter Length: You can select the length of your moving average. Most commonly used length being 50,100 and 200.
Filter Type: This is our propriety smoothing method in order to make the moving averages lag less and influence the way they are calculated slightly. Type 1 being the normal calculation and type 2 being the secret sauce
Reverse MA Filter: This option allows you to use the moving average in reverse. For example, the strategy will go long when the price is above the moving average. However, if you use the reserve MA Filter, you will go short when the price is above the moving average. This method works best in sideways market where price usually retraces back to the moving average. So, in an anticipation of price reverting back to the moving average, it is a useful piece of option to use during sideway markets.
The backtester assumes the following;
- 1000$ capital
- 0.06% commission based on binance
- 1% risk meaning 100% equity on cross leverage
- Backtest results are starting from 2020
If you want to get access to this indicator please DM me or visit our website.
Quickie (Free) BacktesterQuickie is a free tradingview Indicator developed by HFT Research. It works in sideways and trending markets depending the way you set it as well as both on short time frame and long time frame. It comes with backtesting abilities on tradingview.
BITMEX:XBTUSD
Use Bollinger Bands
This piece of the settings will turn and off Bollinger band’s input in the decision making. BB Length will determine the Moving average you are using to take the standard deviation off of which is named as BB Multiplier. Default settings will use 20 moving average and take standard deviation of 2 to create lower and upper bands. Increasing the Multiplier will give you fewer but safer entries
Use RSI
You can also turn on and off the RSI as well. Alternatively, there is an option to use RSI on a different time frame than you are currently on. For example, if you are looking at the 5min chart to use Bollinger bands but you would like to look at the RSI value on the 15min chart. You can do so by selecting the custom RSI timeframe as well as adjusting the Oversold and Overbought value.
Use MA Filter
Lookback: The indicator has an option to look back x number of candles to validate the price crossing. If the market is choppy and the price keeps crossing up and down the moving average you have chosen, it will generate a lot of “noisy” signals. This option allows you to confirm the cross by selecting how many candles the price needs to stay above or below the moving average. Setting it 0 will turn it off.
MA Filter Type: There is a selection of moving averages that is available on TradingView currently. You can choose from 14 different moving average types to detect the trend as accurate as possible.
Filter Length: You can select the length of your moving average. Most commonly used length being 50,100 and 200.
Filter Type: This is our propriety smoothing method in order to make the moving averages lag less and influence the way they are calculated slightly. Type 1 being the normal calculation and type 2 being the secret sauce.
Reverse MA Filter: This option allows you to use the moving average in reverse. For example, the strategy will go long when the price is above the moving average. However, if you use the reserve MA Filter, you will go short when the price is above the moving average. This method works best in sideways market where price usually retraces back to the moving average. So, in an anticipation of price reverting back to the moving average, it is a useful piece of option to use during sideway markets.
For more information please check out our website
inwCoin Bullish/Bearish Divergence - Risk% StrategyEnglish
=========
inwCoin RSI Bullish/ Bearish Divergence Startegy.
RSI Bullish and Bearish divergence is a popular strategy that most people use to find the "reversal pattern" and bet on it.
...But is it really profitable in long run?
To find the answer, I write this strategy to test this hypothesis and the result is interesting.
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How it work?
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As you know, the main logic of bullish / bearish divergence are..
Buy Signal : RSI higher low in Oversold zone and price lower low
Sell Signal : RSI lower high in Overbought zone and price lower high
I also add some parameters to my strategy
1) Use stop loss + specific stop loss level
2) lookback period = RSI / Price lookback period to find divergence
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The result
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Not working at all.
It working ok in some period of time like in sideway market
But when uptrend established, it can't make any profit ( well, it's mean reversion strategy after all haha )
Also, when market keep crashing like in Nov 2018.
This strategy got stop out so many times before you can make 1 profitable trade....
But that trade won't last long because you have to take profit when you got bearish divergence signal.
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Conclusion
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Combine with trend following strategy.
This strategy might be able to fill the gap of sideway market.
But don't depend solely on this strategy because in long run, it can't beat the market.
GoombX backtest publicGoombX is an MA and stoch RSI based indicator which looks for particular crosses to identify strong trends.
It produces clear signals for:
- LONG ENTRY when it detects a significant MA cross and the right stoch RSI conditions
- LONG EXIT when certain stoch RSI conditions are met
- LONG STOP when price moves x% below entry (default 10%)
- SHORT ENTRY when it detects a significant MA cross and the right stoch RSI conditions
- SHORT EXIT when certain stoch RSI conditions are met
- SHORT STOP when price moves x% above entry (default 10%)
It is best fitted for 1D charts
NOTES
This is the Strategy version of GoombX for backtesting purpose only (stops in October 2019)
I strongly recommend backtesting with fees if you plan on using GoombX for automated trading
A signal is only definitive once the trigger candle has closed
To learn how to backtest, please look here:
backtest-rookies.com
and here:
backtest-rookies.com
EMA Mega Cross StrategyBased on Anvamsi's script which uses 12/26 EMA crosses for entry/exit signals. I also add the following features:
* Optimized default parameters for ETH 4hr chart
* Use EMA 55/200 relationship to filter out signals
* Use RSI vs EMA of RSI to filter out signals
* Use 26/55 EMA relationship to filter out signals
* Use volume climax technique as an additional exit strategy
* Uses bull/bear RSI divs as an additional exit strategy
* Adds bull RSI div quick flip plays when nothing else is going on for extra $$
This very experimental and my first major script. I've kept it invite only because the only people using this should have a direct line of communication open with me at this point.
NOTE #1:
You can get 2018 ETH trade profitability to reach 100% if you change line 97 from:
if (shortEMA and (rsi1 <= ema(rsi1,RSIEMALength)) and shorttrend and (ema(close,26) < ema(close,55)))
to:
if (shortEMA and (rsi1 <= ema(rsi1,RSIEMALength)) and shorttrend)
Basically, you remove an extra filter from the short strategy. It's novel to see profitability hit 100% but if you look at performance from 2017, it increases the max draw down by a lot!
NOTE #2:
I couldn't get RSI bear div quick flips to work so they are disabled. The remaining short strategy is in effect.
NOTE #3:
The profitability is good for long-only, if you check Strategy Tester->Performance Summary.
NOTE #4:
I am not an expert trader (mainly due to psychological factors i think) but i can program and have a good understanding of signal processing from working with analog synthesizers. Use this at your own risk. I am not liable if you lose all of your money!
NOTE #5:
Code is really messy. Old code commented out everywhere. :/
SB_CM_RSI_2_Strategy_Version 1.0The strategy is based on the indicator posted by @ChrisMoody "CM RSI-2 Strategy Lower Indicator" which is based on "Larry Connors RSI-2 Strategy - Lower RSI"
In this strategy the longs are placed when a green color is encountered in the rsi and short when red color is encountered in the rsi.
Although the profits can be booked at different interval.
Just message in the script if you have any different idea regarding this indicator.
For the original indicator you can refer to :
For Tips to continue :) :
BTC: 1BjswGcRR6c23pka7qh5t5k56j46cuyyy2
ETH: 0x64fed71c9d6c931639c7ba4671aeb6b05e6b3781
LTC: LKT2ykQ8QSzzfTDB6Tnsf12xwYPjgq95h4
Cowabunga System from babypips.comPlease do read the information below as well, especially if you are new to Forex.
The Cowabunga System is a type of Mechanical Trading System that filters trades based on the trend of the 4 hour chart with EMAs and some other familiar indicators (RSI, Stochastics and MACD) while entering trades base on 15 minute chart.
I have coded (quite amateurishly) the basic system onto a 15 minute chart (the 4 hour settings are coded as well). The author says the system is to be traded off the 15 minute chart with the 4 hour chart only as a reference for trend direction.
4 Hour Chart Settings
5 EMA
10 EMA
Stochastics (10,3,3)
RSI (9)
Then we move onto the 15 minute chart, where he gives us the trade entry rules.
15 Minute Chart Settings
5 EMA
10 EMA
Stochastics (10,3,3)
RSI (9)
MACD (12,26,9)
Entry Rules - long entry rules used, obviously reverse these for shorting.
1. EMA must cross above the 10 EMA.
2. RSI must be greater than 50 and not overbought.
3. Stochastic must be headed up and not be in overbought territory.
4. MACD histogram must go from negative to positive OR be negative and start to increase in value.
What I did.
1. Set the RSI and Stochastic levels to avoid entries when they indicate overbought conditions for long and oversold conditions for short (80 and 20 levels).
2. Users can input specific times they want to backtest.
3. User's can configure profit targets, trailing stops and stops. Default is set it to was 100 pips profit target with a 40 pip trailing stop. (Note, when you are changing these values, please note that each pip is worth 10, so 100 pips is entered as 1000.)
The Cowabunga System from babypips.com is another popular and active system. The author, Pip Surfer, continues to post wins and losses with this system. It shows there is a lot of honesty and integrity with this system if the author keeps up to date even 10 years later and is not afraid of sharing the times the system causes losses.
As an example of this, here is post he shared just last week . It's almost like a journal, he gives specific times and reasons why he entered, lets the readers know when he was stopped out, etc. I think that what he does is equally important as his system.
To read more about this system, visit the thread on babypips.com, click here.
DTR V 1.0DTR V 1.0 – RSI + Stochastic Entry Strategy
by DTR Traders
This is a momentum-based entry and exit strategy that combines the RSI and Stochastic indicators. It’s designed to identify oversold buy opportunities and close positions during overbought conditions — great for catching short-term reversals.
🧠 Strategy Logic:
✅ Entry (Buy Signal):
A long trade is opened when both:
Stochastic is below the oversold level
RSI is below its oversold level
This double-confirmation helps filter out false signals and looks for strong oversold momentum.
❌ Exit (Sell Signal):
The position is closed when both:
Stochastic rises above the overbought level
RSI rises above its overbought level
This ensures you're exiting after a decent bounce or rally.
📈 Chart Behavior:
This script can automatically enter and exit trades using Pine Script’s strategy() function.
It plots visual signals on the chart and you can also see trades and PnL in the Strategy Tester tab. (Some Time Frames are more profitable than others, adjust it to your trading strategy).
💡 Use Cases:
Ideal for traders who like to buy low and sell high using oversold/overbought conditions.
Works well in ranging markets where price frequently reverses from extremes.
Can be adapted to different timeframes.
🚀 Tips for Better Performance:
Consider adding filters like trend confirmation (e.g., MA direction).
Pair with SL/TP management or alerts for real-time decision-making.
Backtest across assets and timeframes to find optimal settings.
JonnyBtc Daily Pullback Strategy (Volume + ADX)📈 JonnyBtc Daily Optimized Pullback Strategy (With Volume + ADX)
This strategy is designed for Bitcoin swing trading on the daily timeframe and uses a combination of price action, moving averages, volume, RSI, and ADX strength filtering to time high-probability entries during strong trending conditions.
🔍 Strategy Logic:
Trend Filter: Requires price to be aligned with both 50 EMA and 200 EMA.
Pullback Entry: Looks for a pullback to a fast EMA (default 21) and a crossover signal back above it.
RSI Confirmation: RSI must be above a minimum threshold for long entries (default 55), or below for short entries.
Volume Filter: Entry is confirmed only when volume is above a 20-day average.
ADX Filter: Only enters trades when ADX is above a strength threshold (default 20), filtering out sideways markets.
Trailing Stop (optional): Uses ATR-based trailing stop-loss and take-profit system, fully configurable.
⚙️ Default Settings:
Timeframe: Daily
Trade Direction: Long-only by default (can be toggled)
Trailing Stop: Enabled (can disable)
Session Filter: Off by default for daily timeframe
📊 Best Use:
Optimized for Bitcoin (BTCUSD) on the 1D chart
Can be adapted to other trending assets with proper tuning
Works best in strong trending markets — not ideal for choppy/ranging conditions
🛠️ Customizable Parameters:
EMA lengths (Fast, Mid, Long)
RSI and ADX thresholds
ATR-based TP/SL multipliers
Trailing stop toggle
Volume confirmation toggle
Time/session filter
⚠️ Disclaimer:
This script is for educational and research purposes only. Past performance does not guarantee future results. Always backtest and verify before trading with real funds.
SpeedBullish Strategy Confirm V6.2SpeedBullish Strategy Confirm V6.2
SpeedBullish V6.2 is an advanced price-action + indicator-based strategy designed to confirm trend strength and signal entries with high precision. This version builds on the W/M pattern structure and adds dynamic filtering with EMA, MACD Histogram, RSI, ATR, and Volume.
✅ Signal Conditions
🔹 Buy Signal:
Price above EMA10 or EMA15
MACD Histogram crosses above 0
RSI > 50
(Optional) Higher low via Pivot Low
(Optional) ATR > ATR SMA * Multiplier
(Optional) Volume > SMA * Multiplier
🔻 Sell Signal:
Price below EMA10 or EMA15
MACD Histogram crosses below 0
RSI < 50
(Optional) Lower high via Pivot High
(Optional) Confirmed high volatility and volume
⚙️ Strategy Features
MACD Histogram for momentum shift detection
RSI filtering for momentum confirmation
EMA10/15 for trend direction
ATR-based volatility filter
Volume confirmation filter
Dynamic TP/SL + Trailing Stop
Webhook Integration for MT5 auto-trade
Visual signal markers + background highlight
🔔 Alerts
Alerts are sent in JSON format via alert() with the current symbol, action (buy/sell), and price. Webhook endpoint and secret key are configurable.
📈 How to Use
Attach the strategy to any symbol and timeframe
Customize filters and confirmations to fit your market conditions
Enable webhook alerts for integration with your MT5 Expert Advisor or trading bot
Backtest and optimize before live deployment
Dskyz (DAFE) GENESIS Dskyz (DAFE) GENESIS: Adaptive Quant, Real Regime Power
Let’s be honest: Most published strategies on TradingView look nearly identical—copy-paste “open-source quant,” generic “adaptive” buzzwords, the same shallow explanations. I’ve even fallen into this trap with my own previously posted strategies. Not this time.
What Makes This Unique
GENESIS is not a black-box mashup or a pre-built template. It’s the culmination of DAFE’s own adaptive, multi-factor, regime-aware quant engine—built to outperform, survive, and visualize live edge in anything from NQ/MNQ to stocks and crypto.
True multi-factor core: Volume/price imbalances, trend shifts, volatility compression/expansion, and RSI all interlock for signal creation.
Adaptive regime logic: Trades only in healthy, actionable conditions—no “one-size-fits-all” signals.
Momentum normalization: Uses rolling, percentile-based fast/slow EMA differentials, ALWAYS normalized, ALWAYS relevant—no “is it working?” ambiguity.
Position sizing that adapts: Not fixed-lot, not naive—not a loophole for revenge trading.
No hidden DCA or pyramiding—what you see is what you trade.
Dashboard and visual system: Directly connected to internal logic. If it’s shown, it’s used—and nothing cosmetic is presented on your chart that isn’t quantifiable.
📊 Inputs and What They Mean (Read Carefully)
Maximum Raw Score: How many distinct factors can contribute to regime/trade confidence (default 4). If you extend the quant logic, increase this.
RSI Length / Min RSI for Shorts / Max RSI for Longs: Fine-tunes how “overbought/oversold” matters; increase the length for smoother swings, tighten floors/ceilings for more extreme signals.
⚡ Regime & Momentum Gates
Min Normed Momentum/Score (Conf): Raise to demand only the strongest trends—your filter to avoid algorithmic chop.
🕒 Volatility & Session
ATR Lookback, ATR Low/High Percentile: These control your system’s awareness of when the market is dead or ultra-volatile. All sizing and filter logic adapts in real time.
Trading Session (hours): Easy filter for when entries are allowed; default is regular trading hours—no surprise overnight fills.
📊 Sizing & Risk
Max Dollar Risk / Base-Max Contracts: All sizing is adaptive, based on live regime and volatility state—never static or “just 1 contract.” Control your max exposures and real $ risk. ATR will effect losses in high volatility times.
🔄 Exits & Scaling
Stop/Trail/Scale multipliers: You choose how dynamic/flexible risk controls and profit-taking need to be. ATR-based, so everything auto-adjusts to the current market mode.
Visuals That Actually Matter
Dashboard (Top Right): Shows only live, relevant stats: scoring, status, position size, win %, win streak, total wins—all from actual trade engine state (not “simulated”).
Watermark (Bottom Right): Momentum bar visual is always-on, regime-aware, reflecting live regime confidence and momentum normalization. If the bar is empty, you’re truly in no-momentum. If it glows lime, you’re riding the strongest possible edge.
*No cosmetics, no hidden code distractions.
Backtest Settings
Initial capital: $10,000
Commission: Conservative, realistic roundtrip cost:
15–20 per contract (including slippage per side) I set this to $25
Slippage: 3 ticks per trade
Symbol: CME_MINI:NQ1!
Timeframe: 1 min (but works on all timeframes)
Order size: Adaptive, 1–3 contracts
No pyramiding, no hidden DCA
Why these settings?
These settings are intentionally strict and realistic, reflecting the true costs and risks of live trading. The 10,000 account size is accessible for most retail traders. 25/contract including 3 ticks of slippage are on the high side for NQ, ensuring the strategy is not curve-fit to perfect fills. If it works here, it will work in real conditions.
Why It Wins
While others put out “AI-powered” strategies with little logic or soul, GENESIS is ruthlessly practical. It is built around what keeps traders alive:
- Context-aware signals, not just patterns
- Tight, transparent risk
- Inputs that adapt, not confuse
- Visuals that clarify, not distract
- Code that runs clean, efficient, and with minimal overfitting risk (try it on QQQ, AMD, SOL, etc. out of the box)
Disclaimer (for TradingView compliance):
Trading is risky. Futures, stocks, and crypto can result in significant losses. Do not trade with funds you cannot afford to lose. This is for educational and informational purposes only. Use in simulation/backtest mode before live trading. No past performance is indicative of future results. Always understand your risk and ownership of your trades.
This will not be my last—my goal is to keep raising the bar until DAFE is a brand or I’m forced to take this private.
Use with discipline, use with clarity, and always trade smarter.
— Dskyz , powered by DAFE Trading Systems.
Vinicius Setup ATR
Description:
This script is a strategy based on the Supertrend indicator combined with volume analysis, candle strength, and RSI. Its goal is to identify potential entry points for buy and sell trades based on technical criteria, without promising profitability or guaranteed results.
Script Components:
Supertrend: Used as the main trend compass. When the trend is positive (direction = 1), buy signals are considered; when negative (direction = -1), sell signals are considered.
Volume: Entries are only validated if the volume is above the average of the last 20 candles, adjusted with a 1.2 multiplier.
Candle Body: The candle body must be larger than a certain percentage of the ATR, ensuring sufficient strength and volatility.
RSI: Used as a filter to avoid trades in extreme overbought or oversold zones.
Support and Resistance: Identified based on simple pivots (5 periods before and after).
Customizable Parameters:
ATR Length and Multiplier: Controls the sensitivity of the Supertrend.
RSI Period: Adjusts the relative strength filter.
Minimum Volume and Candle Body: Settings to validate entry signals.
Entry Conditions:
Buy: Positive trend + strong candle + high volume + RSI below 70.
Sell: Negative trend + strong candle + high volume + RSI above 30.
Exit Conditions:
The trade is closed upon the appearance of an opposite signal.
Notes:
This is a technical system with no profit guarantees.
It is recommended to test with realistic capital values and parameters suited to your risk management.
The script is not optimized for specific profitability, but rather to support study and the construction of setups with objective criteria.
Gabriel's Price Action Strategy🧠 Gabriel's Price Action Strategy — Smart Signal Sequence with Dynamic Risk Control
Created by: OneWallStreetQuant
Strategy Type: Momentum-based Sequence Logic + Smart Volume & RSI Filters
Ideal For: Intraday scalping, swing trading, and momentum trend entries on stocks, forex, crypto, indices.
🚀 Overview
Gabriel's Price Action Strategy is a multi-layered, logic-driven trading system that combines:
✅ Candle Sequence Detection: Detects persistent bullish/bearish momentum using a smart configurable sequence of green/red candles.
✅ Structure Break Filtering: Prevents entries if recent price invalidates the momentum setup (e.g., a red candle breaks a bullish low).
✅ Custom Volume Engine: Integrates a hybrid tick-volume model using Negative/Positive Volume Index (NVI-PVI) to identify smart money flows.
✅ Advanced RSI Logic: Uses Jurik RSX for accurate oversold/overbought filtering.
✅ Optional MTF Trend Filter: Validates trend direction using a slope-based Jurik MA on higher timeframes.
✅ MPT-Based DMI Filter: Adds pyramid entries only during strong trend phases, based on Gain/Pain ratios and Ulcer-index smoothed ADX.
✅ Risk Management: ATR-based SL/TP and fully customizable trailing logic for both profit and stop-loss.
📈 Entry Logic
Trades are triggered only when:
A minimum number of recent candles are bullish/bearish (Min Green/Red Candles)
Structure has not been broken by opposite price action (optional)
Relative volume exceeds average (optional)
RSI is below overbought or above oversold (optional)
MTF slope is aligned with trend direction (optional)
💡 Key Features
Custom Candle Logic: Detects momentum shifts using a tunable lookback window (up to 50 bars).
Smart Volume Filtering: Volume is intelligently estimated using tick-based ranges and NVI-PVI deltas.
Risk Management Built-in: Set your ATR length, SL/TP multipliers, and dynamic trailing offsets with full control.
Scorecard System: A built-in scoring engine evaluates Win Rate, Drawdown, Sharpe Ratio, Recovery Factor, and Profit Factor — visualized on chart as a label.
Backtest-Friendly: Includes date range toggles, bar-magnifier support, and optimized execution on every tick.
📊 Strategy Scorecard (Label)
Automatically calculates:
✅ Total Trades
✅ Win Rate (%)
✅ Net Profit
✅ Profit Factor
✅ Expected Payoff
✅ Max & Avg Drawdown
✅ Recovery Factor
✅ Sharpe Ratio
✅ VaR (95%)
Plus, assigns a normalized score from 0 to 100 for evaluating overall robustness.
⚙️ Customization
Every module — from entry filters to pyramiding and trailing logic — is fully configurable:
Volume Filters ✅
RSI Filters ✅
Structure Break Checks ✅
HTF Jurik MA & Slope Threshold ✅
Multi-Timeframe Mode ✅
Backtest Score Visualization ✅
⚠️ Notes
Enable bar magnifier and calc on every tick for best accuracy.
On early bars, signal logic may delay until enough candles are available.
Best paired with assets showing directional volatility (SPY, BTC, ETH, Gold, etc.).
Ideally paired on trending timeframes such as M1, M5, M15, M30, 1HR, 4 Hourly, Daily, Weekly, Monthly, etc.
Trailing Monster StrategyTrailing Monster Strategy
This is an experimental trend-following strategy that incorporates a custom adaptive moving average (PKAMA), RSI-based momentum filtering, and dynamic trailing stop-loss logic. It is designed for educational and research purposes only, and may require further optimization or risk management considerations prior to live deployment.
Strategy Logic
The strategy attempts to participate in sustained price trends by combining:
- A Power Kaufman Adaptive Moving Average (PKAMA) for dynamic trend detection,
- RSI and Simple Moving Average (SMA) filters for market condition confirmation,
- A delayed trailing stop-loss to manage exits once a trade is in profit.
Entry Conditions
Long Entry:
- RSI exceeds the overbought threshold (default: 70),
- Price is trading above the 200-period SMA,
- PKAMA slope is positive (indicating upward momentum),
- A minimum number of bars have passed since the last entry.
Short Entry:
- RSI falls below the oversold threshold (default: 30),
- Price is trading below the 200-period SMA,
- PKAMA slope is negative (indicating downward momentum),
-A minimum number of bars have passed since the last entry.
Exit Conditions
- A trailing stop-loss is applied once the position has been open for a user-defined number of bars.
- The trailing distance is calculated as a fixed percentage of the average entry price.
Technical Notes
This script implements a custom version of the Power Kaufman Adaptive Moving Average (PKAMA), conceptually inspired by alexgrover’s public implementation on TradingView .
Unlike traditional moving averages, PKAMA dynamically adjusts its responsiveness based on recent market volatility, allowing it to better capture trend changes in fast-moving assets like altcoins.
Disclaimer
This strategy is provided for educational purposes only.
It is not financial advice, and no guarantee of profitability is implied.
Always conduct thorough backtesting and forward testing before using any strategy in a live environment.
Adjust inputs based on your individual risk tolerance, asset class, and trading style.
Feedback is encouraged. You are welcome to fork and modify this script to suit your own preferences and market approach.
Adaptive Fibonacci Pullback System -FibonacciFluxAdaptive Fibonacci Pullback System (AFPS) - FibonacciFlux
This work is licensed under a Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0). Original concepts by FibonacciFlux.
Abstract
The Adaptive Fibonacci Pullback System (AFPS) presents a sophisticated, institutional-grade algorithmic strategy engineered for high-probability trend pullback entries. Developed by FibonacciFlux, AFPS uniquely integrates a proprietary Multi-Fibonacci Supertrend engine (0.618, 1.618, 2.618 ratios) for harmonic volatility assessment, an Adaptive Moving Average (AMA) Channel providing dynamic market context, and a synergistic Multi-Timeframe (MTF) filter suite (RSI, MACD, Volume). This strategy transcends simple indicator combinations through its strict, multi-stage confluence validation logic. Historical simulations suggest that specific MTF filter configurations can yield exceptional performance metrics, potentially achieving Profit Factors exceeding 2.6 , indicative of institutional-level potential, while maintaining controlled risk under realistic trading parameters (managed equity risk, commission, slippage).
4 hourly MTF filtering
1. Introduction: Elevating Pullback Trading with Adaptive Confluence
Traditional pullback strategies often struggle with noise, false signals, and adapting to changing market dynamics. AFPS addresses these challenges by introducing a novel framework grounded in Fibonacci principles and adaptive logic. Instead of relying on static levels or single confirmations, AFPS seeks high-probability pullback entries within established trends by validating signals through a rigorous confluence of:
Harmonic Volatility Context: Understanding the trend's stability and potential turning points using the unique Multi-Fibonacci Supertrend.
Adaptive Market Structure: Assessing the prevailing trend regime via the AMA Channel.
Multi-Dimensional Confirmation: Filtering signals with lower-timeframe Momentum (RSI), Trend Alignment (MACD), and Market Conviction (Volume) using the MTF suite.
The objective is to achieve superior signal quality and adaptability, moving beyond conventional pullback methodologies.
2. Core Methodology: Synergistic Integration
AFPS's effectiveness stems from the engineered synergy between its core components:
2.1. Multi-Fibonacci Supertrend Engine: Utilizes specific Fibonacci ratios (0.618, 1.618, 2.618) applied to ATR, creating a multi-layered volatility envelope potentially resonant with market harmonics. The averaged and EMA-smoothed result (`smoothed_supertrend`) provides a robust, dynamic trend baseline and context filter.
// Key Components: Multi-Fibonacci Supertrend & Smoothing
average_supertrend = (supertrend1 + supertrend2 + supertrend3) / 3
smoothed_supertrend = ta.ema(average_supertrend, st_smooth_length)
2.2. Adaptive Moving Average (AMA) Channel: Provides dynamic market context. The `ama_midline` serves as a key filter in the entry logic, confirming the broader trend bias relative to adaptive price action. Extended Fibonacci levels derived from the channel width offer potential dynamic S/R zones.
// Key Component: AMA Midline
ama_midline = (ama_high_band + ama_low_band) / 2
2.3. Multi-Timeframe (MTF) Filter Suite: An optional but powerful validation layer (RSI, MACD, Volume) assessed on a lower timeframe. Acts as a **validation cascade** – signals must pass all enabled filters simultaneously.
2.4. High-Confluence Entry Logic: The core innovation. A pullback entry requires a specific sequence and validation:
Price interaction with `average_supertrend` and recovery above/below `smoothed_supertrend`.
Price confirmation relative to the `ama_midline`.
Simultaneous validation by all enabled MTF filters.
// Simplified Long Entry Logic Example (incorporates key elements)
long_entry_condition = enable_long_positions and
(low < average_supertrend and close > smoothed_supertrend) and // Pullback & Recovery
(close > ama_midline and close > ama_midline) and // AMA Confirmation
(rsi_filter_long_ok and macd_filter_long_ok and volume_filter_ok) // MTF Validation
This strict, multi-stage confluence significantly elevates signal quality compared to simpler pullback approaches.
1hourly filtering
3. Realistic Implementation and Performance Potential
AFPS is designed for practical application, incorporating realistic defaults and highlighting performance potential with crucial context:
3.1. Realistic Default Strategy Settings:
The script includes responsible default parameters:
strategy('Adaptive Fibonacci Pullback System - FibonacciFlux', shorttitle = "AFPS", ...,
initial_capital = 10000, // Accessible capital
default_qty_type = strategy.percent_of_equity, // Equity-based risk
default_qty_value = 4, // Default 4% equity risk per initial trade
commission_type = strategy.commission.percent,
commission_value = 0.03, // Realistic commission
slippage = 2, // Realistic slippage
pyramiding = 2 // Limited pyramiding allowed
)
Note: The default 4% risk (`default_qty_value = 4`) requires careful user assessment and adjustment based on individual risk tolerance.
3.2. Historical Performance Insights & Institutional Potential:
Backtesting provides insights into historical behavior under specific conditions (always specify Asset/Timeframe/Dates when sharing results):
Default Performance Example: With defaults, historical tests might show characteristics like Overall PF ~1.38, Max DD ~1.16%, with potential Long/Short performance variance (e.g., Long PF 1.6+, Short PF < 1).
Optimized MTF Filter Performance: Crucially, historical simulations demonstrate that meticulous configuration of the MTF filters (particularly RSI and potentially others depending on market) can significantly enhance performance. Under specific, optimized MTF filter settings combined with appropriate risk management (e.g., 7.5% risk), historical tests have indicated the potential to achieve **Profit Factors exceeding 2.6**, alongside controlled drawdowns (e.g., ~1.32%). This level of performance, if consistently achievable (which requires ongoing adaptation), aligns with metrics often sought in institutional trading environments.
Disclaimer Reminder: These results are strictly historical simulations. Past performance does not guarantee future results. Achieving high performance requires careful parameter tuning, adaptation to changing markets, and robust risk management.
3.3. Emphasizing Risk Management:
Effective use of AFPS mandates active risk management. Utilize the built-in Stop Loss, Take Profit, and Trailing Stop features. The `pyramiding = 2` setting requires particularly diligent oversight. Do not rely solely on default settings.
4. Conclusion: Advancing Trend Pullback Strategies
The Adaptive Fibonacci Pullback System (AFPS) offers a sophisticated, theoretically grounded, and highly adaptable framework for identifying and executing high-probability trend pullback trades. Its unique blend of Fibonacci resonance, adaptive context, and multi-dimensional MTF filtering represents a significant advancement over conventional methods. While requiring thoughtful implementation and risk management, AFPS provides discerning traders with a powerful tool potentially capable of achieving institutional-level performance characteristics under optimized conditions.
Acknowledgments
Developed by FibonacciFlux. Inspired by principles of Fibonacci analysis, adaptive averaging, and multi-timeframe confirmation techniques explored within the trading community.
Disclaimer
Trading involves substantial risk. AFPS is an analytical tool, not a guarantee of profit. Past performance is not indicative of future results. Market conditions change. Users are solely responsible for their decisions and risk management. Thorough testing is essential. Deploy at your own considered risk.
Reversal & Breakout Strategy with ORB### Reversal & Breakout Strategy with ORB
This strategy combines three distinct trading approaches—reversals, trend breakouts, and opening range breakouts (ORB)—into a single, cohesive system. The goal is to capture high-probability setups across different market conditions, leveraging a mashup of technical indicators for confirmation and risk management. Below, I’ll explain why this combination works, how the components interact, and how to use it effectively.
#### Why the Mashup?
- **Reversals**: Identifies overextended moves using RSI (overbought/oversold) and SMA50 crosses, filtered by VWAP and SMA200 trend direction. This targets mean-reversion opportunities in trending markets.
- **Breakouts**: Uses EMA9/EMA20 crossovers with VWAP and SMA200 confirmation to catch momentum-driven trend continuations.
- **Opening Range Breakout (ORB)**: Detects early momentum by breaking the high/low of a user-defined opening range (default: 15 bars) with volume confirmation. This adds a time-based edge, ideal for intraday trading.
The synergy comes from blending these methods: reversals catch pullbacks, breakouts ride trends, and ORB exploits early volatility—all filtered by trend (SMA200) and anchored by VWAP for context.
#### How It Works
1. **Indicators**:
- **EMA9/EMA20**: Fast-moving averages for breakout signals.
- **SMA50**: Medium-term trend filter for reversals.
- **SMA200**: Long-term trend direction to align trades.
- **RSI (14)**: Measures overbought (>70) or oversold (<30) conditions.
- **VWAP**: Acts as a dynamic support/resistance level.
- **ATR (14)**: Sets stop-loss distance (default: 1.5x ATR).
- **Volume**: Confirms ORB breakouts (1.5x average volume of opening range).
2. **Entry Conditions**:
- **Long**: Triggers on reversal (SMA50 cross + RSI < 30 + below VWAP + uptrend), breakout (EMA9 > EMA20 + above VWAP + uptrend), or ORB (break above opening range high + volume).
- **Short**: Triggers on reversal (SMA50 cross + RSI > 70 + above VWAP + downtrend), breakout (EMA9 < EMA20 + below VWAP + downtrend), or ORB (break below opening range low + volume).
3. **Risk Management**:
- Risks 5% of equity per trade (based on the initial capital set in the strategy tester).
- Stop-loss: Based on lowest low/highest high over 7 bars ± 1.5x ATR.
- Targets: Two exits at 1:1 and 1:2 risk:reward (50% of position at each).
- Break-even: Stop moves to entry price after the first target is hit.
4. **Backtesting Settings**:
- Commission: Hardcoded at 0.1% per trade (realistic for most brokers).
- Slippage: Hardcoded at 2 ticks (realistic for most markets).
- Tested on datasets yielding 100+ trades (e.g., 2-min or 5-min charts over months).
#### How to Use It
- **Timeframe**: Works best on intraday (2-min, 5-min) or daily charts. Adjust `Opening Range Bars` (e.g., 15 bars = 30 min on 2-min chart) for your timeframe.
- **Settings**:
- Set your initial equity in the TradingView strategy tester’s "Properties" tab under "Initial Capital" (e.g., $10,000). The script automatically risks 5% of this equity per trade.
- Adjust `Stop Loss ATR Multiplier` or `Risk:Reward Targets` based on your risk tolerance.
- Note that commission (0.1%) and slippage (2 ticks) are fixed in the script for backtesting consistency.
- **Execution**: Enter on signal, monitor plotted stop (red) and targets (green/blue). The strategy supports pyramiding (up to 2 positions) for scaling into trends.
#### Backtesting Notes
Results are realistic with commission (0.1%) and slippage (2 ticks) included. For a sufficient sample, test on volatile instruments (e.g., stocks, forex) over 3-6 months on lower timeframes. The default 1.5x ATR stop may seem wide, but it’s justified to avoid premature exits in volatile markets—feel free to tweak it with justification. The script assumes an initial capital of $10,000 in the strategy tester for the 5% risk calculation (e.g., $500 risk per trade); adjust this in the "Properties" tab as needed.
This mashup isn’t just a random mix; it’s a deliberate fusion of complementary strategies, offering traders flexibility across market phases. Questions? Let me know!
Ultimate Trading BotHow the "Ultimate Trading Bot" Works:
This Pine Script trading bot executes buy and sell trades based on a combination of technical indicators:
Indicators Used:
RSI (Relative Strength Index)
Measures momentum and determines overbought (70) and oversold (30) levels.
A crossover above 30 suggests a potential buy, and a cross below 70 suggests a potential sell.
Moving Average (MA)
A simple moving average (SMA) of 50 periods to track the trend.
Prices above the MA indicate an uptrend, while prices below indicate a downtrend.
Stochastic Oscillator (%K and %D)
Identifies overbought and oversold conditions using a smoothed stochastic formula.
A crossover of %K above %D signals a buy, and a crossover below %D signals a sell.
MACD (Moving Average Convergence Divergence)
Uses a 12-period fast EMA and a 26-period slow EMA, with a 9-period signal line.
A crossover of MACD above the signal line suggests a bullish move, and a cross below suggests bearish movement.
Trade Execution:
Buy (Long Entry) Conditions:
RSI crosses above 30 (indicating recovery from an oversold state).
The closing price is above the 50-period moving average (showing an uptrend).
The MACD line crosses above the signal line (indicating upward momentum).
The Stochastic %K crosses above %D (indicating bullish momentum).
→ If all conditions are met, the bot enters a long (buy) position.
Sell (Exit Trade) Conditions:
RSI crosses below 70 (indicating overbought conditions).
The closing price is below the 50-period moving average (downtrend).
The MACD line crosses below the signal line (bearish signal).
The Stochastic %K crosses below %D (bearish momentum).
→ If all conditions are met, the bot closes the long position.
Visuals:
The bot plots the moving average, RSI, MACD, and Stochastic indicators for reference.
It also displays buy/sell signals with arrows:
Green arrow (Buy Signal) → When all buy conditions are met.
Red arrow (Sell Signal) → When all sell conditions are met.
How to Use It in TradingView:
Volatility Momentum Breakout StrategyDescription:
Overview:
The Volatility Momentum Breakout Strategy is designed to capture significant price moves by combining a volatility breakout approach with trend and momentum filters. This strategy dynamically calculates breakout levels based on market volatility and uses these levels along with trend and momentum conditions to identify trade opportunities.
How It Works:
1. Volatility Breakout:
• Methodology:
The strategy computes the highest high and lowest low over a defined lookback period (excluding the current bar to avoid look-ahead bias). A multiple of the Average True Range (ATR) is then added to (or subtracted from) these levels to form dynamic breakout thresholds.
• Purpose:
This method helps capture significant price movements (breakouts) while ensuring that only past data is used, thereby maintaining realistic signal generation.
2. Trend Filtering:
• Methodology:
A short-term Exponential Moving Average (EMA) is applied to determine the prevailing trend.
• Purpose:
Long trades are considered only when the current price is above the EMA, indicating an uptrend, while short trades are taken only when the price is below the EMA, indicating a downtrend.
3. Momentum Confirmation:
• Methodology:
The Relative Strength Index (RSI) is used to gauge market momentum.
• Purpose:
For long entries, the RSI must be above a mid-level (e.g., above 50) to confirm upward momentum, and for short entries, it must be below a similar threshold. This helps filter out signals during overextended conditions.
Entry Conditions:
• Long Entry:
A long position is triggered when the current closing price exceeds the calculated long breakout level, the price is above the short-term EMA, and the RSI confirms momentum (e.g., above 50).
• Short Entry:
A short position is triggered when the closing price falls below the calculated short breakout level, the price is below the EMA, and the RSI confirms momentum (e.g., below 50).
Risk Management:
• Position Sizing:
Trades are sized to risk a fixed percentage of account equity (set here to 5% per trade in the code, with each trade’s stop loss defined so that risk is limited to approximately 2% of the entry price).
• Stop Loss & Take Profit:
A stop loss is placed a fixed ATR multiple away from the entry price, and a take profit target is set to achieve a 1:2 risk-reward ratio.
• Realistic Backtesting:
The strategy is backtested using an initial capital of $10,000, with a commission of 0.1% per trade and slippage of 1 tick per bar—parameters chosen to reflect conditions faced by the average trader.
Important Disclaimers:
• No Look-Ahead Bias:
All breakout levels are calculated using only past data (excluding the current bar) to ensure that the strategy does not “peek” into future data.
• Educational Purpose:
This strategy is experimental and provided solely for educational purposes. Past performance is not indicative of future results.
• User Responsibility:
Traders should thoroughly backtest and paper trade the strategy under various market conditions and adjust parameters to fit their own risk tolerance and trading style before live deployment.
Conclusion:
By integrating volatility-based breakout signals with trend and momentum filters, the Volatility Momentum Breakout Strategy offers a unique method to capture significant price moves in a disciplined manner. This publication provides a transparent explanation of the strategy’s components and realistic backtesting parameters, making it a useful tool for educational purposes and further customization by the TradingView community.
Tutorial - Adding sessions to strategiesA simple script to illustrate how to add sessions to trading strategies.
In this interactive tutorial, you'll learn how to add trading sessions to your strategies using Pine Script. By the end of this session (pun intended!), you'll be able to create custom trading windows that adapt to changing market conditions.
What You'll Learn:
Defining Trading Sessions: Understand how to set up specific time frames for buying and selling, tailored to your unique trading style.
RSI-Based Entry Signals: Discover how to use the Relative Strength Index (RSI) as a trigger for buy and sell signals, helping you capitalize on market trends.
Combining Session Logic with Trading Decisions: Learn how to integrate session-based logic into your strategy, ensuring that trades are executed only during designated times.
By combining these elements, we create an interactive strategy that:
1. Generates buy and sell signals based on RSI levels.
2. Checks if the market is open during a specific trading session (e.g., 1300-1700).
3. Executes trades only when both conditions are met.
**Tips & Variations:**
* Experiment with different RSI periods, thresholds, and sessions to optimize your strategy for various markets and time frames.
* Consider adding more advanced logic, such as stop-losses or position sizing, to further refine your trading approach.
Get ready to take your Pine Script skills to the next level!
~Description partially generated with Llama3_8B
Enhanced Gold Scalping Strategy (Backtest with Time Filter)Enhanced Gold Scalping Strategy (Backtest with Time Filter)
This script is a scalping strategy designed specifically for trading gold on lower timeframes, incorporating popular technical indicators and a session filter for optimal performance. The strategy aims to achieve consistency by combining trend-following and volatility-based conditions.
Key Features:
Indicators Used:
Exponential Moving Average (EMA): Filters trades based on the trend direction using a 50-period EMA.
Relative Strength Index (RSI): Ensures trades are taken in favorable momentum conditions (above 30 for longs and below 70 for shorts).
MACD Crossover: Identifies potential trade entries based on MACD line crossing above/below the signal line.
Average True Range (ATR): Used to dynamically calculate Stop Loss and Take Profit levels and ensure trades occur in high-volatility conditions.
Risk-Reward Optimization:
The strategy uses a customizable Risk-Reward Ratio (default is 2:1) for setting Stop Loss (SL) and Take Profit (TP) levels, ensuring that winning trades outweigh losses.
Volatility Filter:
Trades are only executed when the current ATR exceeds the 14-period ATR moving average by a defined threshold, filtering out low-volatility periods.
Session Filter:
The strategy only trades during active market hours (8:00 AM to 8:00 PM Amsterdam Time) on weekdays. This ensures trades align with periods of high liquidity and market activity.
Dynamic Entry and Exit Levels:
SL and TP levels are plotted dynamically on the chart to provide a clear visual of potential risk and reward for each trade.
Buy and Sell Signals:
Visual markers (green triangles for buy, red triangles for sell) on the chart to highlight entry points for better trade visibility.
How It Works:
Long Conditions:
MACD crossover (MACD line above the signal line).
RSI above 30.
Price is above the 50-period EMA.
ATR-based volatility condition is met.
Trade must occur within the defined session hours.
Short Conditions:
MACD crossunder (MACD line below the signal line).
RSI below 70.
Price is below the 50-period EMA.
ATR-based volatility condition is met.
Trade must occur within the defined session hours.
The strategy calculates dynamic SL and TP levels based on the ATR, ensuring flexibility to market conditions.
Customization Options:
EMA length, RSI length, and MACD parameters.
Risk-Reward Ratio for SL/TP calculations.
Volatility threshold for filtering trades.
Session start and end times for active trading hours.
Recommended Use:
Best suited for scalping gold on lower timeframes (15-min charts).
Disclaimer:
This strategy is intended for educational and backtesting purposes. Past performance is not indicative of future results. Use appropriate risk management and test thoroughly before applying to live trading.
Stronger V4.0 - Optimized Trading Strategy
Name: Stronger V4.0 - Optimized Trading Strategy
Introduction:
Stronger V4.0 is a structured trading strategy designed to identify and act on market breakout and reversal opportunities. By employing advanced filtering tools such as RSI (Relative Strength Index), MACD (Moving Average Convergence Divergence), and Bollinger Bands, this strategy aims to reduce market noise and provide reliable trading signals.
The strategy dynamically adapts to changing market conditions, focusing on delivering high-quality signals rather than frequent ones. This allows traders to approach markets with more confidence and clarity.
How the Strategy Works and Key Features:
How Stronger V4.0 Works:
Stronger V4.0 combines advanced technical indicators and custom logic to identify optimal entry and exit points in the market. By dynamically integrating filters like RSI, MACD, and Bollinger Bands, the strategy adjusts to market conditions and minimizes noise to deliver high-quality signals.
Key Features:
Dynamic Price Analysis:
Tracks price movements within specific periods to detect breakout and reversal opportunities.
Advanced Filtering Mechanisms:
RSI Filter: Avoids trades in overbought/oversold market conditions.
MACD Filter: Confirms market momentum and trend direction.
Bollinger Bands: Adapts thresholds based on market volatility.
Risk Management:
Limits trade risk to sustainable levels to preserve equity.
Encourages consistent growth by maintaining a maximum risk per trade.
Customizable Parameters:
Users can toggle long or short trades and adjust filter settings to match their trading preferences.
Minimalist Display:
Focuses on essential signals only, ensuring a clean and easy-to-read chart layout.
Market Breakout Identification:
One of Stronger V4.0's core functionalities is identifying significant breakout points. These breakout points are calculated based on dynamic price movements and market momentum.
Key moments are highlighted when the price exits a consolidation phase and transitions into a new trend. These points represent strong market opportunities, offering actionable insights for traders.
Using adjustable period settings, the strategy enables traders to tailor the analysis to their preferred timeframe and trading style. By eliminating market noise, Stronger V4.0 helps traders focus on high-probability setups and make informed decisions during volatile conditions.
Why Stronger V4.0 Stands Out:
Adaptive Filters:
Dynamically integrates RSI, MACD, and Bollinger Bands to reduce noise and highlight high-probability setups.
Precision Execution:
Focuses on executing trades at optimal moments, ensuring a balance between sustainability and profitability.
Rigorous Testing:
Extensively backtested under realistic market conditions for consistent performance.
Tailored and Exclusive:
Designed for traders seeking a balance between quality and adaptability.
Risk Disclaimer:
Stronger V4.0 has been backtested under various market conditions; however, past performance does not guarantee future results. The strategy is provided as-is, and traders are encouraged to test it thoroughly and apply appropriate risk management measures. Always trade responsibly.
Precision Trading Strategy: Golden EdgeThe PTS: Golden Edge strategy is designed for scalping Gold (XAU/USD) on lower timeframes, such as the 1-minute chart. It captures high-probability trade setups by aligning with strong trends and momentum, while filtering out low-quality trades during consolidation or low-volatility periods.
The strategy uses a combination of technical indicators to identify optimal entry points:
1. Exponential Moving Averages (EMAs): A fast EMA (3-period) and a slow EMA (33-period) are used to detect short-term trend reversals via crossover signals.
2. Hull Moving Average (HMA): A 66-period HMA acts as a higher-timeframe trend filter to ensure trades align with the overall market direction.
3. Relative Strength Index (RSI): A 12-period RSI identifies momentum. The strategy requires RSI > 55 for long trades and RSI < 45 for short trades, ensuring entries are backed by strong buying or selling pressure.
4. Average True Range (ATR): A 14-period ATR ensures trades occur only during volatile conditions, avoiding choppy or low-movement markets.
By combining these tools, the PTS: Golden Edge strategy creates a precise framework for scalping and offers a systematic approach to capitalize on Gold’s price movements efficiently.
