Real-Fast Fourier Transform of Price w/ Linear Regression [Loxx]Real-Fast Fourier Transform of Price w/ Linear Regression is a indicator that implements a Real-Fast Fourier Transform on Price and modifies the output by a measure of Linear Regression. The solid line is the Linear Regression Trend of the windowed data, The green/red line is the Real FFT of price.
What is the Discrete Fourier Transform?
In mathematics, the discrete Fourier transform (DFT) converts a finite sequence of equally-spaced samples of a function into a same-length sequence of equally-spaced samples of the discrete-time Fourier transform (DTFT), which is a complex-valued function of frequency. The interval at which the DTFT is sampled is the reciprocal of the duration of the input sequence. An inverse DFT is a Fourier series, using the DTFT samples as coefficients of complex sinusoids at the corresponding DTFT frequencies. It has the same sample-values as the original input sequence. The DFT is therefore said to be a frequency domain representation of the original input sequence. If the original sequence spans all the non-zero values of a function, its DTFT is continuous (and periodic), and the DFT provides discrete samples of one cycle. If the original sequence is one cycle of a periodic function, the DFT provides all the non-zero values of one DTFT cycle.
What is the Complex Fast Fourier Transform?
The complex Fast Fourier Transform algorithm transforms N real or complex numbers into another N complex numbers. The complex FFT transforms a real or complex signal x in the time domain into a complex two-sided spectrum X in the frequency domain. You must remember that zero frequency corresponds to n = 0, positive frequencies 0 < f < f_c correspond to values 1 ≤ n ≤ N/2 −1, while negative frequencies −fc < f < 0 correspond to N/2 +1 ≤ n ≤ N −1. The value n = N/2 corresponds to both f = f_c and f = −f_c. f_c is the critical or Nyquist frequency with f_c = 1/(2*T) or half the sampling frequency. The first harmonic X corresponds to the frequency 1/(N*T).
The complex FFT requires the list of values (resolution, or N) to be a power 2. If the input size if not a power of 2, then the input data will be padded with zeros to fit the size of the closest power of 2 upward.
What is Real-Fast Fourier Transform?
Has conditions similar to the complex Fast Fourier Transform value, except that the input data must be purely real. If the time series data has the basic type complex64, only the real parts of the complex numbers are used for the calculation. The imaginary parts are silently discarded.
Inputs:
src = source price
uselreg = whether you wish to modify output with linear regression calculation
Windowin = windowing period, restricted to powers of 2: "4", "8", "16", "32", "64", "128", "256", "512", "1024", "2048"
Treshold = to modified power output to fine tune signal
dtrendper = adjust regression calculation
barsback = move window backward from bar 0
mutebars = mute bar coloring for the range
Further reading:
Real-valued Fast Fourier Transform Algorithms IEEE Transactions on Acoustics, Speech, and Signal Processing, June 1987
Related indicators utilizing Fourier Transform
Fourier Extrapolator of Variety RSI w/ Bollinger Bands
Fourier Extrapolation of Variety Moving Averages
Fourier Extrapolator of Price w/ Projection Forecast
Trend
Ultimate IndicatorThis is a combination of all the price chart indicators I frequently switch between. It contains my day time highlighter (for day trading), multi-timeframe long-term trend indicator for current commodity in the bottom right, customizable trend EMA which also has multi-timeframe drawing capabilities, VWAP, customizable indicators with separate settings from the trend indicator including: EMA, HL2 over time, Donchian Channels, Keltner Channels, Bollinger Bands, and Super Trend. The settings for these are right below the trend settings and can have their length and multiplier adjusted. All of those also have multi-timeframe capabilities separate from the trend multi-time settings.
The Day Trade Highlight option will draw faint yellow between 9:15-9:25, red between 9:25-9:45, yellow between 9:45-10:05. There will be one white background at 9:30am to show the opening of the market. while the market is open there will be a very faint blue background. For the end of the day there will be yellow between 15:45-15:50, red between 15:50-16:00, and yellow between 16:00-16:05. During the night hours, there is no coloring. The purpose of this highlight is to show the opening / closing times of the market and the hot times for large moves.
The indicators can also be colored in the following ways:
1. Simple = Makes all colors for the indicator Gray
2. Trend = Will use the Donchian Channels to get the short-trend direction and by default will color the short-term direction as Blue or Red. Unless using Super Trend, the Donchian Channel is used to find short-term trend direction.
3. Trend Adv = Will use the Donchian Channels to get the short-trend direction and by default will color the short-term direction as Blue or Red. Unless using Super Trend, the Donchian Channel is used to find short-term trend direction. If there is a short-term up-trend during a long-term down-trend, the Blue will become Navy. If short-term down-trend during long-term up-trend, the Red will be Brown.
4. Squeeze = Compares the Bollinger Bands width to the Keltner Channels width and will color based on relative squeeze of the market: Teal = no squeeze. Yellow = little squeeze. Red = decent squeeze. White = huge squeeze. if you do not understand this one, try drawing the Bollinger Bands while using the Squeeze color option and it should become more apparent how this works. I also recommend leaving the length and multiplier to the default 20 and 2 if using this setting and only changing the timeframe to get longer/shorter lengths as I've seen that changing the length or multiplier can more or less make it not work at all.
Along with the indicator settings are options to draw lines/labels/fills for the indicator. I enjoy having only fills for a cleaner look.
The Labels option will show Buy/Sell signals when the short-term trend flips to agree with the long-term trend.
The Trend Bars option will do the same as the Labels option but instead will color the bars white when a Buy/Sell option is given.
The Range Bars option shows will color a bar white when the Close of a candle is outside of a respective ranging indicator option (Bollinger or Keltner).
The Trend Bars will draw white candles no matter which indicator selection you make (even "Off"). However, Range Bars will only draw white when either Bollinger or Keltner are selected.
The Donchian Channels and Super Trend are trending indicators and should be used during trending markets. I like to use the MACD in conjunction with these indicators for possibly earlier entries.
The Bollinger Bands and Keltner Channel are ranging indicators and should be used during ranging markets. I like to use the RSI in conjunction with these indicators and will use 60/40 for overbought and oversold areas rather than 70/30. During a range, I wait for an overbought or oversold indication and will buy/sell when it crosses back into the middle area and close my position when it touches the opposite band.
I have a MACD/RSI combination indicator if you'd like that as well :D
As always, trade at your own risk. This is not some secret indicator that will 100% win. As always, the trades you see in the picture use a 1:1.5 or 1:2 risk to reward ratio, for today (August 8, 2022) it won 5/6 times with one trade still open at the end of the day. Manage your account correctly and you'll win in the long term. Hit me up with any questions or suggestions. Happy Trading!
Master/Last CandleMaster/Followers: Master candle is defined as the start of a trend (bullish/bearish) and followed by a series of candles in the same direction (bullish/bearish) called followers.
Last/Reversals: Last candle is defined as the end of a trend (bullish/bearish) and followed by a series of candles in the opposite direction (bearish/bullish) called reversals.
This indicator marks master/last candle, whether it is master or last depending on the breakout direction of the next candle. Next, we have to look for support (medium/low) and resistance (medium/high) to determine the target, which is not covered here. Remember that, target must cover sell-buy spread or commission offered by broker. When the two points are taken into considered, it is that time to decide making a trade (buy/sell) or not.
Detailed prices at entry and stop loss are included in alerts.
Markets: All.
Timeframes: All.
Usage: Used in combination with support/resistance.
Swing Trend StrategyThis script is a trend following system which uses a long term Moving Average to spot the trend in combination with the Average True Range to filter out Fakeouts, limiting the overall drawdown.
Default Settings and Calculation:
- The trend is detected using the Exponential Moving Average on 200 periods.
- The Average True Range is calculated on 10 periods.
- The Market is considered in an Uptrend when the price closes above the EMA + ATR.
- The Market is considered in a Downtrend when the price closes below the EMA - ATR.
- The strategy will open a LONG position when the market is in an Uptrend.
- The strategy will close its LONG positions when the price closes below the EMA.
- The strategy will open a SHORT position when the market is in a Downtrend.
- The strategy will close its SHORT positions when the price closes above the EMA.
This script is best suited for the 4h timeframe, and shows good results on BTC and ETH especially.
The options allow to modify the type of moving average to use, the period of the moving average, the ATR multiplier to add as well as the possibility to open short trades or not.
Gators Oscillator - Bitcoin Scalp Trader(T&M/e V3!!)Gator's Oscillator:
**For reference, all numbers, and settings displayed on the input screen are only what I HAVE FOUND to be profitable for my own strategy, Yours will differ. This is not financial advice and I am not a financial advisor. Please do your due diligence and own research before considering taking entries based on this strategy and indicator. I am not advertising investing, trading, or skills untaught, this is simply to help incorporate into your own strategy and improve your trading journey!**
INPUTS:
EV: This is an integer value set to default at 55. This value is equated to the lead value, volatility measurement, and standard deviation between averages
EV 2: This integer is used as the base value and is meant to always be GREATER THEN EV, the default is set at 163. There should be at least a 90+ integer difference between EVs for data accuracy.
EV TYPE & EV TYPE 2: This option only affects the output for the moving average histograms. (and data inserted for strategy)
Volatility Smoothing: This is the smoothness of the custom-made volatility oscillator. I have this default at 1 to show time-worthy-term (3.9%+) moves or significant trends to correspond with the standard deviation declination between EVMA and EVMA2.
Directional Length: This is the amount of data observed per candle in the bull versus bear indicator.
Take Profit: Pre-set takes profit level that is set to 4 but can be adjusted for user experience.
Style:
Base Length: Columns equated using a custom-made statistical equation derived from EV TYPE 2+EV2 to determine a range of differential in historic averages to a micro-scale.
Lead Length: Columns equated using a custom-made statistical equation derived from EV TYPE+EV to determine a range of differential in historic averages to a micro-scale.
Weighted EMA Differential: Equation expressing the differences between exponential and simple averages derived from EV+EV Type 2. Default is displaying none, but optional for use if found helpful.
Volatility: Represents volatility from multiple data sets spanning from Bollinger bands to HPV and translated through smoothing.
Bull Strength: The strength of Bulls in the current trend is derived from a DMI+RSI+MACD equation to represent where the trend lies.
Bear Strength: The strength of Bears in the current trend is derived from a DMI+RSI+MACD equation to represent where the trend lies.
(NEW) Standard Deviation between Moving Averages: Use this logarithmic indicator depicted as circles to help determine whether a move is a fake out or not. Compare the circles with the volatility line, if you see them deviating away, it is either a bull/bear trap or trend continuation is imminent until they correlate back together.
CHEAT CODE'S NOTES:
Do not use this indicator on high leverage. I have personally used this indicator for a week and faced a max of 8% drawdown, albeit painful I was on low leverage and still closed on my take profit level.
85% is not 100% do not overtrade using this indicator's entry conditions if you have made 4 consecutive profitable trades.
Mess around with the input values and let me know if you find an even BETTER hit rate, 30+ entries, and a good drawdown!!
V2 UPGRADES:
*Increased Opacity on Bull Bear Columns
*Removed the Stop Loss Input option
*Decreased EV2 to a default of 143 for accuracy
*Added additional disclaimers in the description
* Removed Bull/Bear offset values for accuracy
V3 UPGRADES:
*ADDED THE EMA DIFFERENTIAL FROM SMA STANDARD DEVIATION INDICATOR. REPRESENTED BY PURPLE BARS THAT PLOT BRIGHT AT EXTREME LEVELS (Translate this to the EMA's and SMA's are very far apart) This is a fantastic way to resolve volatility and momentum in one indicator!!
*Line Width increased for volatility
*plot's for Oversold Alma reduced to 3, also adjusted the plot shape to arrows corresponding to 'overbought/oversold values. Look for a cross-over from green/red plot to transparent for best signals.
*Histograms for bull/bear strength correspond to an increase or decrease in value
*Input screen converted into groups, with bull/bear color inline
*Converted base/lead length value's into areas with breaks. IF YOU SEE WHITE (Short/Lead Length), IT IS A SHORT TERM MOVE AND SCALPING OPPORTUNITY. IF YOU SEE BLUE(Long/Base Length) IT MEANS IT IS A MACRO MOVE, WHICH MAY LAST LONGER
-Cheat Code
BINANCE:BTCUSDT BYBIT:BTCUSDT COINBASE:BTCUSD
Strategy - Trend Chaser - PSeTrend Chaser for Philippine Stock Exchange - LONG ONLY
-Elvin Kennedy Latayan 2022
3LS | 3 Line Strike Strategy [Kintsugi Trading]What is the 3LS | 3 Line Strike Strategy?
Incorporating the 3 Line Strike candlestick pattern into our strategy was inspired by Arty at The Moving Average and the amazing traders at TheTrdFloor .
The Three Line Strike is a trend continuation candlestick pattern consisting of four candles. Depending on their heights and collocation, a bullish or a bearish trend continuation can be predicted.
In a symphony of trend analysis, price action, and volume we can find and place high-probability trades with the 3LS Strategy.
How to use it!
----- First, start by choosing a Stop-Loss Strategy, Stop PIP Size, and Risk/Reward Ratio -----
- Stop-Loss Strategy
Fixed PIP Size – This uses the top/bottom of the indicator candle and places a TP based on the chosen Risk:Reward ratio.
ATR Trail (No set Target Profit, only uses ATR Stop)
ATR Trail-Stop (Has set Target Profit, however, stop is based on ATR inputs)
**If you choose an ATR Stop-Loss Strategy - input the desired ATR period and Multiple you would like the stop to be calculated at**
**ATR Stop-Loss Strategies have a unique alert setup for Auto-Trading. See Auto-Trading Section**
- Risk/Reward Ratio = If you have a .5 risk/reward, it means you are risking $100 to make $50.
- Additional Stop PIP Size = Number of PIPs over the default stop location of the top or bottom of the indicator candle.
----- Next, we set the Session Filter -----
Set the Timezone and Trade Session you desire. If no specific session is desired, simply set the Trade Session to 00:00 - 00:00.
----- Next, we set the Moving Average Cloud Fill -----
Enter the Fast and Slow Moving Average Length used to calculate trend direction:
MA Period Fast
MA Period Slow
These inputs will determine whether the strategy looks for Long or Short positions.
----- Next, we set the VSA – Volume Spread Analysis Settings -----
Check the box to show the indicator at the bottom of the chart if desired.
This is just a different visual output of the VSA | Volume Spread Analysis indicator available for free under the community indicators tab. You can add that indicator to your chart and see the same output in candle format.
In combination with the Moving Average Cloud, the Volume Spread Analysis will help us determine when to take a trade and in what direction.
The strategy is essentially looking for small reversals going against the overall trend and placing a trade once that reversal ends and the price moves back in the direction of the overall trend.
The 3LS Strategy utilizes confirmation between trend, volume, and price action to place high probability trades.
The VSA is completely customizable by:
Moving Average Length
MA-1 Multiplier
MA-2 Multiplier
MA-3 Multiplier
Check out the VSA | Volume Spread Analysis indicator in the community scripts section under the indicators tab to use this awesome resource on other strategies.
----- Next, we have the option to view the automated KT Bull/Bear Signals -----
Check the boxes to show the buy-sell signal on the chart if desired.
----- Next, we set the risk we want to use if Auto Trading the strategy -----
I always suggest using no more than 1-3% of your total account balance per trade. Remember, if you have multiple strategies triggering per day with each using 1%, the total percent at risk will be much larger.
For Example – if you have 10 strategies each risking 1% your total risk is 10% of your account, not 1%! Be mindful to only use 1-3% of your total account balance across all strategies, not just each individual one.
----- Finally, we backtest our ideas -----
After using the 'Strategy Tester' tab on TradingView to thoroughly backtest your predictions you are ready to take it to the next level - Automated Trading!
This was my whole reason for creating the script. If you work a full-time job, live in a time zone that is hard to trade, or just don't have the patience, this will be a game-changer for you as it was for me.
Auto-Trading
When it comes to auto-trading this strategy I have included two options in the script that utilize the alert messages generated by TradingView.
*Note: Please trade on a demo account until you feel comfortable enough to use real money, and then please stick to 1%-2% of your total account value in risk per trade.*
AutoView
PineConnector
**ATR Auto-Trading Alert Setup**
How to create alerts on 3 Line Strike Strategy
For Trailing Stops:
1) Adjust autoview/pineconnector settings
2) Click "add alert"
3) Select "Condition" = Strategy Name
4) Select "Order Fills Only" from the drop-down
3) Remove template message text from "message" box and place the exact text. '{{strategy.order.alert_message}}'
4) Click "create"
For Fixed Pip Stop:
1) Adjust autoview/pineconnector settings
2) Click "add alert"
3) Select "Condition" = Strategy Name
4) Select "alert() function calls only"
5) I like to title my Alert Name the same thing I named it as an Indicator Template to keep track
Good luck with your trading!
Refracted EMARefracted EMA is a price based indicator with bands that is built on moving average.
The price range between the bands directly depends on relationship of Average True Range to Moving Average. This gives us very valuable variable constant that changes with the market moves.
So the bands expand and contract due to changes in volatility of the market, which makes this tool very flexible exposing psychological levels.
TF Segmented Polynomial Regression [LuxAlgo]This indicator displays polynomial regression channels fitted using data within a user selected time interval.
The model is fitted using the same method described in our previous script:
Settings
Degree: Degree of the fitted polynomial
Width: Multiplicative factor of the model RMSE. Controls the width of the polynomial regression's channels
Timeframe: Fits the polynomial regression using data within the selected timeframe interval
Show fit for new bars: If selected, will fit the regression model for newly generated bars, else the previous fitted value is displayed.
Src: Input source
Usage
Segmented (or piecewise) models yield multiple fits by first partitioning the data into multiple intervals from specific partitioning conditions. In this script this partitioning condition is for a user selected timeframe to change.
Segmented models can be particularly pertinent for market prices, which often describes a series of local trends.
Segmented polynomial regressions can describe the nature of underlying trends in the price from their fit, such as if an underlying trend is more linear (trending) or constant (ranging), and if a trend is monotonic.
The above chart shows a monthly partitioning on SPX 15m, using a polynomial regression of degree 3. Channel extremities allows highlighting local tops/bottoms.
For real time applications users can choose to fit a current model to incoming price data using the Show fit for new bars settings.
Details
The script does not make use of line.new to display the segmented linear regressions, which allows showing a higher number of historical fits. Each channel extremity as well as the model fit is displayed from the plot function, as such user can more easily set alerts on them.
It is important to note that achieving this requires accessing future price data, as such this script is subject to lookahead bias, historical results differ from the results one could have obtained in real-time.
LudovicaLudovica is a trend following strategy that works on intraday timeframes (15 minutes).
The stop loss is decided based on the last price movement, take profits are projected through a Fibonacci extension. Two different extensions are calculated, based on a filter that affects the last price movement it is chosen which one to use for take profits.
Money management is fixed fractional: regardless of the distance between entry point and stop loss, the risk on capital for each trade is decided by the user in the strategy inputs. Take profits from 1 to 4 plan to exit with 15% of the initial size, TPs from 5 to 8 plan to exit with 10% of initial size.
There is a trailing stop system to reduce the drawdown of the strategy (note that stop loss moves as the trade develops).
Take profits are limit orders, stops (loss or trailing) occur at candlestick close (set alerts on the strategy).
Optimized strategies selectable from input panel:
-ETHUSDTPERP 15 min
-CRVUSDTPERP 15 min v1
-CRVUSDTPERP 15 min v2
-SNXUSDTPERP 15 min
Other pairs in development and soon available.
This strategy is in beta stage.
Unicorn MultiOsMultiOs is an oscillator that combines several widely used oscillators into one. In order to combine different oscillators, it is necessary to reduce them to a single scale. To do this we have developed a custom method based on z-scoring and adjusting by volatility .
The user can choose which of the oscillators from the list to combine into one. The combinations are countless. Some of the combinations may be a better fit for certain markets or trading styles. We call this new class of indicators obtained by combining several oscillators into one - "super oscillators". MultiOs provides a wide scopе for experimentation in creating different super oscillators. A good way to start is to combine all the oscillators from the list into one.
As our practice shows, combining several oscillators into one provides a number of advantages:
The compound super oscillator is smoother than any of its components, but its lag does not increase. This is due to the fact that the calculation does not require additional rolling window averaging. The averaging is performed over an ensemble of several non-smoothed oscillators. The signals are easier to read due to this alternative smoothing mechanism.
The signals are more meaningful and confirmed because they contain contributions from several oscillators and represent their consensus.
In the Candle Mode the MultiOs oscillator is plotted as a candlestick chart. You can apply all sorts of technical analysis to the oscillator candlestick chart, including candlestick patterns analysis. Reversal candlestick patterns in the overbought and oversold zones can give you leading price reversal signals.
We have also included an option to apply the regular smoothing to the MultiOs oscillator. The smoothing feature applies a simple moving average to the oscillator. The Smoothing parameter sets the period of the smoothing moving average.
This feature helps to reduce the number of false trend change signals. But don't forget that smoothing increases the indicator lag. So if you use smoothing, prefer smaller Smoothing parameter values (less than 10). And try to find the optimal tradeoff.
HOW TO USE
Choose which oscillators you would like to include into the mixture, and use the resulting super oscillator as your normal oscillator: forecast price reversals with overbought/oversold conditions and divergences, enter trends with zero line cross signals, detect narrow sideways markets when the oscillator fluctuates in the «gray zone» not going overbought or oversold.
When using this script, please, keep in mind that past results do not necessarily reflect future results and that many factors influence trading results.
SETTINGS
The indicator settings panel allows you to set the parameters that control the calculation and visualization of the indicator. You can also more deeply customize the display of the indicator on the Style tab of the indicator settings panel. This can be useful, for example, to change the colors or make some of the lines brighter.
GLOBAL MODE
Candle Mode - turns on/off the Candle Mode in which the MultiOs oscillator is plotted as a candlestick chart.
MAIN
Oscillator period - sets the oscillator period, which determines the size of the main rolling window, on which all calculations are made.
Smoothing - sets the oscillator smoothing intensity. The value 1 corresponds to the absence of smoothing.
Use Momentum, Use RSI , Use Stochastic , etc. - include/exclude the corresponding oscillator in/from the MultiOs calculation.
DISPLAY
Show MultiOS, Show Momentum, Show RSI , etc. - enable/disable the display of the corresponding oscillator.
Show Zero Line - enables/disables the display of the zero level.
Unicorn X-AlgoUnicorn X-Algo is a multifunctional trading indicator. It is designed to help traders make real-time decisions using quantitative models.
Its core is a trend trading strategy based on our enhanced Trailing Stop-Loss algorithm. This strategy provides the user with position entry and exit signals. It is customizable and has a built-in instant backtesting feature.
For those who have difficulty with finding the good settings the indicator has the Automatic Mode. In this mode, there is no need for the user to adjust any settings. The indicator calculates optimized trading signals automatically.
In addition, the indicator provides a number of useful tools that aim to provide additional confirmation to the trading signals. They include: support and resistance levels forecast, price range prediction and institutional activity detection.
The script can send real-time alerts to the user’s Email and to the cell phone via notifications in the TradingView app.
The indicator can be used for various types of trend and swing trading, including positional trading, day trading and scalping.
Unicorn X-Algo allows users to:
forecast direction of trends with BUY and SELL signals;
determine the right time to close a position;
detect institutional activity in the market;
forecast key support and resistance levels;
predict the future price range for any market;
customize any settings and do a backtest with one click;
see historical trades on the chart;
use the fully Automatic Mode where the algorithm optimizes all its settings itself.
When using this script, keep in mind that past results do not necessarily reflect future results and that many factors influence trading results.
FEATURES
Trading signals
The feature calculates trend or swing entry and exit signals. The underlying strategy does not use fixed Take-Profit levels. It trails the price with a Trailing Stop-Loss to get as many pips as possible from price movements.
The feature is based on our custom Volatility Stop algorithm. It uses linear regressions instead of averaging. As our practice shows, this helps to reduce signal lag while keeping the number of false signals low.
Trading signals are customizable with Sensitivity and Trade Length parameters which determine the trading signals frequency and width of the Trailing-Stop levels, respectively.
Automatic Mode
The Trading Signals function has an automatic mode. When it is turned on, you do not need to adjust the trading signals settings. The algorithm tries to calculate the best settings automatically using an optimization algorithm.
In this mode, Buy and Sell signals are displayed as green and red triangles respectively. There are two types of exit signals displayed as circles and crosses. A circle signal means that a price reversal is expected and you can partially close the position. A cross signal means that a trading signal in the opposite direction is expected soon and you can partially or completely close your position.
Support and Resistance Levels
Support/Resistance levels forecasting model. The forecasted levels are non-repainting. Once calculated for a specified period in the future (day, week, month, etc.), they don't change during this period.
The feature allows the trader to plan trades and use the forecasted levels as entry levels and targets for opening and closing positions. Both intraday and higher timeframes are supported.
The forecasting model analyses the distribution of the price time series to find clusters in the data. These clusters are then used to make the key price levels forecast.
Big Money Activity detection
The Big Money Activity tool identifies areas on the price chart associated with instructional traders' activity in the market.
Institutional activity in a trending market can be a leading signal for upcoming reversal. Institutions could be fixing their profit, causing the price to move against the current trend.
Institutional activity in a sideways market can be due to positions accumulation and signal a new trend formation.
The algorithm uses tick volume, volume, and volatility data to forecast activity of institutional investors. The method develops the idea described in the Daigler & Wiley (2015) and Shalen (1993) works. It says that when institutional traders actively open or close their positions in the market, a divergence between volume and volatility time-series arises. It can be due to their use of position-splitting algorithms that reduce the impact of their positions on the market.
Trading Range Forecast
Trading Range Forecast feature predicts the price range of an asset for a selected period of time in the future, called Forecast Horizon. It can be the next day or 12-hour trading session. This function works if your chart timeframe is intraday (i.e. the timeframe below "D"). It shows the upper and lower bounds between which the price is going to stay in the upcoming Forecast Horizon period.
Instant Backtesting
After changing any settings, you can immediately see the performance of the strategy on the Instant Backtesting panel. Two metrics are displayed there - the percentage of profitable trades and the total return. This information, as well as the historical trades shown on the chart, will help you quickly and easily evaluate any settings you make.
SETTINGS
TRADING SIGNALS
Trade Length - defines the length of the trades the algorithm tries to make. Recommended values are from 1.0 to 6.0.
Sensitivity - controls the sensitivity of the trading signals algorithm. The sensitivity determines the density of trading signals and how close the trailing-stop levels follow the price. The higher the value of this parameter is, the less sensitive the algorithm is. High values of the Sensitivity parameters (100-500) can help to withstand large price swings to stay in longer price moves. Lower values (10-100) work well for short- and medium-term trades.
TRADING TOOLS
Big Money Activity - turns on and off the identification of the areas associated with institutional traders activity.
SUPPORТ AND RESISTANCЕ LEVELS
Show Support And Resistance Levels - turns on and off support and resistance levels calculation.
TRADING RANGE FORECAST
Show Trading Range Forecast - turns on/off trading range forecasting
Forecast Horizon - sets the period for which the trading range forecast is made
Forecasting Method - allows to choose a forecasting algorithm for the trading range forecast.
BACKTESTING
Use Starting Date - turns on/off the starting date for the strategy and backtests. When off, all available historical data is used.
Starting Date - sets the starting date for the strategy and backtests.
Show Instant Backtesting Dashboard - turns on/off a dashboard that shows the current strategy performance: the percentage of profitable trades and total return.
Leverage - sets the leverage that the strategy uses.
Unicorn QuantDeeply customizable trading algorithm with instant backtesting. It emulates real trading and displays all the actions it takes on the chart. For example, it shows when to enter or partially close a position, move Stop-Loss to breakeven, etc. The user can replicate these actions in their trading terminal in real time. The algorithm uses up to three Take-Profit levels, and a Stop-Loss level that can move in a trade to protect the floating profit.
The script can send real-time alerts to the user’s Email and to the cell phone via notifications in the TradingView app.
The indicator is designed to be used on all timeframes, including lower ones for intraday trading and scalping.
HOW TO USE
Set the Stop-Loss and up to three Take-Profit levels. Choose the rules for moving the Stop-Loss level in a trade. Adjust the sensitivity of the trading signals. And check the backtest result in the Instant Backtesting dashboard. If the performance of the strategy satisfies you, proceed with the forward testing or live trading.
When using this script, please, keep in mind that past results do not necessarily reflect future results and there are many factors that influence trading results.
FEATURES
Trading Signals
The feature calculates Buy and Sell signals for trend or swing trading. The user can change the Sensitivity parameter to control the frequency of the signals. This allows them to be adjusted for different markets and timeframes.
Position Manager
To make the Position Manager setup as easy as possible, the algorithm calculates Stop-Loss and Take-Profit levels in Average True Range (ATR) units. They are self-adjusting for any market and timeframe, since they account for its average volatility .
You don't have to worry about what market you are trading - Forex, Stocks, Crypto, etc. With the self-adjusting Stop-Loss and Take-Profit, you can find settings that work for one market and use the same numerical values as a starting point for a completely different market.
Instant Backtesting
After changing any settings, you can immediately see the performance of the strategy on the Instant Backtesting panel. Two metrics are displayed there - the percentage of profitable trades and the total return. This information, as well as the historical trades shown on the chart, will help you quickly and easily evaluate the settings.
SETTINGS
TRADING SIGNALS
Sensitivity - controls the sensitivity of the trading signals algorithm. It determines the frequency of the trading signals. The higher the value of this parameter, the less trading signals you get and the longer trends the algorithm tries to catch. The lower the sensitivity value, the more signals you receive. This can be useful if you want to profit from small price movements.
POSITION MANAGER
SL - sets the Stop-Loss level measured in ATR units.
TP1, TP2, TP3 - set the Take-Profit levels measured in the ATR units.
Close % at TP1, Close % at TP2, Close % at TP3 - set portions of the open position (as a percentage of the initial order size) to close at each of the TP levels.
At TP1 move SL to, At TP2 move SL to - set the rules for moving the Stop-Loss level in an open trade to protect the floating profit.
Show Open Position Dashboard - turns on/off a dashboard that shows the current Stop-Loss and Take-Profit levels for the open position.
BACKTESTING
Use Starting Date - turns on/off the starting date for the strategy and backtests. When off, all available historical data is used.
Starting Date - sets the starting date for the strategy and backtests.
Show Instant Backtesting Dashboard - turns on/off a dashboard that shows the current strategy performance: the percentage of profitable trades and total return.
Leverage - sets the leverage that the strategy uses.
ADXVMA iTrend [Loxx]ADXVMA iTrend is an iTrend indicator with ADXVMA smoothing. Trend is used to determine where the trend starts and ends. Adjust the period inputs accordingly to suit your backtest requirements. This is also useful for scalping lower timeframes.
What is the 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.
Included
Bar coloring
Alerts
Signals
Loxx's Expanded Source Types
VHF-Adaptive T3 iTrend [Loxx]VHF-Adaptive T3 iTrend is an iTrend indicator with T3 smoothing and Vertical Horizontal Filter Adaptive period input. iTrend is used to determine where the trend starts and ends. You'll notice that the noise filter on this one is extreme. Adjust the period inputs accordingly to suit your take and your backtest requirements. This is also useful for scalping lower timeframes. Enjoy!
What is VHF Adaptive Period?
Vertical Horizontal Filter (VHF) was created by Adam White to identify trending and ranging markets. VHF measures the level of trend activity, similar to ADX DI. Vertical Horizontal Filter does not, itself, generate trading signals, but determines whether signals are taken from trend or momentum indicators. Using this trend information, one is then able to derive an average cycle length.
What is the T3 moving average?
Better Moving Averages Tim Tillson
November 1, 1998
Tim Tillson is a software project manager at Hewlett-Packard, with degrees in Mathematics and Computer Science. He has privately traded options and equities for 15 years.
Introduction
"Digital filtering includes the process of smoothing, predicting, differentiating, integrating, separation of signals, and removal of noise from a signal. Thus many people who do such things are actually using digital filters without realizing that they are; being unacquainted with the theory, they neither understand what they have done nor the possibilities of what they might have done."
This quote from R. W. Hamming applies to the vast majority of indicators in technical analysis . Moving averages, be they simple, weighted, or exponential, are lowpass filters; low frequency components in the signal pass through with little attenuation, while high frequencies are severely reduced.
"Oscillator" type indicators (such as MACD , Momentum, Relative Strength Index ) are another type of digital filter called a differentiator.
Tushar Chande has observed that many popular oscillators are highly correlated, which is sensible because they are trying to measure the rate of change of the underlying time series, i.e., are trying to be the first and second derivatives we all learned about in Calculus.
We use moving averages (lowpass filters) in technical analysis to remove the random noise from a time series, to discern the underlying trend or to determine prices at which we will take action. A perfect moving average would have two attributes:
It would be smooth, not sensitive to random noise in the underlying time series. Another way of saying this is that its derivative would not spuriously alternate between positive and negative values.
It would not lag behind the time series it is computed from. Lag, of course, produces late buy or sell signals that kill profits.
The only way one can compute a perfect moving average is to have knowledge of the future, and if we had that, we would buy one lottery ticket a week rather than trade!
Having said this, we can still improve on the conventional simple, weighted, or exponential moving averages. Here's how:
Two Interesting Moving Averages
We will examine two benchmark moving averages based on Linear Regression analysis.
In both cases, a Linear Regression line of length n is fitted to price data.
I call the first moving average ILRS, which stands for Integral of Linear Regression Slope. One simply integrates the slope of a linear regression line as it is successively fitted in a moving window of length n across the data, with the constant of integration being a simple moving average of the first n points. Put another way, the derivative of ILRS is the linear regression slope. Note that 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.
We can measure the lag of moving averages with respect to a linear trend by computing how they behave when the input is a line with unit slope. Both SMA (n) and ILRS(n) have lag of n/2, but ILRS is much smoother than SMA .
Our second benchmark moving average is well known, called EPMA or End Point Moving Average. It is the endpoint of the linear regression line of length n as it is fitted across the data. EPMA hugs the data more closely than a simple or exponential moving average of the same length. The price we pay for this is that it is much noisier (less smooth) than ILRS, and it also has the annoying property that it overshoots the data when linear trends are present.
However, EPMA has a lag of 0 with respect to linear input! This makes sense because a linear regression line will fit linear input perfectly, and the endpoint of the LR line will be on the input line.
These two moving averages frame the tradeoffs that we are facing. On one extreme we have ILRS, which is very smooth and has considerable phase lag. EPMA has 0 phase lag, but is too noisy and overshoots. We would like to construct a better moving average which is as smooth as ILRS, but runs closer to where EPMA lies, without the overshoot.
A easy way to attempt this is to split the difference, i.e. use (ILRS(n)+EPMA(n))/2. This will give us a moving average (call it IE /2) which runs in between the two, has phase lag of n/4 but still inherits considerable noise from EPMA. IE /2 is inspirational, however. Can we build something that is comparable, but smoother? Figure 1 shows ILRS, EPMA, and IE /2.
Filter Techniques
Any thoughtful student of filter theory (or resolute experimenter) will have noticed that you can improve the smoothness of a filter by running it through itself multiple times, at the cost of increasing phase lag.
There is a complementary technique (called twicing by J.W. Tukey) which can be used to improve phase lag. If L stands for the operation of running data through a low pass filter, then twicing can be described by:
L' = L(time series) + L(time series - L(time series))
That is, we add a moving average of the difference between the input and the moving average to the moving average. This is algebraically equivalent to:
2L-L(L)
This is the Double Exponential Moving Average or DEMA , popularized by Patrick Mulloy in TASAC (January/February 1994).
In our taxonomy, DEMA has some phase lag (although it exponentially approaches 0) and is somewhat noisy, comparable to IE /2 indicator.
We will use these two techniques to construct our better moving average, after we explore the first one a little more closely.
Fixing Overshoot
An n-day EMA has smoothing constant alpha=2/(n+1) and a lag of (n-1)/2.
Thus EMA (3) has lag 1, and EMA (11) has lag 5. Figure 2 shows that, if I am willing to incur 5 days of lag, I get a smoother moving average if I run EMA (3) through itself 5 times than if I just take EMA (11) once.
This suggests that if EPMA and DEMA have 0 or low lag, why not run fast versions (eg DEMA (3)) through themselves many times to achieve a smooth result? The problem is that multiple runs though these filters increase their tendency to overshoot the data, giving an unusable result. This is because the amplitude response of DEMA and EPMA is greater than 1 at certain frequencies, giving a gain of much greater than 1 at these frequencies when run though themselves multiple times. Figure 3 shows DEMA (7) and EPMA(7) run through themselves 3 times. DEMA^3 has serious overshoot, and EPMA^3 is terrible.
The solution to the overshoot problem is to recall what we are doing with twicing:
DEMA (n) = EMA (n) + EMA (time series - EMA (n))
The second term is adding, in effect, a smooth version of the derivative to the EMA to achieve DEMA . The derivative term determines how hot the moving average's response to linear trends will be. We need to simply turn down the volume to achieve our basic building block:
EMA (n) + EMA (time series - EMA (n))*.7;
This is algebraically the same as:
EMA (n)*1.7-EMA( EMA (n))*.7;
I have chosen .7 as my volume factor, but the general formula (which I call "Generalized Dema") is:
GD (n,v) = EMA (n)*(1+v)-EMA( EMA (n))*v,
Where v ranges between 0 and 1. When v=0, GD is just an EMA , and when v=1, GD is DEMA . In between, GD is a cooler DEMA . By using a value for v less than 1 (I like .7), we cure the multiple DEMA overshoot problem, at the cost of accepting some additional phase delay. Now we can run GD through itself multiple times to define a new, smoother moving average T3 that does not overshoot the data:
T3(n) = GD ( GD ( GD (n)))
In filter theory parlance, T3 is a six-pole non-linear Kalman filter. Kalman filters are ones which use the error (in this case (time series - EMA (n)) to correct themselves. In Technical Analysis , these are called Adaptive Moving Averages; they track the time series more aggressively when it is making large moves.
Included
Bar coloring
Alerts
Signals
Loxx's Expanded Source Types
T&M/E Wave V2Trend and Momentum With Exception Wave Indicator and Strategy:
This strategy is hand made and I have spent days and many hours making it. The strategy is meant to determine the power between buyers and sellers, match the current power with a historic trend (through a moving average statistical equation), and finally volatility (measured with a mix between standard deviation from Bollinger Bands and HPV). Below will be a list of how to determine the inputs for the indicator
**For reference, all numbers, and settings displayed on the input screen are only what I HAVE FOUND to be profitable for my own strategy, Yours will differ. This is not financial advice and I am not a financial advisor. Please do your due diligence and own research before considering taking entries based on this strategy and indicator. I am not advertising investing, trading, or skills untaught, this is simply to help incorporate into your own strategy and improve your trading journey!**
INPUTS:
EV: This is an integer value set to default at 55. This value is equated to the lead value, volatility measurement, and standard deviation between averages
EV 2: This integer is used as the base value and is meant to always be GREATER THEN EV, the default is set at 163. There should be at least a 90+ integer difference between EVs for data accuracy.
EV TYPE & EV TYPE 2: This option only affects the output for the moving average histograms. (and data inserted for strategy)
Volatility Smoothing: This is the smoothness of the custom-made volatility oscillator. I have this default at 1 to show time-worthy-term (3.9%+) moves or significant trends to correspond with the standard deviation declination between EVMA and EVMA2.
Directional Length: This is the amount of data observed per candle in the bull versus bear indicator.
Take Profit: Pre-set takes profit level that is set to 4 but can be adjusted for user experience.
Style:
Base Length: Columns equated using a custom-made statistical equation derived from EV TYPE 2+EV2 to determine a range of differential in historic averages to a micro-scale.
Lead Length: Columns equated using a custom-made statistical equation derived from EV TYPE+EV to determine a range of differential in historic averages to a micro-scale.
Weighted EMA Differential: Equation expressing the differences between exponential and simple averages derived from EV+EV Type 2. Default is displaying none, but optional for use if found helpful.
Volatility: Represents volatility from multiple data sets spanning from Bollinger bands to HPV and translated through smoothing.
Bull Strength: The strength of Bulls in the current trend is derived from a DMI+RSI+MACD equation to represent where the trend lies.
Bear Strength: The strength of Bears in the current trend is derived from a DMI+RSI+MACD equation to represent where the trend lies.
CHEAT CODE'S NOTES:
Do not use this indicator on high leverage. I have personally used this indicator for a week and faced a max of 8% drawdown, albeit painful I was on low leverage and still closed on my take profit level.
85% is not 100% do not overtrade using this indicator's entry conditions if you have made 4 consecutive profitable trades.
Mess around with the input values and let me know if you find an even BETTER hit rate, 30+ entries and a good drawdown!!
V2 UPGRADES:
*Increased Opacity on Bull Bear Columns
*Removed the Stop Loss Input option
*Decreased EV2 to a default of 143 for accuracy
*Added additional disclaimers in the description
* Removed Bull/Bear offset values for accuracy
-Cheat Code
BYBIT:BTCUSDT
Donchian Channels+Standard Donchian Channels, this includes a Trend EMA which can be configured and the channels will use to give buy and sell signals. The channels are also colored in such a way to indicate a trend reversals. My favorite part that sets this apart from others is, if using the bClose option (which I recommend you do) the trend will not reverse until there is a close above/below the previous channel high/low. i.e. a reversal into an uptrend requires the current bar to close above the previous upper channel rather than just a new high.
The coloring of the current trend allows for a quick read of current market conditions and I use this on any timeframe across all forms of charts (forex stock, futures , crypto, etc). When taking one of the signals I use the opposite channel as the stop loss (when buying use bottom, and selling use top channel)
Update 1:
- Added my name to the code
- Updated the picture to show off the indicator better
- Raised the brightness of the fill color a bit, looks nicer I think
As a warning: I have obviously hand picked this picture to really show off this indicator's power to work in a trending market. Donchian Channels are a trending indicator and work best in trending markets with decent pull backs. If there are multiple signals going in each direction, it is a choppy market and you should stay out until it starts trending again. I generally use a 1:1.5 risk to reward ratio but sometimes will stretch it to 1:2 if it is a nice trade and I feel the market is in my favor as you can see from the trades placed in the picture (and I use that method for any commodity / chart and timeframe). I use the close of the white candle and then (since they are trades going short) I use the upper Donchian Channel as my stop loss.
I personally like to have the lines and labels turned off and enable all other options. Labels are just there to really stand out so you don't miss the white candle indication for a trade. OH! Also, I've had comments from friends that the white candles are hard to see, I turn off my candle borders in settings; makes it super easy to see them then. I turn lines off as the fill does the job well enough and it seems cleaner in my eyes.
If you'd like to see this picture on your chart, it is Micro E-Mini S&P 500 Futures from July 10, 2022 @ 18:00 on the 1-min chart.
just now
Update 2:
- Added day trading time highlights
- Added ranging market indicator (This I'm still working on so use at your own discretion, it's intended purpose is to tell when the Donchian Channels are not going to give great signals and to use a ranging indicator instead)
- Added multi-timeframe trend screener (handy if you want to quickly see the trend direction (based on the Trend EMA you set) of several time frames without having to change charts). It will draw in the bottom right of the chart.
Mark MinerviniHi everyone,
Just sharing a script that I made when I began to be interested in Mark Minervini, Wiliam O'Neil, Nicolas Darvas,.. trading style.
This script displays :
- 10 EMA (orange)
- 20 EMA (blue light)
- 50 SMA (blue)
-150 SMA (green)
-200 SMA (red)
- Shows when the stock is "extended" from EMA10 to high of the candle (Works in Daily, you can adjust the % to make it match with the stock's volatility)
(Shows a red area between price and 10 EMA)
- Shows when Mark Minervini's trend template is respected by highlighting green between 150 & 200 SMA.
I Although added bollinger bands and 5 EMA for very strong stocks. (I never use them)
Have fun
EMA Cross CloudSimple ema cross trading alerts, completely customizable fast and slow crossovers with rendered cloud.
This cross indicator attempts to filter counter trend trades by added additional ema market and if crossunder/over occurs opposite of ema market the cloud will turn gray, otherwise if it's with the overall trend then red/green.
The last ema is a trailing stop guideline that is rendered with yellow crosses, could also utilize other stops such as the top or bottom of the cloud.
Alerts are baked in for ema crosses, trend breaks into stops.
NLX Trading Bot Framework (+Trend Score & QQE)- Demo of my NLX Modular Trading Framework -
It includes all the common indicators and creates a positive or negative score, which can be used with my Modular Trading Framework and linked to an entry/exit indicator to filter out buy/sell signals if the trend is not favorable.
Combination of:
SuperTrend
VWAP Bands
Relative Strength Index ( RSI )
Commodity Channel Index ( CCI )
William Percent Range (WPR)
Directional Movement Index (DMI)
Elder Force Index ( EFI )
Momentum
Demarker
Parabolic SAR
- Getting Started -
1. Add this Trend Index to your Chart
2. Add one of my Indicator Modules to your Chart, such as the QQE++ Indicator
3. In the QQE Indicator Settings combine it with the Trend Index (and choose L1 Type)
4. Optional: Add the Noise Filter, and in the Noise Filter Settings you select the QQE Indicator as combination (and choose L2 for Type)
5. Add the Backtest Module to your Chart
6. Select the Noise Filter in the Backtest Settings
- Access -
Only as part of the NLX Framework - see my signature below for more info.
Smoothed Heikin Ashi Trend on Chart - TraderHalai BACKTESTSmoothed Heikin Ashi Trend on chart - Backtest
This is a backtest of the Smoothed Heikin Ashi Trend indicator, which computes the reverse candle close price required to flip a Heikin Ashi trend from red to green and vice versa. The original indicator can be found in the scripts section of my profile.
This particular back test uses this indicator with a Trend following paradigm with a percentage-based stop loss.
Note, that backtesting performance is not always indicative of future performance, but it does provide some basis for further development and walk-forward / live testing.
Testing was performed on Bitcoin , as this is a primary target market for me to use this kind of strategy.
Sample Backtesting results as of 10th June 2022:
Backtesting parameters:
Position size: 10% of equity
Long stop: 1% below entry
Short stop: 1% above entry
Repainting: Off
Smoothing: SMA
Period: 10
8 Hour:
Number of Trades: 1046
Gross Return: 249.27 %
CAGR Return: 14.04 %
Max Drawdown: 7.9 %
Win percentage: 28.01 %
Profit Factor (Expectancy): 2.019
Average Loss: 0.33 %
Average Win: 1.69 %
Average Time for Loss: 1 day
Average Time for Win: 5.33 days
1 Day:
Number of Trades: 429
Gross Return: 458.4 %
CAGR Return: 15.76 %
Max Drawdown: 6.37 %
Profit Factor (Expectancy): 2.804
Average Loss: 0.8 %
Average Win: 7.2 %
Average Time for Loss: 3 days
Average Time for Win: 16 days
5 Day:
Number of Trades: 69
Gross Return: 1614.9 %
CAGR Return: 26.7 %
Max Drawdown: 5.7 %
Profit Factor (Expectancy): 10.451
Average Loss: 3.64 %
Average Win: 81.17 %
Average Time for Loss: 15 days
Average Time for Win: 85 days
Analysis:
The strategy is typical amongst trend following strategies with a less regular win rate, but where profits are more significant than losses. Most of the losses are in sideways, low volatility markets. This strategy performs better on higher timeframes, where it shows a positive expectancy of the strategy.
The average win was positively impacted by Bitcoin’s earlier smaller market cap, as the percentage wins earlier were higher.
Overall the strategy shows potential for further development and may be suitable for walk-forward testing and out of sample analysis to be considered for a demo trading account.
Note in an actual trading setup, you may wish to use this with volatility filters, combined with support resistance zones for a better setup.
As always, this post/indicator/strategy is not financial advice, and please do your due diligence before trading this live.
Original indicator links:
On chart version -
Oscillator version -
Update - 27/06/2022
Unfortunately, It appears that the original script had been taken down due to auto-moderation because of concerns with no slippage / commission. I have since adjusted the backtest, and re-uploaded to include the following to address these concerns, and show that I am genuinely trying to give back to the community and not mislead anyone:
1) Include commission of 0.1% - to match Binance's maker fees prior to moving to a fee-less model.
2) Include slippage of 10 ticks (This is a realistic slippage figure from searching online for most crypto exchanges)
3) Adjust account balance to 10,000 - since most of us are not millionaires.
The rest of the backtesting parameters are comparable to previous results:
Backtesting parameters:
Initial capital: 10000 dollars
Position size: 10% of equity
Long stop: 2% below entry
Short stop: 2% above entry
Repainting: Off
Smoothing: SMA
Period: 10
Slippage: 10 ticks
Commission: 0.1%
This script still remains to shows viability / profitablity on higher term timeframes (with slightly higher drawdown), and I have included the backtest report below to document my findings:
8 Hour:
Number of Trades: 1082
Gross Return: 233.02%
CAGR Return: 14.04 %
Max Drawdown: 7.9 %
Win percentage: 25.6%
Profit Factor (Expectancy): 1.627
Average Loss: 0.46 %
Average Win: 2.18 %
Average Time for Loss: 1.33 day
Average Time for Win: 7.33 days
Once again, please do your own research and due dillegence before trading this live. This post is for education and information purposes only, and should not be taken as financial advice.
Nyquist Moving Average (NMA) MACD [Loxx]Nyquist Moving Average (NMA) MACD is a MACD indicator using Nyquist Moving Average for its calculation.
What is the Nyquist Moving Average?
A moving average outlined originally developed by Dr . Manfred G. Dürschner in his paper "Gleitende Durchschnitte 3.0".
In signal processing theory, the application of a MA to itself can be seen as a Sampling procedure. The sampled signal is the MA (referred to as MA.) and the sampling signal is the MA as well (referred to as MA). If additional periodic cycles which are not included in the price series are to be avoided sampling must obey the Nyquist Criterion.
It can be concluded that the Moving Averages 3.0 on the basis of the Nyquist Criterion bring about a significant improvement compared with the Moving Averages 2.0 and 1.0. Additionally, the efficiency of the Moving Averages 3.0 can be proven in the result of a trading system with NWMA as basis.
What is the MACD?
Moving average convergence divergence (MACD) is a trend-following momentum indicator that shows the relationship between two moving averages of a security’s price. The MACD is calculated by subtracting the 26-period exponential moving average (EMA) from the 12-period EMA.
The result of that calculation is the MACD line. A nine-day EMA of the MACD called the "signal line," is then plotted on top of the MACD line, which can function as a trigger for buy and sell signals. Traders may buy the security when the MACD crosses above its signal line and sell—or short—the security when the MACD crosses below the signal line. Moving average convergence divergence (MACD) indicators can be interpreted in several ways, but the more common methods are crossovers, divergences, and rapid rises/falls.
Included
Bar coloring
2 types of signal output options
Alerts
Loxx's Expanded Source Types
RSI Precision Trend Candles [Loxx]RSI Precision Trend Candles is a candle coloring indicator that uses an average range algorithm to determine trend direction. The precision trend algorithm can be used on any calculated output to tease out interesting trend information.
What is RSI?
The relative strength index (RSI) is a momentum indicator used in technical analysis. RSI measures the speed and magnitude of a security's recent price changes to evaluate overvalued or undervalued conditions in the price of that security.
The RSI is displayed as an oscillator (a line graph) on a scale of zero to 100. The indicator was developed by J. Welles Wilder Jr. and introduced in his seminal 1978 book, New Concepts in Technical Trading Systems.
Included
Bar coloring
Signals
Alerts
Loxx's Expanded Source Types
