Fusion MFI RSIHello fellas,
This superb indicator summons two monsters called Relative Strength Index (RSI) and Money Flow Index (MFI) and plays the Yu-Gi-Oh! card "Polymerization" to combine them.
Overview
The Fusion MFI RSI Indicator is an advanced analytical tool designed to provide a nuanced understanding of market dynamics by combining the Relative Strength Index (RSI) and the Money Flow Index (MFI). Enhanced with sophisticated smoothing techniques and the Inverse Fisher Transform (IFT), this indicator excels in identifying key market conditions such as overbought and oversold states, trends, and potential reversal points.
Key Features (Brief Overview)
Fusion of RSI and MFI: Integrates momentum and volume for a comprehensive market analysis.
Advanced Smoothing Techniques: Employs Hann Window, Jurik Moving Average (JMA), T3 Smoothing, and Super Smoother to refine signals.
Inverse Fisher Transform (IFT) Enhances the clarity and distinctiveness of indicator outputs.
Detailed Feature Analysis
Fusion of RSI and MFI
RSI (Relative Strength Index): Developed by J. Welles Wilder Jr., the RSI measures the speed and magnitude of directional price movements. Wilder recommended using a 14-day period and identified overbought conditions above 70 and oversold conditions below 30.
MFI (Money Flow Index): Created by Gene Quong and Avrum Soudack, the MFI combines price and volume to measure trading pressure. It is typically calculated using a 14-day period, with over 80 considered overbought and under 20 as oversold.
Application in Fusion: By combining RSI and MFI, the indicator leverages RSI's sensitivity to price changes with MFI's volume-weighted confirmation, providing a robust analysis tool. This combination is particularly effective in confirming the strength behind price movements, making the signals more reliable.
Advanced Smoothing Techniques
Hann Window: Traditionally used to reduce the abrupt data discontinuities at the edges of a sample, it is applied here to smooth the price data.
Jurik Moving Average (JMA): Known for preserving the timing and smoothness of the data, JMA reduces market noise effectively without significant lag.
T3 Smoothing: Developed to respond quickly to market changes, T3 provides a smoother response to price fluctuations.
Super Smoother: Filters out high-frequency noise while retaining important trends.
Application in Fusion: These techniques are chosen to refine the output of the combined RSI and MFI values, ensuring the indicator remains responsive yet stable, providing clearer and more actionable signals.
Inverse Fisher Transform (IFT):
Developed by John Ehlers, the IFT transforms oscillator outputs to enhance the clarity of extreme values. This is particularly useful in this fusion indicator to make critical turning points more distinct and actionable.
Mathematical Calculations for the Fusion MFI RSI Indicator
RSI (Relative Strength Index)
The RSI is calculated using the following steps:
Average Gain and Average Loss: First, determine the average gain and average loss over the specified period (typically 14 days). This is done by summing all the gains and losses over the period and then dividing each by the period.
Average Gain = (Sum of Gains over the past 14 periods) / 14
Average Loss = (Sum of Losses over the past 14 periods) / 14
Relative Strength (RS): This is the ratio of average gain to average loss.
RS = Average Gain / Average Loss
RSI: Finally, the RSI is calculated using the RS value:
RSI = 100 - (100 / (1 + RS))
MFI (Money Flow Index)
The MFI is calculated using several steps that incorporate both price and volume:
Typical Price: Calculate the typical price for each period.
Typical Price = (High + Low + Close) / 3
Raw Money Flow: Multiply the typical price by the volume for the period.
Raw Money Flow = Typical Price * Volume
Positive and Negative Money Flow: Compare the typical price of the current period to the previous period to determine if the money flow is positive or negative.
If today's Typical Price > Yesterday's Typical Price, then Positive Money Flow = Raw Money Flow; Negative Money Flow = 0
If today's Typical Price < Yesterday's Typical Price, then Negative Money Flow = Raw Money Flow; Positive Money Flow = 0
Money Flow Ratio: Calculate the ratio of the sum of Positive Money Flows to the sum of Negative Money Flows over the past 14 periods.
Money Flow Ratio = (Sum of Positive Money Flows over 14 periods) / (Sum of Negative Money Flows over 14 periods)
MFI: Finally, calculate the MFI using the Money Flow Ratio.
MFI = 100 - (100 / (1 + Money Flow Ratio))
Fusion of RSI and MFI
The final Fusion MFI RSI value could be calculated by averaging the IFT-transformed values of RSI and MFI, providing a single oscillator value that reflects both momentum and volume-weighted price action:
Fusion MFI RSI = (MFI weight * MFI) + (RSI weight * RSI)
Suggested Settings and Trading Rules
Original Usage
RSI: Wilder suggested buying when the RSI moves above 30 from below (enter long) and selling when the RSI moves below 70 from above (enter short). He recommended exiting long positions when the RSI reaches 70 or higher and exiting short positions when the RSI falls below 30.
MFI: Quong and Soudack recommended buying when the MFI is below 20 and starts rising (enter long), and selling when it is above 80 and starts declining (enter short). They suggested exiting long positions when the MFI reaches 80 or higher and exiting short positions when the MFI falls below 20.
Fusion Application
Settings: Use a 14-day period for this indicator's calculations to maintain consistency with the original settings suggested by the inventors.
Trading Rules:
Enter Long Signal: Consider entering a long position when both RSI and MFI are below their respective oversold levels and begin to rise. This indicates strong buying pressure supported by both price momentum and volume.
Exit Long Signal: Exit the long position when either RSI or MFI reaches its respective overbought threshold, suggesting a potential reversal or decrease in buying pressure.
Enter Short Signal: Consider entering a short position when both indicators are above their respective overbought levels and begin to decline, suggesting that selling pressure is mounting.
Exit Short Signal: Exit the short position when either RSI or MFI falls below its respective oversold threshold, indicating diminishing selling pressure and a potential upward reversal.
How to Use the Indicator
Select Source and Timeframe: Choose the data source and the timeframe for analysis.
Configure Fusion Settings: Adjust the weights for RSI and MFI.
Choose Smoothing Technique: Select and configure the desired smoothing method to suit the market conditions and personal preference.
Enable Fisherization: Optionally apply the Inverse Fisher Transform to enhance signal clarity.
Customize Visualization: Set up gradient coloring, background plots, and bands according to your preferences.
Interpret the Indicator: Use the Fusion value and visual cues to identify market conditions and potential trading opportunities.
Conclusion
The Fusion MFI RSI Indicator integrates classical and modern technical analysis concepts to provide a comprehensive tool for market analysis. By combining RSI and MFI with advanced smoothing techniques and the Inverse Fisher Transform, this indicator offers enhanced insights, aiding traders in making more informed and timely trading decisions. Customize the settings to align with your trading strategy and leverage this powerful tool to navigate financial markets effectively.
Best regards,
simwai
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Credits to:
@loxx – T3
@everget – JMA
@cheatcountry – Hann Window
Inversefishertransform
GKD-C Non-Lag Inverse Fisher Transform of RSX [Loxx]Giga Kaleidoscope GKD-C Non-Lag Inverse Fisher Transform of RSX is a Confirmation module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
█ Giga Kaleidoscope Modularized Trading System
What is Loxx's "Giga Kaleidoscope Modularized Trading System"?
The Giga Kaleidoscope Modularized Trading System is a trading system built on the philosophy of the NNFX (No Nonsense Forex) algorithmic trading.
What is the NNFX algorithmic trading strategy?
The NNFX (No-Nonsense Forex) trading system is a comprehensive approach to Forex trading that is designed to simplify the process and remove the confusion and complexity that often surrounds trading. The system was developed by a Forex trader who goes by the pseudonym "VP" and has gained a significant following in the Forex community.
The NNFX trading system is based on a set of rules and guidelines that help traders make objective and informed decisions. These rules cover all aspects of trading, including market analysis, trade entry, stop loss placement, and trade management.
Here are the main components of the NNFX trading system:
1. Trading Philosophy: The NNFX trading system is based on the idea that successful trading requires a comprehensive understanding of the market, objective analysis, and strict risk management. The system aims to remove subjective elements from trading and focuses on objective rules and guidelines.
2. Technical Analysis: The NNFX trading system relies heavily on technical analysis and uses a range of indicators to identify high-probability trading opportunities. The system uses a combination of trend-following and mean-reverting strategies to identify trades.
3. Market Structure: The NNFX trading system emphasizes the importance of understanding the market structure, including price action, support and resistance levels, and market cycles. The system uses a range of tools to identify the market structure, including trend lines, channels, and moving averages.
4. Trade Entry: The NNFX trading system has strict rules for trade entry. The system uses a combination of technical indicators to identify high-probability trades, and traders must meet specific criteria to enter a trade.
5. Stop Loss Placement: The NNFX trading system places a significant emphasis on risk management and requires traders to place a stop loss order on every trade. The system uses a combination of technical analysis and market structure to determine the appropriate stop loss level.
6. Trade Management: The NNFX trading system has specific rules for managing open trades. The system aims to minimize risk and maximize profit by using a combination of trailing stops, take profit levels, and position sizing.
Overall, the NNFX trading system is designed to be a straightforward and easy-to-follow approach to Forex trading that can be applied by traders of all skill levels.
Core components of an NNFX algorithmic trading strategy
The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend
3. Confirmation 1 - a technical indicator used to identify trends
4. Confirmation 2 - a technical indicator used to identify trends
5. Continuation - a technical indicator used to identify trends
6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown
7. Exit - a technical indicator used to determine when a trend is exhausted
What is Volatility in the NNFX trading system?
In the NNFX (No Nonsense Forex) trading system, ATR (Average True Range) is typically used to measure the volatility of an asset. It is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. ATR is calculated by taking the average of the true range values over a specified period.
True range is calculated as the maximum of the following values:
-Current high minus the current low
-Absolute value of the current high minus the previous close
-Absolute value of the current low minus the previous close
ATR is a dynamic indicator that changes with changes in volatility. As volatility increases, the value of ATR increases, and as volatility decreases, the value of ATR decreases. By using ATR in NNFX system, traders can adjust their stop loss and take profit levels according to the volatility of the asset being traded. This helps to ensure that the trade is given enough room to move, while also minimizing potential losses.
Other types of volatility include True Range Double (TRD), Close-to-Close, and Garman-Klass
What is a Baseline indicator?
The baseline is essentially a moving average, and is used to determine the overall direction of the market.
The baseline in the NNFX system is used to filter out trades that are not in line with the long-term trend of the market. The baseline is plotted on the chart along with other indicators, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR).
Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards, only long trades are taken, and if the baseline is sloping downwards, only short trades are taken. This approach helps to ensure that trades are in line with the overall trend of the market, and reduces the risk of entering trades that are likely to fail.
By using a baseline in the NNFX system, traders can have a clear reference point for determining the overall trend of the market, and can make more informed trading decisions. The baseline helps to filter out noise and false signals, and ensures that trades are taken in the direction of the long-term trend.
What is a Confirmation indicator?
Confirmation indicators are technical indicators that are used to confirm the signals generated by primary indicators. Primary indicators are the core indicators used in the NNFX system, such as the Average True Range (ATR), the Moving Average (MA), and the Relative Strength Index (RSI).
The purpose of the confirmation indicators is to reduce false signals and improve the accuracy of the trading system. They are designed to confirm the signals generated by the primary indicators by providing additional information about the strength and direction of the trend.
Some examples of confirmation indicators that may be used in the NNFX system include the Bollinger Bands, the MACD (Moving Average Convergence Divergence), and the MACD Oscillator. These indicators can provide information about the volatility, momentum, and trend strength of the market, and can be used to confirm the signals generated by the primary indicators.
In the NNFX system, confirmation indicators are used in combination with primary indicators and other filters to create a trading system that is robust and reliable. By using multiple indicators to confirm trading signals, the system aims to reduce the risk of false signals and improve the overall profitability of the trades.
What is a Continuation indicator?
In the NNFX (No Nonsense Forex) trading system, a continuation indicator is a technical indicator that is used to confirm a current trend and predict that the trend is likely to continue in the same direction. A continuation indicator is typically used in conjunction with other indicators in the system, such as a baseline indicator, to provide a comprehensive trading strategy.
What is a Volatility/Volume indicator?
Volume indicators, such as the On Balance Volume (OBV), the Chaikin Money Flow (CMF), or the Volume Price Trend (VPT), are used to measure the amount of buying and selling activity in a market. They are based on the trading volume of the market, and can provide information about the strength of the trend. In the NNFX system, volume indicators are used to confirm trading signals generated by the Moving Average and the Relative Strength Index. Volatility indicators include Average Direction Index, Waddah Attar, and Volatility Ratio. In the NNFX trading system, volatility is a proxy for volume and vice versa.
By using volume indicators as confirmation tools, the NNFX trading system aims to reduce the risk of false signals and improve the overall profitability of trades. These indicators can provide additional information about the market that is not captured by the primary indicators, and can help traders to make more informed trading decisions. In addition, volume indicators can be used to identify potential changes in market trends and to confirm the strength of price movements.
What is an Exit indicator?
The exit indicator is used in conjunction with other indicators in the system, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR), to provide a comprehensive trading strategy.
The exit indicator in the NNFX system can be any technical indicator that is deemed effective at identifying optimal exit points. Examples of exit indicators that are commonly used include the Parabolic SAR, the Average Directional Index (ADX), and the Chandelier Exit.
The purpose of the exit indicator is to identify when a trend is likely to reverse or when the market conditions have changed, signaling the need to exit a trade. By using an exit indicator, traders can manage their risk and prevent significant losses.
In the NNFX system, the exit indicator is used in conjunction with a stop loss and a take profit order to maximize profits and minimize losses. The stop loss order is used to limit the amount of loss that can be incurred if the trade goes against the trader, while the take profit order is used to lock in profits when the trade is moving in the trader's favor.
Overall, the use of an exit indicator in the NNFX trading system is an important component of a comprehensive trading strategy. It allows traders to manage their risk effectively and improve the profitability of their trades by exiting at the right time.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v1.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data between modules. Data is passed between each module as described below:
GKD-B => GKD-V => GKD-C(1) => GKD-C(2) => GKD-C(Continuation) => GKD-E => GKD-BT
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Strategy with 1-3 take profits, trailing stop loss, multiple types of PnL volatility, and 2 backtesting styles
Baseline: Hull Moving Average
Volatility/Volume: Hurst Exponent
Confirmation 1: Non-Lag Inverse Fisher Transform of RSX as shown on the chart above
Confirmation 2: Williams Percent Range
Continuation: Fisher Transform
Exit: Rex Oscillator
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD protocol chain.
Giga Kaleidoscope Modularized Trading System Signals (based on the NNFX algorithm)
Standard Entry
1. GKD-C Confirmation 1 Signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
6. GKD-C Confirmation 1 signal was less than 7 candles prior
Volatility/Volume Entry
1. GKD-V Volatility/Volume signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-B Baseline agrees
6. GKD-C Confirmation 1 signal was less than 7 candles prior
Continuation Entry
1. Standard Entry, Baseline Entry, or Pullback; entry triggered previously
2. GKD-B Baseline hasn't crossed since entry signal trigger
3. GKD-C Confirmation Continuation Indicator signals
4. GKD-C Confirmation 1 agrees
5. GKD-B Baseline agrees
6. GKD-C Confirmation 2 agrees
1-Candle Rule Standard Entry
1. GKD-C Confirmation 1 signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
1-Candle Rule Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 1 signal was less than 7 candles prior
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume Agrees
1-Candle Rule Volatility/Volume Entry
1. GKD-V Volatility/Volume signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 1 signal was less than 7 candles prior
Next Candle:
1. Price retraced (Long: close < close or Short: close > close)
2. GKD-B Volatility/Volume agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-B Baseline agrees
PullBack Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is beyond 1.0x Volatility of Baseline
Next Candle:
1. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
2. GKD-C Confirmation 1 agrees
3. GKD-C Confirmation 2 agrees
4. GKD-V Volatility/Volume Agrees
]█ Setting up the GKD
The GKD system involves chaining indicators together. These are the steps to set this up.
Use a GKD-C indicator alone on a chart
1. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Simple"
Use a GKD-V indicator alone on a chart
**nothing, it's already useable on the chart without any settings changes
Use a GKD-B indicator alone on a chart
**nothing, it's already useable on the chart without any settings changes
Baseline (Baseline, Backtest)
1. Import the GKD-B Baseline into the GKD-BT Backtest: "Input into Volatility/Volume or Backtest (Baseline testing)"
2. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Baseline"
Volatility/Volume (Volatility/Volume, Backte st)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Solo"
2. Inside the GKD-V indicator, change the "Signal Type" setting to "Crossing" (neither traditional nor both can be backtested)
3. Import the GKD-V indicator into the GKD-BT Backtest: "Input into C1 or Backtest"
4. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Volatility/Volume"
5. Inside the GKD-BT Backtest, a) change the setting "Backtest Type" to "Trading" if using a directional GKD-V indicator; or, b) change the setting "Backtest Type" to "Full" if using a directional or non-directional GKD-V indicator (non-directional GKD-V can only test Longs and Shorts separately)
6. If "Backtest Type" is set to "Full": Inside the GKD-BT Backtest, change the setting "Backtest Side" to "Long" or "Short
7. If "Backtest Type" is set to "Full": To allow the system to open multiple orders at one time so you test all Longs or Shorts, open the GKD-BT Backtest, click the tab "Properties" and then insert a value of something like 10 orders into the "Pyramiding" settings. This will allow 10 orders to be opened at one time which should be enough to catch all possible Longs or Shorts.
Solo Confirmation Simple (Confirmation, Backtest)
1. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Simple"
1. Import the GKD-C indicator into the GKD-BT Backtest: "Input into Backtest"
2. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Solo Confirmation Simple"
Solo Confirmation Complex without Exits (Baseline, Volatility/Volume, Confirmation, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Complex"
4. Import the GKD-V indicator into the GKD-C indicator: "Input into C1 or Backtest"
5. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full wo/ Exits"
6. Import the GKD-C into the GKD-BT Backtest: "Input into Exit or Backtest"
Solo Confirmation Complex with Exits (Baseline, Volatility/Volume, Confirmation, Exit, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Complex"
4. Import the GKD-V indicator into the GKD-C indicator: "Input into C1 or Backtest"
5. Import the GKD-C indicator into the GKD-E indicator: "Input into Exit"
6. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full w/ Exits"
7. Import the GKD-E into the GKD-BT Backtest: "Input into Backtest"
Full GKD without Exits (Baseline, Volatility/Volume, Confirmation 1, Confirmation 2, Continuation, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C 1 indicator, change the "Confirmation Type" setting to "Confirmation 1"
4. Import the GKD-V indicator into the GKD-C 1 indicator: "Input into C1 or Backtest"
5. Inside the GKD-C 2 indicator, change the "Confirmation Type" setting to "Confirmation 2"
6. Import the GKD-C 1 indicator into the GKD-C 2 indicator: "Input into C2"
7. Inside the GKD-C Continuation indicator, change the "Confirmation Type" setting to "Continuation"
8. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full wo/ Exits"
9. Import the GKD-E into the GKD-BT Backtest: "Input into Exit or Backtest"
Full GKD with Exits (Baseline, Volatility/Volume, Confirmation 1, Confirmation 2, Continuation, Exit, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C 1 indicator, change the "Confirmation Type" setting to "Confirmation 1"
4. Import the GKD-V indicator into the GKD-C 1 indicator: "Input into C1 or Backtest"
5. Inside the GKD-C 2 indicator, change the "Confirmation Type" setting to "Confirmation 2"
6. Import the GKD-C 1 indicator into the GKD-C 2 indicator: "Input into C2"
7. Inside the GKD-C Continuation indicator, change the "Confirmation Type" setting to "Continuation"
8. Import the GKD-C Continuation indicator into the GKD-E indicator: "Input into Exit"
9. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full w/ Exits"
10. Import the GKD-E into the GKD-BT Backtest: "Input into Backtest"
Baseline + Volatility/Volume (Baseline, Volatility/Volume, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Baseline + Volatility/Volume"
2. Inside the GKD-V indicator, make sure the "Signal Type" setting is set to "Traditional"
3. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
4. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Baseline + Volatility/Volume"
5. Import the GKD-V into the GKD-BT Backtest: "Input into C1 or Backtest"
6. Inside the GKD-BT Backtest, change the setting "Backtest Type" to "Full". For this backtest, you must test Longs and Shorts separately
7. To allow the system to open multiple orders at one time so you can test all Longs or Shorts, open the GKD-BT Backtest, click the tab "Properties" and then insert a value of something like 10 orders into the "Pyramiding" settings. This will allow 10 orders to be opened at one time which should be enough to catch all possible Longs or Shorts.
█ GKD-C Non-Lag Inverse Fisher Transform of RSX
What is the Inverse Fisher Transform?
The Inverse Fisher Transform (IFT) is a technical analysis indicator developed by John Ehlers, an expert in the field of signal processing and technical analysis. The IFT is designed to convert price data into a Gaussian probability distribution, which makes it easier to identify market turning points and produce clearer trading signals.
The Inverse Fisher Transform is based on the Fisher Transform, which is a mathematical technique used to convert non-Gaussian distributions into Gaussian distributions. The Fisher Transform is particularly useful in financial markets because price data often exhibit non-Gaussian characteristics, such as skewness and kurtosis.
To calculate the Inverse Fisher Transform, follow these steps:
1. Normalize the price data by computing the price relative to a moving average or another relevant indicator, ensuring the data falls within a range of -1 to 1.
2. Apply the Fisher Transform formula to the normalized price data:
Fisher Transform = 0.5 * ln
where ln represents the natural logarithm and X is the normalized price data.
3. Smooth the transformed data using a moving average or another smoothing technique to reduce noise and improve signal clarity.
4. Apply the Inverse Fisher Transform formula to the smoothed Fisher Transform data:
Inverse Fisher Transform = (exp(2 * Y) - 1) / (exp(2 * Y) + 1)
where Y represents the smoothed Fisher Transform data and exp is the exponential function.
The Inverse Fisher Transform indicator generates trading signals based on crossovers. A buy signal occurs when the IFT crosses above a certain threshold, while a sell signal occurs when the IFT crosses below a different threshold. These thresholds can be adjusted to match specific trading styles and market conditions. Traders often use the IFT in conjunction with other technical analysis tools to confirm signals and improve their trading strategies.
What is RSX?
The Jurik RSX ( Relative Strength Index ) is a technical indicator used in financial markets to measure the strength of price movement. It was developed by Mark Jurik and is based on the RSI formula, with the addition of smoothing and other modifications.
The Jurik RSX is designed to be smoother and more responsive than traditional RSI indicators, making it more useful for detecting trends and trading signals. It is also less prone to false signals and noise, which can be a problem with some other technical indicators.
The Jurik RSX can be used in a variety of ways, including as a trend-following indicator or a momentum indicator . It can also be combined with other indicators and trading strategies to improve overall performance.
What is the Non-Lag Moving Average?
The Non-Linear Generalized Moving Average (non-LAGMA) is a type of moving average that aims to provide a smoother and more accurate representation of the underlying data trend than a traditional moving average. It does this by applying weighted coefficients to the data based on its position in the cycle, which helps to reduce the impact of noise and outliers.
Unlike a simple moving average (SMA) or an exponential moving average (EMA), the non-LAGMA takes a more adaptive approach to calculating the average by assigning different weights to the data points in the input window. This weighting system helps to emphasize more recent data points and reduce the lag often associated with traditional moving averages, making it more responsive to changing market conditions.
The non-LAGMA can be used as a trend-following indicator or as a signal generator for trading strategies, similar to other moving averages. Traders may use non-LAGMA in conjunction with other technical analysis tools to confirm signals and improve their trading strategies. It is particularly useful in markets with high levels of noise or when attempting to identify trends in the early stages of their formation.
What is the Non-Lag Inverse Fisher Transform of RSX?
This indicator smooths RSX with a Non-Lag Filter and then injects this output into an Inverse Fisher Transform calculation. This indicator has three types of signals: middle, signal, and levels cross.
Requirements
Inputs
Confirmation 1: GKD-V Volatility / Volume indicator
Confirmation 2: GKD-C Confirmation indicator
Continuation: GKD-C Confirmation indicator
Solo Confirmation Simple: GKD-B Baseline
Solo Confirmation Complex: GKD-V Volatility / Volume indicator
Solo Confirmation Super Complex: GKD-V Volatility / Volume indicator
Stacked 1: None
Stacked 2+: GKD-C, GKD-V, or GKD-B Stacked 1
Outputs
Confirmation 1: GKD-C Confirmation 2 indicator
Confirmation 2: GKD-C Continuation indicator
Continuation: GKD-E Exit indicator
Solo Confirmation Simple: GKD-BT Backtest
Solo Confirmation Complex: GKD-BT Backtest or GKD-E Exit indicator
Solo Confirmation Super Complex: GKD-C Continuation indicator
Stacked 1: GKD-C, GKD-V, or GKD-B Stacked 2+
Stacked 2+: GKD-C, GKD-V, or GKD-B Stacked 2+ or GKD-BT Backtest
Additional features will be added in future releases.
inverse_fisher_transform_adaptive_stochastic█ Description
The indicator is the implementation of inverse fisher transform an indicator transform of the adaptive stochastic (dominant cycle), as in the Cycle Analytics for Trader pg. 198 (John F. Ehlers). Indicator transformation in brief means reshaping the indicator to be more interpretable. The inverse fisher transform is achieved by compressing values near the extremes many extraneous and irrelevant wiggles are removed from the indicator, as cited.
█ Inverse Fisher Transform
input = 2*(adaptive_stoc - .5)
output = e(2*k*input) -1 / e(2*k*input) +1
█ Feature:
iFish i.e. output value
trigger i.e. previous 1 bar of iFish * 0.90
if iFish crosses above the trigger, consider a buy indicated with the green line
while, iFish crosses below the trigger, consider a sell indicate by the red line
in addition iFish needs to be greater than the previous iFish
Fisherized CCIIntroduction
This here is a non-repainting indicator where I use inverse Fisher transformation and smoothing on the well-known CCI (Commdity Channel Index) momentum indicator.
"The Inverse Fisher Transform" describes the calculation and use of the inverse Fisher transform by Dr . Ehlers in 2004. The transform is applied to any indicator with a known probability distribution function. It enables to transform an indicator signal into the range between +1 and -1. This can help to eliminate the noise of an indicator.
The CCI is an momentum indicator which describes the distance of the price to the average price.
For smoothing I used the Hann Window and NET (Noise Elimination Technique) methods.
Additional Features
Divergence Analysis
Trend-adaptive Histogram
Timeframe selection
Usage
It is usually used to spot potential trend reverals or mean-reversion (against the trend) trades on lower timeframes. IMO it can be even used to spot trend-following trades. It always depends on which settings you have, which timeframe do you use and which indicators you combine with it.
The suggested timeframe for this indicator is 15 min (with the length setting on 50).
The histogram with adaptive mode enabled could be used as filter applied on the buy and sell signals.
The divergence analysis can help to spot additional entries/exits or confirm the buy and sell signals.
Always try to find the best settings! This indicators has a lot of customization options you should take advantage of.
Signals
The indicator uses the following logic to generate the buy and sell signals:
Normal
Buy -> When CCI and MA go above the top band (usually +100) and cross
Sell -> When CCI and MA go below the the bottom band (usually -100) and cross
Fisherized
Buy -> When CCI and MA go above the the zero line and cross
Sell -> When CCI and MA go below the the zero line and cross
Have fun with the indicator! I am open for feedback and questions. :)
Non-Lag Inverse Fisher Transform of RSX [Loxx]Non-Lag Inverse Fisher Transform of RSX is an Inverse Fisher Transform on the Non-Lagged Smoothing Filter of Jurik RSX.
What is the Inverse Fisher Transform?
The Inverse Fisher Transform was authored by John Ehlers. The IFT applies some math functions and constants to a moving average of the relative strength index (rsi) of the closing price to calculate its oscillator position. T
read more here: www.mesasoftware.com
What is RSX?
RSI is a very popular technical indicator, because it takes into consideration market speed, direction and trend uniformity. However, the its widely criticized drawback is its noisy (jittery) appearance. The Jurk RSX retains all the useful features of RSI , but with one important exception: the noise is gone with no added lag.
What is the Non-lag moving average?
The Non Lag Moving average follows price closely and gives very quick signals as well as early signals of price change. As a standalone Moving Average, it should not be used on its own, but as an additional confluence tool for early signals.
Included:
Alerts
Signals
Bar coloring
Chimpanzee V2.5 part A by joylay83Hi everyone, I am an amateur pinecoder. I would like to share my script which is coded with the intention of generating signals to send to 3commas webhook. It is still in development and revision.
This collection of indicators use:
Chart: 15m.
Inverse Fisher Transformation of the RSI to detect dips in the 15m timeframe.
Bollinger band (4H) to filter out false signals.
Triple EMA 21: to mimic price action for easier coding alerts. Currently not involved in generating signals. will be incorporated in the future.
StochRSI: As a visual filter. Currently not involved in generating signals. will be incorporated in the future.
Background will be green if stochRSI is low and red if stockRSI is high.
Candlesticks will be marked with a flag is TEMA breached BB.
One would need to play around with timeframes, BB settings and IFTRSI threshold for different signals.
There are 2 Signal Modes (with regards to IFTRSI):
Threshold: When price action falls below BB and IFTRSI hits buy threshold, a buy/sell signal is generated. Eg if IFTRSI buy threshold is set to -0.9, the buy signal will remain continuously positive as long as IFTRSI is < 0.9.
Cross: When price action falls below BB and IFTRSI hits threshold, nothing happens. It will wait until the IFTRSI cross back over the threshold before firing a signal.
There is another identical set of indicators running on a higher time frame (IFTRSI: 4H, BB: D or 3D, TEMA 21 4H) but on the same chart. This tend to generate less signals but are more reliable. A usage example would be to send a larger buy order if the signal comes from this higher time frame, or execute a sell order after multiple buys from the lower time frame.
It comes in 2 parts:
Part A: Contains overlay display. This displays BB, Triple EMA, buy/sell and StochRSI in labels. the labels are self explanatory.
Part B (please search for it): which is actually the same code but contain non-overlay display. You may also put part B overlay=true but scale to LEFT. The advantage of using overlay=true is that you can move the signal right over the candlesticks (mainly for troubleshooting/debugging). This part contains Inverse Fisher RSI, %B, Signal Line. %B is supposedly idential to Bollinger Bands in Part A.
By default, when there is a buy/sell signal:
lower time frame 15m: Signal Line in Part B will turn blue with a value 1 or -1 which corresponds to a buy or sell label in Part A
higher time frame 4H: Signal Line in Part B will turn red with a value 2 or -2 which corresponds to a HTF buy or sell label in Part A
Part A or B may be used to send signal to the webhook. You have to make sure that the settings of Part A and B are identical.
You may choose to un-display some items to reduce clutter.
Current problems:
1. Still too many buy signals
Although many times it will generate excellent buy signal at many swing lows, but there are many buy signals prior to a major swing low. This can be observed in the picture above. It also generate a couple of buy signals prior to the swing lows. I am currently experimenting with 20m and hourly timeframe to address this issue. More filters are needed eg an oscillator or detecting candlestick patterns.
2. Premature sell signals.
The sell signal is often generated at the beginning of a major bull run. My idea to solve this problem is to move to a higher timeframe and sell only when TEMA crossunder the upper bollinger band.
3. Lack of a backtester that can test multiple concurrent deals.
Buy -> Buy (average down) -> Buy (average down) -> Buy (average down) -> Sell
4. Lack of the ability to calculate average purchase price
Probably have to code it as a strategy
5. Display lag
As the browser is running 2 copies of the idential script, it tends to lag when you drag your chart around. So far there are no timeouts or delay in firing alerts to 3commas.
I do welcome any suggestion for improvement and constructive criticism. tqvm.
Credits : Thank you for doing an awesome job. I learnt a lot from your codes and tutorials.
Credits not listed in any order. If your code is used here and did not receive due credit, kindly drop me a note. tq.
Blessing 3 by JTA Today
@ZenAndTheArtOfTrading (extremely-easy-to-understand tutorials eg fixing repainting)
@LazyBear (various codes)
@Galactus-B Argo I
@TheTradingParrot (Inverse Fisher RSI and Gavin's backtester)
@zendog123 (backtester and various codes)
@ydeniz2000 (Bollinger Bands)
TradingView built-in scripts
Inverse Fisher Transform ScreenerThis is a Screener for Inverse Fisher Transform on multiple oscillators
This tool is intended to aid you to visually analyse reasonable buy and sell IFT-signal thresholds across multiple tokens and different sources. It will help you speed up the tedious and manual work of trying out different IFT-settings when you're able to review the chart visually to find which values are present the most often and the location of that signal on the chart.
What does it bring to the table, why is it useful?
- Invese Fisher Transform on multiple oscillators such as RSI, MFI, CCI, Stochastic
- Combine multiple sources into one signal, select how it's calculated
- Visually review the chart for good IFT-settings
- 4 dynamic buy labels with different thresholds
- 4 dynamic sell labels with different thresholds
- Buy and sell on signal reversal
- Create your own trade alerts for automation
- Backtester compatible (plots 1 and 2 for buy and sell signals)
- A dynamic table counting amount of signals for each setting
- The labels are automatically updated when you change the values in the settings
How to use?
1. Change signal source and method
2. Change buy and sell thresholds
3. Show/hide additional labels
4. Review chart
5. Change trade settings
6. Backtest
7. Create alerts
Description
With this indicator you're able to visually review the signal strength of one or multiple oscillators processed with Inverse Fisher Transform ( IFT ), combine them and choose the method of calculation when they are combined. This produces a signal which strongly fluctuates between -1 and +1 instead of the more common 0-100 most oscillators uses. The intention is to make the decision making clearer and easier when you decide when to enter or exit a trade. This aims to help you remove the feelings from your trading.
Inverse Fisher Transform was first presented by John Ehlers in Stocks & Commodities V. 22:5 where he proposes to process RSI with the formula for hyperbolic tangent, tanh (x). This transforms the oscillator into a smoother and more compressed version with quicker oscillations.
Inverse Fisher Transform on Williams %RInverse Fisher Transform On Williams %R
Since Williams R indicator produces negative values, I preferred to add 50 instead of subtracting 50.
It produces values between 0.5 and -0.5.
Generates clear buy and sell signals.
Williams %R determines overbought and oversold levels.
You can see more softly.
VictoriaThis indicator visualises different oscillators processed through Inverse Fisher Transform
What is included:
Inverse Fisher Transform on different oscillators
You can combine multiple oscillators into one
The combination of sources can be calculated in different ways
Set different buy and sell signal thresholds
View selected thresholds in the chart
Use TradingView Technicals Buy and Sell signals to dynamically change threshold values
Convert signal to alerts
Multiple filters to allow or block signals
Backtest compatible
Alerts compatible
Two different chart modes:
You can view multiple oscillators in the same chart
You can view trade signals/alerts on the chart from the thresholds you have selected
Description:
With this indicator you're able to visually review the signal strength of one or multiple oscillators processed with Inverse Fisher Transform (IFT), combine them and choose the method of calculation when they are combined. This produces a signal which strongly fluctuates between -1 and +1 instead of the more common 0-100 most oscillators uses. The intention is to make the decision making clearer and easier when you decide when to enter or exit a trade. This aims to help you remove the feelings from your trading.
Inverse Fisher Transform was first presented by John Ehlers in Stocks & Commodities V. 22:5 where he proposes to process RSI with the formula for hyperbolic tangent, tanh(x). This transforms the oscillator into a smoother and more compressed version with quicker oscillations.
Within a bull or bear period of the traded asset the signal have different strengths. To harness this to our advantage we use the combined strength of the TradingView Technical indicator which gives us a Buy, Strong Buy, Sell or a Strong Sell on the selected timeframe and asset. This makes it possible to delay the buy in bearish conditions to only trigger when it is really oversold and also allow the signal be more relaxed and exit the trade sooner. While on the other hand if the condition is bullish the buy signal is relaxed and the sell requires a stronger signal. All of this is possible to change in the indicator to fine tune the settings for the specific asset and timeframe selected. We also have the possibility of blocking the buy signals with different filters.
[GJ]IFRSITHE INVERSE FISHER TRANSFORM STOCH RSI
HOW IT WORKS
This indicator uses the inverse fisher transform on the stoch RSI for clear buying and selling signals. The stoch rsi is used to limit it in the range of 0 and 100. We subtract 50 from this to get it into the range of -50 to +50 and multiply by .1 to get it in the range of -5 to +5. We then use the 9 period weighted MA to remove some "random" trade signals before we finally use the inverse fisher transform to get the output between -1 and +1
HOW TO USE
Buy when the indicator crosses over –0.5 or crosses over +0.5 if it has not previously crossed over –0.5.
Sell when the indicator crosses under +0.5 or crosses under –0.5 if it has not previously crossed under +0.5.
We can see multiple examples of good buy and sell signals from this indicator on the attached chart for QCOM. Let me know if you have any suggestions or thoughts!
[blackcat] L2 Ehlers Inverse Fisher Cyber CycleLevel: 2
Background
John F. Ehlers introuced the Inverse Fisher Transform of Cyber Cycle in May, 2004.
Function
"The Inverse Fisher Transform ," describes the calculation and use of the inverse Fisher transform by Dr . Ehlers in 2004. The transform is applied to any indicator with a known probability distribution function, but this script offers a sample transforms: Cyber Cycle . I have created inputs for the trigger levels for entry and exit so that the user may adjust these levels as desired.
In his article, Dr . Ehlers states the inverse Fisher transform can work with any oscillator, and that values between -1 and 1 are more suited for the transform calculations. Here is one version of the inverse Fisher transform of Cyber Cycle . This version takes the highest and lowest value of the Cyber Cycle and normalizes the scale to a range of -1 to 1. John Ehlers shows how to use the inverse Fisher transform ( IFT ) to compress oscillator-type indicators to give clear trading indications of when to buy or sell. The IFT is a nonlinear transformation that changes the probability distribution, so for example, unbounded indicators can be transformed into bounded indicators with a high probability of being either +1 or -1.
Key Signal
ICycle--> Inverse Fisher Transform of Cyber Cycle fast line
Trigger--> Inverse Fisher Transform of Cyber Cycle slow line
Pros and Cons
100% John F. Ehlers definition translation, even variable names are the same. This help readers who would like to use pine to read his book.
Remarks
The 69th script for Blackcat1402 John F. Ehlers Week publication.
Readme
In real life, I am a prolific inventor. I have successfully applied for more than 60 international and regional patents in the past 12 years. But in the past two years or so, I have tried to transfer my creativity to the development of trading strategies. Tradingview is the ideal platform for me. I am selecting and contributing some of the hundreds of scripts to publish in Tradingview community. Welcome everyone to interact with me to discuss these interesting pine scripts.
The scripts posted are categorized into 5 levels according to my efforts or manhours put into these works.
Level 1 : interesting script snippets or distinctive improvement from classic indicators or strategy. Level 1 scripts can usually appear in more complex indicators as a function module or element.
Level 2 : composite indicator/strategy. By selecting or combining several independent or dependent functions or sub indicators in proper way, the composite script exhibits a resonance phenomenon which can filter out noise or fake trading signal to enhance trading confidence level.
Level 3 : comprehensive indicator/strategy. They are simple trading systems based on my strategies. They are commonly containing several or all of entry signal, close signal, stop loss, take profit, re-entry, risk management, and position sizing techniques. Even some interesting fundamental and mass psychological aspects are incorporated.
Level 4 : script snippets or functions that do not disclose source code. Interesting element that can reveal market laws and work as raw material for indicators and strategies. If you find Level 1~2 scripts are helpful, Level 4 is a private version that took me far more efforts to develop.
Level 5 : indicator/strategy that do not disclose source code. private version of Level 3 script with my accumulated script processing skills or a large number of custom functions. I had a private function library built in past two years. Level 5 scripts use many of them to achieve private trading strategy.
[blackcat] L2 Ehlers Inverse Fisher RSILevel: 2
Background
John F. Ehlers introuced the Inverse Fisher Transform of RSI in May, 2004.
Function
"The Inverse Fisher Transform," describes the calculation and use of the inverse Fisher transform by Dr. Ehlers in 2004. The transform is applied to any indicator with a known probability distribution function, but this script offers a sample transforms: RSI. I have created inputs for the trigger levels for entry and exit so that the user may adjust these levels as desired.
In his article, Dr. Ehlers states the inverse Fisher transform can work with any oscillator, and that values between -1 and 1 are more suited for the transform calculations. Here is one version of the inverse Fisher transform of RSI. This version takes the highest and lowest value of the RSI and normalizes the scale to a range of -1 to 1. John Ehlers shows how to use the inverse Fisher transform (IFT) to compress oscillator-type indicators to give clear trading indications of when to buy or sell. The IFT is a nonlinear transformation that changes the probability distribution, so for example, unbounded indicators can be transformed into bounded indicators with a high probability of being either +1 or -1.
Key Signal
IFish--> Ehlers Inverse Fisher RSI fast line
Trigger--> Ehlers Inverse Fisher RSI slow line
Pros and Cons
100% John F. Ehlers definition translation, even variable names are the same. This help readers who would like to use pine to read his book.
Remarks
The 68th script for Blackcat1402 John F. Ehlers Week publication.
Readme
In real life, I am a prolific inventor. I have successfully applied for more than 60 international and regional patents in the past 12 years. But in the past two years or so, I have tried to transfer my creativity to the development of trading strategies. Tradingview is the ideal platform for me. I am selecting and contributing some of the hundreds of scripts to publish in Tradingview community. Welcome everyone to interact with me to discuss these interesting pine scripts.
The scripts posted are categorized into 5 levels according to my efforts or manhours put into these works.
Level 1 : interesting script snippets or distinctive improvement from classic indicators or strategy. Level 1 scripts can usually appear in more complex indicators as a function module or element.
Level 2 : composite indicator/strategy. By selecting or combining several independent or dependent functions or sub indicators in proper way, the composite script exhibits a resonance phenomenon which can filter out noise or fake trading signal to enhance trading confidence level.
Level 3 : comprehensive indicator/strategy. They are simple trading systems based on my strategies. They are commonly containing several or all of entry signal, close signal, stop loss, take profit, re-entry, risk management, and position sizing techniques. Even some interesting fundamental and mass psychological aspects are incorporated.
Level 4 : script snippets or functions that do not disclose source code. Interesting element that can reveal market laws and work as raw material for indicators and strategies. If you find Level 1~2 scripts are helpful, Level 4 is a private version that took me far more efforts to develop.
Level 5 : indicator/strategy that do not disclose source code. private version of Level 3 script with my accumulated script processing skills or a large number of custom functions. I had a private function library built in past two years. Level 5 scripts use many of them to achieve private trading strategy.
Inverse Fisher Transform of NWMA Aroon Oscillator As originally described by Manfred G. Dürschner. Applies an inverse fisher transform to an aroon oscillator calculated using smoothed price. Smoothing is done via NWMA or "Moving Average 3.0".
Signals are Buy > 0 and Sell < 0
length 1 must be at least twice length 2 (lambda >= 2.0)
Profit Accumulator Heat MapHeat Map Indicator
This is a support indicator to the Main Indicator which has also been published.
This is a list of a number of indicators which cover trend, momentum and volatility. The key is very simple for this indicator, green is a long trade, red is a short trade and grey is an indicator which may be transitioning. The indicators uses are: MACD, PSAR, Bollinger Bands, RSI, Momentum and Chandelier Exit. All of the settings are customisable within the indicator and the user can best fit these around their charts. The simplicity of the heat map is that the more of one colour there is, the more likely it is that a trade can be placed.
I've been using this successfully on the one hour FX charts, but seems to work equally as well on higher or lower time frames (not less than 15min).
The other indicators which are part of the suite are shown on the website which is highlighted in my signature at the bottom of the page. Purchase of the main indicator gives access to the full suite of eight indicators. I use the other indicators to confirm the direction of the trade and to determine if I want to trade or not. I use it along with the 2min, 15min and 4hr timeframes to identify the best entry window and how long I'm likely to be in the trade.
Support can be provided via private message or in the comments below.
The links are provided below for access to the indicator.
Inverse Fisher Transform of SMI and sto. RSI, MTF confirmedThe system uses 1 hour and 15 min timeframe data. Signals coming from 15 min Inverse Fisher Transform of SMI and stochastic RSI are confirmed by 1 hour Inverse Fisher Transform SMI, according to the following rules:
long cond.: 15 min IFTSMI crosses ABOVE -0.5 or SRSI k-line crosses ABOVE 50 while 1-hour IFTSMI is already ABOVE -0.5
short cond.:15 min IFTSMI crosses BELOW 0.5 or SRSI k-line crosses BELOW 50 while 1-hour IFTSMI is already BELOW 0.5
SMI and Inverse Fisher Transform of SMI codes belong to @kivancozbilgic.
Hancock - IFT RSI T3MAThis is a version of the Inverse Fisher Transform Relative Strength Index with T3MA smoothing and histogram difference based on EMA signal line.
Configurable parameters:
RSI length - This is the period used for the RSI .
RSI Smooth Length - This is the smoothing period of the Weighted Moving Average used for the smoothing in Inverse Fisher Transform .
RSI Signal - This is the period used for EMA signal line.
RSI Overbought - Configures the overbought threshold (0.5 default).
RSI Oversold - Configures the oversold threshold (-0.5 default).
T3 Smoothing - Enabling this applies T3MA smoothing to the RSI .
T3 Length - This is the period used for the T3MA smoothing of the RSI .
T3 Factor - This is the factor used for the T3MA smoothing of the RSI .
I've added a histogram plotting the difference between the signal line and RSI to make it easier to make trades. Oversold and Overbought thresholds are indicated by the red and green horizontal lines. Signal line is coloured for trade direction.
Happy trading folks!
Hancock
Hancock - Floating O/B O/S IFT RSI T3MAThis is a version of the Inverse Fisher Transform Relative Strength Index with floating oversold and overbought thresholds.
Configurable parameters:
RSI length - This is the period used for the RSI .
RSI Smooth Length - This is the smoothing period of the Weighted Moving Average used for the smoothing in Inverse Fisher Transform .
RSI Threshold Period - This is the period used for calculating the floating oversold and overbought thresholds.
RSI Overbought - Configures the overbought threshold (80% default).
RSI Oversold - Configures the oversold threshold (20% default).
T3 Smoothing - Enabling this applies T3MA smoothing to the RSI.
T3 Length - This is the period used for the T3MA smoothing of the RSI.
T3 Factor - This is the factor used for the T3MA smoothing of the RSI.
RSI line breaching the thresholds are clearly indicated by filled chart plots.
An inverse Fisher transform of RSI is designed to enhance the extremes (overbought and oversold zones), in combination with floating thresholds this version allows faster and cleaner trend detection and identification. With additional smoothing, false signals can be avoided. As with any other indicator some experimenting with parameters is advised (in order to find optimal settings for symbol/time frame pair).
Happy trading folks!
Hancock
Fisher Least Squares Moving AverageIntroduction
I already estimated the least-squares moving average numerous times, one of the most elegant ways was by rescaling a linear function to the price by using the z-score, today i will propose a new smoother (FLSMA) based on the line rescaling approach and the inverse fisher transform of a scaled moving average error with the goal to provide an alternative least-squares smoother, the indicator won't use the correlation coefficient and will try to adresses problems such as overshoots and lag reduction.
Line Rescaling Method
For those who did not see my least squares moving average estimation using the line rescaling method here is a resume, we want to fit a polynomial function of degree 1 to the price by reducing the sum of squares between the price and the filter, squares is a term meaning the squared difference between the price and its estimation. The line rescaling technique work as follow :
1 - get the z-score of a line.
2 - multiply this z-score with the correlation between the price and a line.
3 - multiply the precedent result with the standard deviation of the price, then sum that to a simple moving average.
This process is shorter than the classical least-squares moving average method.
Z-Score Derivation And The Inverse Fisher Transform
The FLSMA will use a similar approach to the line rescaling technique but instead of using the correlation during step 2 we will use an alternative calculated from the error between the estimate and the price.
In order to do so we must use the inverse fisher transform, the inverse fisher transform can take a z-score and scale it in a range of (1,-1), it is possible to estimate the correlation with it. First lets create our modified z-score in the form of : Z = ma((y - Y)/e) where y is the price, Y our output estimate and e the moving average absolute error between the price and Y and lets call it scaled smoothed error , then apply the inverse fisher transform : r = IFT(Z) = tanh(Z) , we then multiply the z-score of the line with it.
Performance
The FLSMA greatly reduce the overshoots, this mean that the maximas of abs(r) are lower than the maxima's of the absolute correlation, such case is not "bad" but we can see that the filter is not closer to the price than the LSMA during trending periods, we can assume the filter don't reduce least-squares as well as the LSMA.
The image above is the running mean of the absolute error of each the FLSMA (in red) and the LSMA (in blue), we could fix this problem by multiplying the smooth scaled error by p where p can be any number, for example :
z = sma(src - nz(b ,src),length)/e * p where p = 2
In red the FLSMA and in blue the FLSMA with p = 2 , the greater p is the less lag the FLSMA will have.
Conclusion
It could be possible to get better results than the LSMA with such design, the presented indicator use its own correlation replacement but it is possible to use anything in a range of (1,-1) to multiply the line z-score. Although the proposed filter only reduce overshoots without keeping the accuracy of the LSMA i believe the code can be useful for others.
Thanks for reading.
Inverse Fisher Fast Z-scoreIntroduction
The fast z-score is a modification of the classic z-score that allow for smoother and faster results by using two least squares moving averages, however oscillators of this kind can be hard to read and modifying its shape to allow a better interpretation can be an interesting thing to do.
The Indicator
I already talked about the fisher transform, this statistical transform is originally applied to the correlation coefficient, the normal transform allow to get a result similar to a smooth z-score if applied to the correlation coefficient, the inverse transform allow to take the z-score and rescale it in a range of (1,-1), therefore the inverse fisher transform of the fast z-score can rescale it in a range of (1,-1).
inverse = (exp(k*fz) - 1)/(exp(k*fz) + 1)
Here k will control the squareness of the output, an higher k will return heavy side step shapes while a lower k will preserve the smoothness of the output.
Conclusion
The fisher transform sure is useful to kinda filter visual information, it also allow to draw levels since the rescaling is in a specific range, i encourage you to use it.
Notes
During those almost 2 weeks i was even lazier and sadder than ever before, so i think its no use to leave, i also have papers to publish and i need tv for that.
Thanks for reading !
Inverse Fisher Z-Score Introduction
The inverse fisher transform or hyperbolic tangent function is a type os sigmoid function (sometime called squashing function) , those types of functions can rescale a result in a certain range and are widely used in artificial intelligence. More in depth the fisher transform can make the correlation coefficient of a time series normally distributed, in practice if you apply the fisher transform to the correlation coefficient between a time series and a linear function you will end up with an estimate of the z-score of the time series. The inverse transform however can do the contrary, it can take the z-score and transform it into a rough estimate of the correlation coefficient, if your z-score is not smooth then you will have a non-smooth estimate of the correlation coefficient, that's quite nice no ?
The Indicator
The inverse fisher transform of the z-score will produce results in a range of 1/-1, here however i will rescale in a range of 100/0 because its a standard range for oscillators in technical analysis. Values over 80 indicate an overbought market, under 20 an oversold market. The smooth option in the indicator settings will make the indicator use a linearly weighted moving average as input thus resulting in a smoother result.
The indicator with smooth option.
Conclusion
I presented a new oscillator indicator who use the inverse fisher transform of a z-score. Using the fisher transform and its inverse can give a new shape to your indicator, make sure to control the scale of your indicator before applying the fisher transform, the inverse transform should be applied to values in range of 1/-1 but you can use higher limits (2/-2,3/-3...) , however remember that higher limits will approximate an heavy side step function (square shape) . I hope you will find an use to this indicator.
Thanks for reading !
rsiD new form RSI This indicator is based on inverse fisher rsi with some modification
so in this way we can create RSI that if cross the zero its bullish and fall bellow zero is bearish.
Also in this way it easy to create more accurate signal based on the RSI
I set it on 14 length , if you want it more active set it on 5
Inverse Fisher RSI-MTF2 alertsThis is the study with allerts of the RSI-MTF2
if there is repainting then I suggest to go to lower time frame and graph of 1 hour or half hour then it will not repaint. the issue i think exist only in 24 hours time frame when you build it on shorter graph
still the results will be great (test it in strategy that i put before this one)
have fun
