GKD-C XMA Histogram [Loxx]The Giga Kaleidoscope GKD-C XMA Histogram is a Confirmation module included in Loxx's "Giga Kaleidoscope Modularized Trading System."
█ GKD-C XMA Histogram
The "XMA Histogram" utilizes a dynamic approach to analyze market trends through various types of moving averages, including Exponential Moving Average (EMA), Fast Exponential Moving Average (FEMA), Linear Weighted Moving Average (LWMA), Simple Moving Average (SMA), and Smoothed Moving Average (SMMA). This flexibility allows traders to select the moving average that best fits their trading style and market conditions. The indicator calculates the selected moving average over a specified period for a given price source, then examines the difference between the current and previous values of this moving average.
A threshold, adjusted for market precision, determines significant changes. If the change in the moving average exceeds this threshold, it signals potential market momentum. The histogram visualizes this momentum, marking upward momentum with green and downward momentum with red. The XMA Histogram is designed to signal potential entry and exit points, identifying when the price crosses the moving average in a way that suggests a strong trend. This tool is particularly useful for traders looking to capitalize on trends by providing a clear, visual representation of market momentum and direction shifts.
█ Giga Kaleidoscope Modularized Trading System
Core components of an NNFX algorithmic trading strategy
The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend
3. Confirmation 1 - a technical indicator used to identify trends
4. Confirmation 2 - a technical indicator used to identify trends
5. Continuation - a technical indicator used to identify trends
6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown
7. Exit - a technical indicator used to determine when a trend is exhausted
8. Metamorphosis - a technical indicator that produces a compound signal from the combination of other GKD indicators*
*(not part of the NNFX algorithm)
What is Volatility in the NNFX trading system?
In the NNFX (No Nonsense Forex) trading system, ATR (Average True Range) is typically used to measure the volatility of an asset. It is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. ATR is calculated by taking the average of the true range values over a specified period.
True range is calculated as the maximum of the following values:
-Current high minus the current low
-Absolute value of the current high minus the previous close
-Absolute value of the current low minus the previous close
ATR is a dynamic indicator that changes with changes in volatility. As volatility increases, the value of ATR increases, and as volatility decreases, the value of ATR decreases. By using ATR in NNFX system, traders can adjust their stop loss and take profit levels according to the volatility of the asset being traded. This helps to ensure that the trade is given enough room to move, while also minimizing potential losses.
Other types of volatility include True Range Double (TRD), Close-to-Close, and Garman-Klass
What is a Baseline indicator?
The baseline is essentially a moving average, and is used to determine the overall direction of the market.
The baseline in the NNFX system is used to filter out trades that are not in line with the long-term trend of the market. The baseline is plotted on the chart along with other indicators, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR).
Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards, only long trades are taken, and if the baseline is sloping downwards, only short trades are taken. This approach helps to ensure that trades are in line with the overall trend of the market, and reduces the risk of entering trades that are likely to fail.
By using a baseline in the NNFX system, traders can have a clear reference point for determining the overall trend of the market, and can make more informed trading decisions. The baseline helps to filter out noise and false signals, and ensures that trades are taken in the direction of the long-term trend.
What is a Confirmation indicator?
Confirmation indicators are technical indicators that are used to confirm the signals generated by primary indicators. Primary indicators are the core indicators used in the NNFX system, such as the Average True Range (ATR), the Moving Average (MA), and the Relative Strength Index (RSI).
The purpose of the confirmation indicators is to reduce false signals and improve the accuracy of the trading system. They are designed to confirm the signals generated by the primary indicators by providing additional information about the strength and direction of the trend.
Some examples of confirmation indicators that may be used in the NNFX system include the Bollinger Bands, the MACD (Moving Average Convergence Divergence), and the MACD Oscillator. These indicators can provide information about the volatility, momentum, and trend strength of the market, and can be used to confirm the signals generated by the primary indicators.
In the NNFX system, confirmation indicators are used in combination with primary indicators and other filters to create a trading system that is robust and reliable. By using multiple indicators to confirm trading signals, the system aims to reduce the risk of false signals and improve the overall profitability of the trades.
What is a Continuation indicator?
In the NNFX (No Nonsense Forex) trading system, a continuation indicator is a technical indicator that is used to confirm a current trend and predict that the trend is likely to continue in the same direction. A continuation indicator is typically used in conjunction with other indicators in the system, such as a baseline indicator, to provide a comprehensive trading strategy.
What is a Volatility/Volume indicator?
Volume indicators, such as the On Balance Volume (OBV), the Chaikin Money Flow (CMF), or the Volume Price Trend (VPT), are used to measure the amount of buying and selling activity in a market. They are based on the trading volume of the market, and can provide information about the strength of the trend. In the NNFX system, volume indicators are used to confirm trading signals generated by the Moving Average and the Relative Strength Index. Volatility indicators include Average Direction Index, Waddah Attar, and Volatility Ratio. In the NNFX trading system, volatility is a proxy for volume and vice versa.
By using volume indicators as confirmation tools, the NNFX trading system aims to reduce the risk of false signals and improve the overall profitability of trades. These indicators can provide additional information about the market that is not captured by the primary indicators, and can help traders to make more informed trading decisions. In addition, volume indicators can be used to identify potential changes in market trends and to confirm the strength of price movements.
What is an Exit indicator?
The exit indicator is used in conjunction with other indicators in the system, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR), to provide a comprehensive trading strategy.
The exit indicator in the NNFX system can be any technical indicator that is deemed effective at identifying optimal exit points. Examples of exit indicators that are commonly used include the Parabolic SAR, and the Average Directional Index (ADX).
The purpose of the exit indicator is to identify when a trend is likely to reverse or when the market conditions have changed, signaling the need to exit a trade. By using an exit indicator, traders can manage their risk and prevent significant losses.
In the NNFX system, the exit indicator is used in conjunction with a stop loss and a take profit order to maximize profits and minimize losses. The stop loss order is used to limit the amount of loss that can be incurred if the trade goes against the trader, while the take profit order is used to lock in profits when the trade is moving in the trader's favor.
Overall, the use of an exit indicator in the NNFX trading system is an important component of a comprehensive trading strategy. It allows traders to manage their risk effectively and improve the profitability of their trades by exiting at the right time.
What is an Metamorphosis indicator?
The concept of a metamorphosis indicator involves the integration of two or more GKD indicators to generate a compound signal. This is achieved by evaluating the accuracy of each indicator and selecting the signal from the indicator with the highest accuracy. As an illustration, let's consider a scenario where we calculate the accuracy of 10 indicators and choose the signal from the indicator that demonstrates the highest accuracy.
The resulting output from the metamorphosis indicator can then be utilized in a GKD-BT backtest by occupying a slot that aligns with the purpose of the metamorphosis indicator. The slot can be a GKD-B, GKD-C, or GKD-E slot, depending on the specific requirements and objectives of the indicator. This allows for seamless integration and utilization of the compound signal within the GKD-BT framework.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v2.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
6. GKD-M - Metamorphosis module (Metamorphosis, Number 8 in the NNFX algorithm, but not part of the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data to A backtest module wherein the various components of the GKD system are combined to create a trading signal.
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Multi-Ticker CC Backtest
Baseline: Hull Moving Average
Volatility/Volume: Hurst Exponent
Confirmation 1: Advance Trend Pressure as shown on the chart above
Confirmation 2: uf2018
Continuation: Coppock Curve
Exit: Rex Oscillator
Metamorphosis: Baseline Optimizer
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, GKD-M, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD system.
█ Giga Kaleidoscope Modularized Trading System Signals
Standard Entry
1. GKD-C Confirmation gives signal
2. Baseline agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Volatility/Volume agrees
1-Candle Standard Entry
1a. GKD-C Confirmation gives signal
2a. Baseline agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
Next Candle
1b. Price retraced
2b. Baseline agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Baseline Entry
1. GKD-B Baseline gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Volatility/Volume agrees
7. Confirmation 1 signal was less than 'Maximum Allowable PSBC Bars Back' prior
1-Candle Baseline Entry
1a. GKD-B Baseline gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSBC Bars Back' prior
Next Candle
1b. Price retraced
2b. Baseline agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Volatility/Volume Entry
1. GKD-V Volatility/Volume gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Baseline agrees
7. Confirmation 1 signal was less than 7 candles prior
1-Candle Volatility/Volume Entry
1a. GKD-V Volatility/Volume gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSVVC Bars Back' prior
Next Candle
1b. Price retraced
2b. Volatility/Volume agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Baseline agrees
Confirmation 2 Entry
1. GKD-C Confirmation 2 gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Volatility/Volume agrees
6. Baseline agrees
7. Confirmation 1 signal was less than 7 candles prior
1-Candle Confirmation 2 Entry
1a. GKD-C Confirmation 2 gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSC2C Bars Back' prior
Next Candle
1b. Price retraced
2b. Confirmation 2 agrees
3b. Confirmation 1 agrees
4b. Volatility/Volume agrees
5b. Baseline agrees
PullBack Entry
1a. GKD-B Baseline gives signal
2a. Confirmation 1 agrees
3a. Price is beyond 1.0x Volatility of Baseline
Next Candle
1b. Price inside Goldie Locks Zone Minimum
2b. Price inside Goldie Locks Zone Maximum
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Continuation Entry
1. Standard Entry, 1-Candle Standard Entry, Baseline Entry, 1-Candle Baseline Entry, Volatility/Volume Entry, 1-Candle Volatility/Volume Entry, Confirmation 2 Entry, 1-Candle Confirmation 2 Entry, or Pullback entry triggered previously
2. Baseline hasn't crossed since entry signal trigger
4. Confirmation 1 agrees
5. Baseline agrees
6. Confirmation 2 agrees
Скользящие средние
LSMA Z-Score [BackQuant]LSMA Z-Score
Main Features and Use in the Trading Strategy
- The indicator normalizes the LSMA into a detrended Z-Score, creating an oscillator with standard deviation levels to indicate trend strength.
- Adaptive coloring highlights the rate of change and potential reversals, with different colors for positive and negative changes above and below the midline.
- Extreme levels with adaptive coloring indicate the probability of a reversion, providing strategic entry or exit points.
- Alert conditions for crossing the midline or significant shifts in trend direction enhance its utility within a trading strategy.
1. What is an LSMA?
The Least Squares Moving Average (LSMA) is a technical indicator that smoothens price data to help identify trends. It uses the least squares regression method to fit a straight line through the selected price points over a specified period. This approach minimizes the sum of the squares of the distances between the line and the price points, providing a more statistically grounded moving average that can adapt more smoothly to price changes.
2. What is a Z-Score?
A Z-Score is a statistical measurement that describes a value's relationship to the mean of a group of values, measured in terms of standard deviations from the mean. If a Z-Score is 0, it indicates that the data point's score is identical to the mean score. A Z-Score helps in understanding if a data point is typical for a given data set or if it is atypical. In finance, a Z-Score is often used to measure how far a piece of data is from the average of a set, which can be helpful in identifying outliers or unusual data points.
3. Why Turning LSMA into a Z-Score is Innovative and Its Benefits
Converting LSMA into a Z-Score is innovative because it combines the trend identification capabilities of the LSMA with the statistical significance testing of Z-Scores. This transformation normalizes the LSMA, creating a detrended oscillator that oscillates around a mean (zero line), with standard deviation levels to show trend strength. This method offers several benefits:
Enhanced Trend Detection:
- By normalizing the LSMA, traders can more easily identify when the price is deviating significantly from its trend, which can signal potential trading opportunities.
Standardization:
- The Z-Score transformation allows for comparisons across different assets or time frames, as the score is standardized.
Objective Measurement of Trend Strength:
- The use of standard deviation levels provides an objective measure of trend strength and volatility.
4. How It Can Be Used in the Context of a Trading System
This indicator can serve as a versatile tool within a trading system for a range of things:
Trend Confirmation:
- A positive Z-Score can confirm an uptrend, while a negative Z-Score can confirm a downtrend, providing traders with signals to enter or exit trades.
Oversold/Overbought Conditions:
- Extreme Z-Score levels can indicate overbought or oversold conditions, suggesting potential reversals or pullbacks.
Volatility Assessment:
- The standard deviation levels can help traders assess market volatility, with wider bands indicating higher volatility.
5. How It Can Be Used for Trend Following
For trend following strategies, this indicator can be particularly useful:
Trend Strength Indicator:
- By monitoring the Z-Score's distance from zero, traders can gauge the strength of the current trend, with larger absolute values indicating stronger trends.
Directional Bias:
- Positive Z-Scores can be used to establish a bullish bias, while negative Z-Scores can establish a bearish bias, guiding trend following entries and exits.
Color-Coding for Trend Changes :
- The adaptive coloring of the indicator based on the rate of change and extreme levels provides visual cues for potential trend reversals or continuations.
Thus following all of the key points here are some sample backtests on the 1D Chart
Disclaimer: Backtests are based off past results, and are not indicative of the future.
This is using the Midline Crossover:
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
GKD-C Hodrick-Prescott Filter [Loxx]The Giga Kaleidoscope GKD-C Hodrick-Prescott Filter is a Confirmation module included in Loxx's "Giga Kaleidoscope Modularized Trading System."
█ GKD-C Hodrick-Prescott Filter
The Hodrick-Prescott (HP) filter is a mathematical tool used in macroeconomics to separate a time series into its trend component and its cyclical component. It was developed by economists Robert Hodrick and Edward Prescott in 1980.
The HP filter works by decomposing a time series into two components: a trend component and a cyclical component. The trend component represents the long-term behavior of the time series, while the cyclical component represents the short-term fluctuations around the trend.
The HP filter is based on the assumption that the trend component of a time series varies smoothly over time, while the cyclical component varies more rapidly. The filter uses a mathematical algorithm to estimate the trend component of the time series, and then subtracts the trend from the original time series to obtain the cyclical component.
The HP filter is widely used in macroeconomics to analyze business cycles, as it allows researchers to separate the underlying trend in economic data from the short-term fluctuations. It is also used in finance to analyze asset prices, and in other fields where time series analysis is important.
█ Giga Kaleidoscope Modularized Trading System
Core components of an NNFX algorithmic trading strategy
The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend
3. Confirmation 1 - a technical indicator used to identify trends
4. Confirmation 2 - a technical indicator used to identify trends
5. Continuation - a technical indicator used to identify trends
6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown
7. Exit - a technical indicator used to determine when a trend is exhausted
8. Metamorphosis - a technical indicator that produces a compound signal from the combination of other GKD indicators*
*(not part of the NNFX algorithm)
What is Volatility in the NNFX trading system?
In the NNFX (No Nonsense Forex) trading system, ATR (Average True Range) is typically used to measure the volatility of an asset. It is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. ATR is calculated by taking the average of the true range values over a specified period.
True range is calculated as the maximum of the following values:
-Current high minus the current low
-Absolute value of the current high minus the previous close
-Absolute value of the current low minus the previous close
ATR is a dynamic indicator that changes with changes in volatility. As volatility increases, the value of ATR increases, and as volatility decreases, the value of ATR decreases. By using ATR in NNFX system, traders can adjust their stop loss and take profit levels according to the volatility of the asset being traded. This helps to ensure that the trade is given enough room to move, while also minimizing potential losses.
Other types of volatility include True Range Double (TRD), Close-to-Close, and Garman-Klass
What is a Baseline indicator?
The baseline is essentially a moving average, and is used to determine the overall direction of the market.
The baseline in the NNFX system is used to filter out trades that are not in line with the long-term trend of the market. The baseline is plotted on the chart along with other indicators, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR).
Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards, only long trades are taken, and if the baseline is sloping downwards, only short trades are taken. This approach helps to ensure that trades are in line with the overall trend of the market, and reduces the risk of entering trades that are likely to fail.
By using a baseline in the NNFX system, traders can have a clear reference point for determining the overall trend of the market, and can make more informed trading decisions. The baseline helps to filter out noise and false signals, and ensures that trades are taken in the direction of the long-term trend.
What is a Confirmation indicator?
Confirmation indicators are technical indicators that are used to confirm the signals generated by primary indicators. Primary indicators are the core indicators used in the NNFX system, such as the Average True Range (ATR), the Moving Average (MA), and the Relative Strength Index (RSI).
The purpose of the confirmation indicators is to reduce false signals and improve the accuracy of the trading system. They are designed to confirm the signals generated by the primary indicators by providing additional information about the strength and direction of the trend.
Some examples of confirmation indicators that may be used in the NNFX system include the Bollinger Bands, the MACD (Moving Average Convergence Divergence), and the MACD Oscillator. These indicators can provide information about the volatility, momentum, and trend strength of the market, and can be used to confirm the signals generated by the primary indicators.
In the NNFX system, confirmation indicators are used in combination with primary indicators and other filters to create a trading system that is robust and reliable. By using multiple indicators to confirm trading signals, the system aims to reduce the risk of false signals and improve the overall profitability of the trades.
What is a Continuation indicator?
In the NNFX (No Nonsense Forex) trading system, a continuation indicator is a technical indicator that is used to confirm a current trend and predict that the trend is likely to continue in the same direction. A continuation indicator is typically used in conjunction with other indicators in the system, such as a baseline indicator, to provide a comprehensive trading strategy.
What is a Volatility/Volume indicator?
Volume indicators, such as the On Balance Volume (OBV), the Chaikin Money Flow (CMF), or the Volume Price Trend (VPT), are used to measure the amount of buying and selling activity in a market. They are based on the trading volume of the market, and can provide information about the strength of the trend. In the NNFX system, volume indicators are used to confirm trading signals generated by the Moving Average and the Relative Strength Index. Volatility indicators include Average Direction Index, Waddah Attar, and Volatility Ratio. In the NNFX trading system, volatility is a proxy for volume and vice versa.
By using volume indicators as confirmation tools, the NNFX trading system aims to reduce the risk of false signals and improve the overall profitability of trades. These indicators can provide additional information about the market that is not captured by the primary indicators, and can help traders to make more informed trading decisions. In addition, volume indicators can be used to identify potential changes in market trends and to confirm the strength of price movements.
What is an Exit indicator?
The exit indicator is used in conjunction with other indicators in the system, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR), to provide a comprehensive trading strategy.
The exit indicator in the NNFX system can be any technical indicator that is deemed effective at identifying optimal exit points. Examples of exit indicators that are commonly used include the Parabolic SAR, and the Average Directional Index (ADX).
The purpose of the exit indicator is to identify when a trend is likely to reverse or when the market conditions have changed, signaling the need to exit a trade. By using an exit indicator, traders can manage their risk and prevent significant losses.
In the NNFX system, the exit indicator is used in conjunction with a stop loss and a take profit order to maximize profits and minimize losses. The stop loss order is used to limit the amount of loss that can be incurred if the trade goes against the trader, while the take profit order is used to lock in profits when the trade is moving in the trader's favor.
Overall, the use of an exit indicator in the NNFX trading system is an important component of a comprehensive trading strategy. It allows traders to manage their risk effectively and improve the profitability of their trades by exiting at the right time.
What is an Metamorphosis indicator?
The concept of a metamorphosis indicator involves the integration of two or more GKD indicators to generate a compound signal. This is achieved by evaluating the accuracy of each indicator and selecting the signal from the indicator with the highest accuracy. As an illustration, let's consider a scenario where we calculate the accuracy of 10 indicators and choose the signal from the indicator that demonstrates the highest accuracy.
The resulting output from the metamorphosis indicator can then be utilized in a GKD-BT backtest by occupying a slot that aligns with the purpose of the metamorphosis indicator. The slot can be a GKD-B, GKD-C, or GKD-E slot, depending on the specific requirements and objectives of the indicator. This allows for seamless integration and utilization of the compound signal within the GKD-BT framework.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v2.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
6. GKD-M - Metamorphosis module (Metamorphosis, Number 8 in the NNFX algorithm, but not part of the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data to A backtest module wherein the various components of the GKD system are combined to create a trading signal.
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Multi-Ticker CC Backtest
Baseline: Hull Moving Average
Volatility/Volume: Hurst Exponent
Confirmation 1: Advance Trend Pressure as shown on the chart above
Confirmation 2: uf2018
Continuation: Coppock Curve
Exit: Rex Oscillator
Metamorphosis: Baseline Optimizer
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, GKD-M, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD system.
█ Giga Kaleidoscope Modularized Trading System Signals
Standard Entry
1. GKD-C Confirmation gives signal
2. Baseline agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Volatility/Volume agrees
1-Candle Standard Entry
1a. GKD-C Confirmation gives signal
2a. Baseline agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
Next Candle
1b. Price retraced
2b. Baseline agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Baseline Entry
1. GKD-B Baseline gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Volatility/Volume agrees
7. Confirmation 1 signal was less than 'Maximum Allowable PSBC Bars Back' prior
1-Candle Baseline Entry
1a. GKD-B Baseline gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSBC Bars Back' prior
Next Candle
1b. Price retraced
2b. Baseline agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Volatility/Volume Entry
1. GKD-V Volatility/Volume gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Baseline agrees
7. Confirmation 1 signal was less than 7 candles prior
1-Candle Volatility/Volume Entry
1a. GKD-V Volatility/Volume gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSVVC Bars Back' prior
Next Candle
1b. Price retraced
2b. Volatility/Volume agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Baseline agrees
Confirmation 2 Entry
1. GKD-C Confirmation 2 gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Volatility/Volume agrees
6. Baseline agrees
7. Confirmation 1 signal was less than 7 candles prior
1-Candle Confirmation 2 Entry
1a. GKD-C Confirmation 2 gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSC2C Bars Back' prior
Next Candle
1b. Price retraced
2b. Confirmation 2 agrees
3b. Confirmation 1 agrees
4b. Volatility/Volume agrees
5b. Baseline agrees
PullBack Entry
1a. GKD-B Baseline gives signal
2a. Confirmation 1 agrees
3a. Price is beyond 1.0x Volatility of Baseline
Next Candle
1b. Price inside Goldie Locks Zone Minimum
2b. Price inside Goldie Locks Zone Maximum
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Continuation Entry
1. Standard Entry, 1-Candle Standard Entry, Baseline Entry, 1-Candle Baseline Entry, Volatility/Volume Entry, 1-Candle Volatility/Volume Entry, Confirmation 2 Entry, 1-Candle Confirmation 2 Entry, or Pullback entry triggered previously
2. Baseline hasn't crossed since entry signal trigger
4. Confirmation 1 agrees
5. Baseline agrees
6. Confirmation 2 agrees
Entry FraggerEntry Fragger is a simple buy signal indicator.
It is most suitable for cryptocurrency, especially for altcoins on the 5 minute to daily timeframe and is based on simple volume calculations, in combination with EMA's.
Main Signal Logic explained:
A buy signal is generated by counting candles with an above average sell volume of 130% to 170%, taking into account the candles position below and above the 50 and 200 EMA.
If criteria meet, the first green candle above the 50 EMA's suggests upcoming higher prices.
The indicator has 2 input variables.
"Signal Confirmations (0 - 7):" Changes signal accuracy by a defining an ammount of high sell volume candles necessary below the 50 EMA.
"Volume Calculation Base (9 - 200):" Sets the exponential volume multiplier, this affects candle coloring and the volume calculation inside the candle.
"Style Settings": Turn ON/OFF Signals, Cloud, Bar Coloring, EMA's, etc...
There are no generally suitable default numbers for those 2 inputs, those have to be tested out, depending on cryptocurrency and timeframe.
The calculation is very basic, the underlying idea being, market maker initiating range breakouts through rapid increase of volume above or below the EMA's .
Example settings:
SOLUSDT: Signal Confirmations: 2, Volume Calculation Base 13.
SOLUSDT: Signal Confirmations: 0, Volume Calculation Base 20.
As you can see it affects signals quite a lot, but staying accurate.
Finetune the inputs to your preference.
Risk to Reward, Stoploss, Take Profit, position sizing, etc... is up to the user.
Recommended entry is to wait for following candle closes, entering half of the candle size and setting Stoploss outside the structure, like this:
Or right below the candles open, for safety.
ChartRage - ELMAELMA - Exponential Logarithmic Moving Average
This is a new kind of moving average that is using exponential normalization of a logarithmic formula. The exponential function is used to average the weight on the moving average while the logarithmic function is used to calculate the overall price effect.
Features and Settings:
◻️ Following rate of change instead of absolute levels
◻️ Choose input source of the data
◻️ Real time signals through price interaction
◻️ Change ELMA length
◻️ Change the exponential decay rate
◻️ Customize base color and signal color
Equation of the ELMA:
This formula calculates a weighted average of the logarithm of prices, where more recent prices have a higher weight. The result is then exponentiated to return the ELMA value. This approach emphasizes the relative changes in price, making the ELMA sensitive to the % rate of change rather than absolute price levels. The decay rate can be adjusted in the settings.
Comparison EMA vs ELMA:
In this image we see the differences to the Exponential Moving Average.
Price Interaction and earlier Signals:
In this image we have added the bars, so we can see that the ELMA provides different signals of resistance and support zones and highlights them, by changing to the color yellow, when prices interact with the ELMA.
Strategy by trading Support and Resistance Zones:
The ELMA helps to evaluate trends and find entry points in bullish market conditions, and exit points in bearish conditions. When prices drop below the ELMA in a bull market, it is considered a buying signal. Conversely, in a bear market, it serves as an exit signal when prices trade above the ELMA.
Volatile Markets:
The ELMA works on all timeframes and markets. In this example we used the default value for Bitcoin. The ELMA clearly shows support and resistance zones. Depending on the asset, the length and the decay rate should be adjusted to provide the best results.
Real Time Signals:
Signals occur not after a candle closes but when price interacts with the ELMA level, providing real time signals by shifting color. (default = yellow)
Disclaimer* All analyses, charts, scripts, strategies, ideas, or indicators developed by us are provided for informational and educational purposes only. We do not guarantee any future results based on the use of these tools or past data. Users should trade at their own risk.
This work is licensed under Attribution-NonCommercial-ShareAlike 4.0 International
creativecommons.org
MOST on RSIMOST is applied on this RSI moving average with an extra default option added VAR/VIDYA (Variable Index Dynamic Moving Average)
MOST added on RSI has a Moving Average of RSI and a trailing percent stop level of the Moving Average that can be adjusted by changing the length of the MA and %percent of the stop level.
BUY SIGNAL when the Moving Average Line crosses above the MOST Line
LONG CONDITION when the Moving Average is above the MOST
SELL SIGNAL when Moving Average Line crosses below MOST Line
SHORT CONDITION when the Moving Average is below MOST
-MOST indicator advised to use with Variable Moving Average in the sideways market by its developer Anıl Özekşi, so there are a couple of alternative Moving Average OPTIONS to use in the calculation of MOST:
"SMA", "Bollinger Bands", "EMA", "SMMA (RMA)", "WMA", "VWMA", "VAR"
SMA: Simple Moving Average
EMA: Exponential Movin Average
SMMA (RMA: Smoothed Moving Average, Rolling/Running Moving Average
WMA: Weighted Moving Average
WWMA: Welles Wilder's Moving Average
VAR: Variable Index Dynamic Moving Average aka VIDYA
The Moving Average length and stop loss percent values must be increased for less reliable but late signals. Conversely, it must be decreased to have more and faster signals.
As this indicator is derived from TradingView's built-in RSI, it has Bollinger Bands bounding RSI and a tool that can be used for Bullish & Bearish divergences between the price and RSI. (Show Divergence option)
Finally, users may check the box "Show Signals" to visually see the BUY & SELL signals.
Universal Algorithm [BackQuant]Universal Algorithm
It is a trading strategy designed CLEAR TREND DETECTION . This script is the culmination of extensive research and development efforts aimed at providing traders with a robust tool capable of adapting to a wide array of market conditions. This description delves into the core components, methodologies, and operational parameters of Universal Algo to offer potential users a clear understanding of its functionalities and the principles underpinning its design.
Core Methodologies and Features:
Integrated Systems: Universal Algo is built around six core systems, each contributing unique analytical perspectives to enhance trade signal reliability. These systems are designed to identify clear trend opportunities for significant gains, while also employing logic to navigate through ranging markets effectively.
Adaptive Market Logic: By incorporating volatility metrics, the algorithm dynamically adjusts to changing market conditions. This ensures that the strategy remains effective across different market regimes, aiming to reduce market noise and improve signal quality.
Selective Shorting Mechanism: While the primary focus is on capturing long positions, it includes an optional shorting feature. This can be activated by users to adapt the strategy during macro downtrends, thus providing a flexible approach to market participation.
Backtesting and Forward-Testing Rigor : The strategy has undergone rigorous testing to validate its performance and reliability. It demonstrates prudent risk management by optimizing conditions under which short positions are considered, aiming to mitigate drawdowns and preserve capital.
Operational Parameters:
Customization Options: The script offers a range of user inputs, allowing for customization of the backtesting starting date, the decision to display the strategy equity curve, among other settings. These inputs cater to diverse trading needs and preferences, offering users control over their strategy implementation.
Transparency and Logic Insight: While specific calculation details and proprietary indicators are integral to maintaining the uniqueness of Universal Algo , the strategy is grounded on well-established financial analysis techniques. These include momentum analysis, volatility assessments, and adaptive thresholding, among others, to formulate its trade signals.
Realistic Trading Conditions : Backtesting, considered realistic trading conditions, including appropriate account size, commission, slippage, and sustainable risk levels per trade. The strategy is designed and tested with a focus on achieving a balance between risk and reward, striving for robustness and reliability rather than unrealistic profitability promises.
Concluding Thoughts:
Universal Algo is offered to the TradingView community as a tool for traders seeking to enhance their market analysis and trading strategies. Its development is driven by a commitment to quality, innovation, and adaptability, aiming to provide valuable insights and decision-support in various market conditions. Potential users are encouraged to evaluate Universal Algo within the context of their overall trading approach and objectives.
EMA20 in MTFThe "EMA20 in MTF" indicator on TradingView is a versatile tool designed to display the 20-period Exponential Moving Average (EMA) as a horizontal line across various time frames. This indicator provides traders with a comprehensive view of the EMA's behavior by plotting it on multiple time frames (MTF), including Quarterly, Monthly, Weekly, Daily, and 125 Minutes.
By incorporating EMA data from different time frames, traders can gain insights into both short-term and long-term trends. The Quarterly and Monthly time frames offer a broader perspective on market movements, while the Weekly and Daily time frames provide intermediate-term trends. The inclusion of the 125 Minutes time frame further enhances precision, catering to intraday trading strategies.
Overall, the "EMA20 in MTF" indicator serves as a valuable tool for traders seeking to analyze EMA dynamics across various time frames, aiding in trend identification and decision-making processes.
Predictive Channel SignalsThis script is a comprehensive tool designed to enhance trading strategies by utilizing predictive channels, multiple moving average types, and dynamic signal generation. The script is meticulously crafted for traders who seek to identify potential support and resistance levels, anticipate market reversals, and optimize entry and exit points through advanced technical analysis featuring with the help of codes provided by LuxAlgo.
Core Features:
Dynamic Predictive Channels: The script calculates predictive channels based on price movements and volatility, represented by adjustable factors for sensitivity and slope. These channels adapt to changing market conditions, providing real-time support and resistance levels.
Versatile Moving Averages: Users can select from a variety of moving average types, including SMA, EMA, SMMA (RMA), HullMA, WMA, VWMA, DEMA, and TEMA. This flexibility allows traders to tailor the analysis to their specific strategy and market view.
Signal Generation: The script generates buying and selling signals based on the interaction between moving averages and predictive channels. Signals are categorized into low, mid, and high tiers, indicating the strength and potential risk/reward of the trade opportunity.
Visual Cues and Customization: With an emphasis on usability, the script offers customizable color schemes for easy interpretation of bullish and bearish zones, moving averages, and trading signals. Traders can quickly identify market trends and reversal points at a glance.
Advanced Calculations: Utilizing calculations such as the Average True Range (ATR) for volatility assessment, the script ensures that signals are both sensitive to market dynamics and robust against false positives.
Ideal for Traders Who:
Prefer a technical analysis approach with a focus on moving averages and price channels.
Desire a customizable tool that can adapt to different trading styles and market conditions.
Seek to enhance their trading strategy with predictive insights and actionable signals.
Circle = Entry Point
End of polyline = Stop Loss
1 Circle = Low Strength
2 Circles = Mid Strength
3 Circles = High Strength
Dynamic Bern TrailThis indicator will help you following price movements in trending or ranging markets. Within it's calculations it uses ATR, EMA with a smoothing effect. It includes a buffer zone to help determine where price may turn around and reverse or to identify when a breakout occurs by breaking through the ATR trail. You can customize and play around with several settings to adjust it for your asset. Adjustments that can be made besides visuals are ATR Length, ATR Multiplier, EMA Length, Smoothing Length and the Buffer Multiplier.
QTE Scalper ModifiedA modified version of the QTE scalper indicator. Produces a buy/sell signal based on a 2 candle pattern. For long signals it produces a signal when the high and low of the second candle are below the high and low of the first candle and both candles close above the 10 period EMA. The reverse is true for short signals.
Added functionality so that signals will trigger an alert: Add the indicator to the chart on the instrument and timeframe you wish to use it on. Add an alert and in the 'condition' section choose the indicator and set the trigger as 'once per bar close'. You will have to set individual alerts for both long and short signals and if you change the time period on the chart.
SVMKR_UT_Bot_HMA_UCS_LRSThis Pine Script code is a TradingView study script titled "SVMKR_UT_Bot_HMA_UCS_LRS". It combines two separate trading indicators: the UT Bot (Ultimate Trailing Stop Bot) and the UCS_LRS (Linear Regression Slope) indicator.
UT Bot (Ultimate Trailing Stop Bot):
The UT Bot is designed to provide buy and sell signals based on a trailing stop strategy.
It calculates the trailing stop level using the Average True Range (ATR) and Heikin Ashi candle signals if enabled.
Buy signals are generated when the price crosses above the trailing stop, while sell signals occur when the price crosses below the trailing stop.
Additionally, buy and sell signals are visually represented on the chart with corresponding labels and shapes.
The script also includes options to customize the sensitivity of the trailing stop and to color the bars based on buy or sell signals.
Hull Moving Average (HMA):
This section calculates and plots the Hull Moving Average, a type of moving average that reduces lag and improves smoothing compared to traditional moving averages.
It uses the weighted moving average (WMA) to compute the HMA, which helps to identify trend direction and potential reversal points.
UCS_LRS (Linear Regression Slope):
The UCS_LRS indicator calculates the linear regression slope of the closing prices over a specified period.
It then applies exponential smoothing to the slope values and calculates an average slope.
Buy signals are generated when the current slope is greater than the average slope and positive, indicating an uptrend.
Conversely, sell signals are generated when the current slope is less than the average slope and negative, suggesting a downtrend.
The linear regression slope and its average are plotted on the chart, allowing traders to visually identify trend strength and potential reversal points.
Overall, this combined script provides traders with a comprehensive set of tools for trend following and momentum trading strategies, integrating trailing stop analysis, moving average smoothing, and linear regression slope analysis into a single script for technical analysis on TradingView charts.
Hull AMA SignalsThis script is a comprehensive trading indicator named "Hull AMA Signals", which combines AMA and HSO by LuxAlgo and ther video based strategy techniques to provide buy (long) and sell (short) signals. It overlays directly on the price chart, offering a dynamic and visually intuitive trading aid. The core components of this indicator are Adaptive Moving Averages (AMA), Hull Moving Average (HMA), and a unique Hull squeeze oscillator (HSO), each configured with customizable parameters for flexibility and adaptability to various market conditions.
Features and Components
Adaptive Moving Averages (AMA): This indicator employs two sets of AMAs, each with distinct lengths, multipliers, lags, and overshoot parameters. The AMAs are designed to adapt their sensitivity based on the market's volatility, making them more responsive during significant price movements and less prone to false signals during periods of consolidation.
Hull Moving Average (HMA): The HMA is calculated using a sophisticated algorithm that aims to reduce the lag commonly associated with traditional moving averages. It provides a smoother and more responsive moving average line, which helps in identifying the prevailing market trend more accurately.
Hull Squeeze Oscillator (HSO): A novel component of this indicator, the HSO, is designed to identify potential market breakouts. It does so by comparing the Hull Moving Average's direction and momentum against a dynamically calculated mean, generating bullish or bearish signals based on the crossover and divergence from this mean.
Buy (Long) and Sell (Short) Signals: The script intelligently combines signals from the AMA crossovers and the Hull squeeze oscillator to pinpoint potential buy and sell opportunities. Bullish signals are generated when there's a positive crossover in the AMAs accompanied by a bullish dot from the HSO, whereas bearish signals are indicated by a negative crossover in the AMAs along with a bearish dot from the HSO.
Customization and Style Options: Users have the ability to adjust various parameters such as the length of the moving averages, multipliers, and source data, enabling customization for different trading strategies and asset classes. Additionally, color-coded visual elements like gradients and shapes enhance the readability and instant recognition of trading signals.
Use Cases
Trend Identification: By analyzing the direction and position of the AMAs and HMA, traders can easily discern the prevailing market trend, helping them to align their trades with the market momentum.
Signal Confirmation: The combination of AMA crossovers and HSO signals provides a robust framework for confirming trade entries and exits, potentially increasing the reliability of the trading signals.
Volatility Adaptation: The adaptive nature of the AMAs and the dynamic calculation of the HSO mean allow this indicator to adjust to changing market volatility, making it suitable for a wide range of market environments.
This indicator is suitable for traders looking for a comprehensive and dynamic technical analysis tool that combines trend analysis with signal generation, offering both visual appeal and practical trading utility.
Candle Colours and EMA Colours [LuciTech]this indicator assigns a colour to each candle based on the relationship between the price and the EMAs, The indicator first checks whether the close price is above or below the first EMA, If the close price is above the first EMA the candle is coloured green. If the close price inbetween both EMAs the candle is colored gray. If the close price is below the second EMA, the candle is coloured red.
the indicator also colours the EMAs based on the closed price, if closed price is above the EMAs its coloured green and if price is closed below the EMA is coloured red.
The colours of the candles and EMAs can be changed in "style" and the periods of the EMAs can be changed in inputs.
Momentum Ghost Machine [ChartPrime]Momentum Ghost Machine (ChartPrime) is designed to be the next generation in momentum/rate of change analysis. This indicator utilizes the properties of one of our favorite filters to create a more accurate and stable momentum oscillator by using a high quality filtered delayed signal to do the momentum comparison.
Traditional momentum/roc uses the raw price data to compare current price to previous price to generate a directional oscillator. This leaves the oscillator prone to false readings and noisy outputs that leave traders unsure of the real likelihood of a future movement. One way to mitigate this issue would be to use some sort of moving average. Unfortunately, this can only go so far because simple moving average algorithms result in a poor reconstruction of the actual shape of the underlying signal.
The windowed sinc low pass filter is a linear phase filter, meaning that it doesn't change the shape or size of the original signal when applied. This results in a faithful reconstruction of the original signal, but without the "high frequency noise". Just like any filter, the process of applying it requires that we have "future" samples resulting in a time delay for real time applications. Fortunately this is a great thing in the context of a momentum oscillator because we need some representation of past price data to compare the current price data to. By using an ideal low pass filter to generate this delayed signal we can super charge the momentum oscillator and fix the majority of issues its predecessors had.
This indicator has a few extra features that other momentum/roc indicators dont have. One major yet simple improvement is the inclusion of a moving average to help gauge the rate of change of this indicator. Since we included a moving average, we thought it would only be appropriate to add a histogram to help visualize the relationship between the signal and its average. To go further with this we have also included linear extrapolation to further help you predict the momentum and direction of this oscillator. Included with this extrapolation we have also added the histogram in the extrapolation to further enhance its visual interpretation. Finally, the inclusion of a candle coloring feature really drives how the utility of the Momentum Machine .
There are three distinct options when using the candle coloring feature: Direct, MA, and Both. With direct the candles will be colored based on the indicators direction and polarity. When it is above zero and moving up, it displays a green color. When it is above zero and moving down it will display a light green color. Conversely, when the indicator is below zero and moving down it displays a red color, and when it it moving up and below zero it will display a light red color. MA coloring will color the candles just like a MACD. If the signal is above its MA and moving up it will display a green color, and when it is above its MA and moving down it will display a light green color.
When the signal is below its MA and moving down it will display a red color, and when its below its ma and moving up it will display a light red color. Both combines the two into a single color scheme providing you with the best of both worlds. If the indicator is above zero it will display the MA colors with a slight twist. When the indicator is moving down and is below its MA it will display a lighter color than before, and when it is below zero and is above its MA it will display a darker color color.
Length of 50 with a smoothing of 100
Length of 50 with a smoothing of 25
By default, the indicator is set to a momentum length of 50, with a post smoothing of 2. We have chosen the longer period for the momentum length to highlight the performance of this indicator compared to its ancestors. A major point to consider with this indicator is that you can only achieve so much smoothing for a chosen delay. This is because more data is required to produce a smoother signal at a specified length. Once you have selected your desired momentum length you can then select your desired momentum smoothing . This is made possible by the use of the windowed sinc low pass algorithm because it includes a frequency cutoff argument. This means that you can have as little or as much smoothing as you please without impacting the period of the indicator. In the provided examples above this paragraph is a visual representation of what is going on under the hood of this indicator. The blue line is the filtered signal being compared to the current closing price. As you can see, the filtered signal is very smooth and accurately represents the underlying price action without noise.
We hope that users can find the same utility as we did in this indicator and that it levels up your analysis utilizing the momentum oscillator or rate of change.
Enjoy
Dynamic Trailing (Zeiierman)█ Overview
The Dynamic Trailing (Zeiierman) indicator enhances the traditional SuperTrend approach by providing a more nuanced, adaptable tool for trend analysis and market volatility assessment. It combines techniques to identify dynamic support and resistance levels, trend directions, and market volatility. By integrating the Average True Range (ATR) with a unique multiplier system and smoothing mechanisms, this indicator offers a nuanced approach to trend-following strategies, making it a valuable asset for traders looking to leverage SuperTrend methodologies with additional insights into market dynamics.
█ How It Works
At its core, this indicator builds on the traditional SuperTrend formula by utilizing a modified ATR calculation to define the deviation for dynamic support and resistance levels. These levels are dynamically adjusted based on market volatility. The innovation lies in the addition of the Hull Moving Average (HMA) and the Triple Exponential Moving Average (TEMA) for an enhanced smoothing effect, making the indicator's trend signals more reliable and less prone to market noise. The trend direction is determined by comparing the closing price with the dynamic levels, facilitating clear bullish or bearish signals.
The indicator incorporates a 'Supertrend' function, which uses the dynamic levels and the price’s position relative to them to determine the trend direction. This determination is visualized through color-coded lines and a cloud zone, which expands or contracts based on the ATR and a user-defined width setting, illustrating the market's volatility and trend strength.
ATR Calculation: Utilizes the Average True Range (ATR) to measure market volatility. The ATR is a cornerstone of this indicator, helping to dynamically adjust the support and resistance levels according to the market’s changing conditions.
Supertrend Calculation: Implements a supertrend formula that combines the ATR with user-defined multipliers to plot potential trend directions. This feature helps in identifying whether the market is in an uptrend or downtrend, offering visual cues for potential reversals.
TEMA Calculation: Employs the Triple Exponential Moving Average (TEMA) through a Hull Moving Average (HMA) calculation to smooth out price data. This smoothing process helps in reducing market noise and makes the trend direction clearer.
Dynamic Support and Resistance: Calculates dynamic support and resistance levels by applying a deviation (derived from the ATR and user-defined multiplier) to the smoothed price data. These levels adapt to market conditions, providing areas where price might experience support or resistance.
Trend and Cloud Calculation: Determines the overall trend direction and plots a 'Cloud' zone around it, which adjusts in width based on the ATR and a user-defined cloud width setting. This cloud acts as a visual buffer, indicating the strength and stability of the current trend.
█ How to Use
Trend Identification: The primary function of this indicator is to help traders quickly identify the prevailing market trend. A change in the color of the dynamic trailing line or its position relative to the price can signal potential trend reversals.
Dynamic Support and Resistance: Unlike static levels, the dynamic levels adjust with market conditions, providing current areas where the price might experience support or resistance.
Dynamic Support
Dynamic Resistance
█ Settings
Mult (Multiplier): Adjusts the multiplier for the ATR calculation, affecting the deviation distance for support and resistance levels. Higher values decrease sensitivity and vice versa.
Len (Length): Sets the period for the HMA in the TEMA calculation, influencing the indicator's responsiveness to price changes.
Smoothness: Determines the smoothness of the dynamic support and resistance lines by setting the SMA length. Higher values result in smoother lines.
Cloud Width : Modifies the width of the cloud, providing a visual representation of market volatility.
Color Settings (upcol and dncol): Allows users to customize the colors of the indicator's lines and cloud, aiding in visual trend identification.
-----------------
Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
MA - Plus / Connectable [Azullian]
The Moving Average Plus indicator enhances trend analysis by offering refined calculations and a variety of moving average types for sharper insights. As a component of the connectable indicator system on TradingView, it's designed to simplify strategy testing, visualization, and construction, all without requiring coding skills. In line with our suite of connectable indicators , it integrates through TradingView's input source, serving as a signal connector that links different indicators. Each connectable indicator, including the Moving Average Plus, plays a role in contributing signal weight to the system, culminating in an informed output for strategies or signal monitors.
█ DISTINCTIVE FEATURES
The Moving Average Plus indicator brings a set of features to enhance your market analysis:
• Variety of Moving Average Options: Select from multiple moving average types such as ALMA, EMA, HMA, RMA, and SMA, providing flexibility and precision in identifying market trends.
• Customizable Analysis Tools: Tailor the indicator settings to suit your specific analytical needs, enabling a more personalized approach to trend analysis.
• Enhanced Trend Visualization: Visual cues and detailed trend line plotting offer clear insights into market movements, aiding in decision-making processes.
• Integrated Signal Weighting: Utilize the signal weight mechanism for a comprehensive understanding of trend strength and market dynamics.
█ UNIFORM SETTINGS AND A WAY OF WORK
Although connectable indicators may have specific weight scoring conditions, they all aim to follow a standardized general approach to weight scoring settings, as outlined below.
■ Connectable indicators - Settings
• 🗲 Energy: Energy applies an ATR multiplier to the plotted shapes on the chart. A higher value plots shapes farther away from the candle, enhancing visibility.
• ☼ Brightness: Brightness determines the opacity of the shape plotted on the chart, aiding visibility. Indicator weight also influences opacity.
• → Input: Use the input setting to specify a data source for the indicator. Here you can connect the indicator to other indicators.
• ⌥ Flow: Determine where you want to receive signals from:
○ Both: Weights from this indicator and the connected indicator will apply
○ Indicator only: Only weights from this indicator will apply
○ Input only: Only weights from the connected indicator will apply
• ⥅ Weight multiplier: Multiply all weights in the entire indicator by a given factor, useful for quickly testing different indicators in a granular setup.
• ⥇ Threshold: Set a threshold to indicate the minimum amount of weight it should receive to pass it through to the next indicator.
• ⥱ Limiter: Set a hard limit to the maximum amount of weight that can be fed through the indicator.
■ Connectable indicators - Weight scoring settings
▢ Weight scoring conditions
• SM – Signal mode: Enable specific conditions for weight scoring
○ Start: A new trend starting will score
○ End: A trend ending will score
○ Zone: Continuous scoring for each candle between the start and the end.
• SP – Signal period: Defines a range of candles within which a signal can score.
• SC - Signal count: Specifies the number of bars to retrospectively examine and score.
○ Single: Score for a single occurrence
○ All occurrences: Score for all occurrences
○ Single + Threshold: Score for single occurrences within the signal period (SP)
○ Every + Threshold: Score for all occurrences within the signal period (SP)
▢ Weight scoring direction
• ES: Enter Short weight
• XL: Exit long weight
• EL: Enter Long weight
• XS: Exit Short weight
▢ Weight scoring values
• Weights can hold either positive or negative scores. Positive weights enhance a particular trading direction, while negative weights diminish it.
█ MA - Plus - INDICATOR SETTINGS
■ Main settings
• Enable/Disable Indicator: Toggle the entire indicator on or off.
• T - Type: Choose a type of moving average. (ALMA, EMA, HMA, RMA, SMA, SWMA, VWMA, WMA)
• L - Length: Set a period on which the moving average is calculated.
• F - Filter: Set a conditional filter for scoring:
○ Line position: Score bullish when the current trendline is above the next trendline, score bearish when the current trendline is below the next trendline
○ Line direction: Score bullish when the trend line is going up, score bearish when the trendline is going down.
○ Line candle position: Score bullish when the candles are above the current trendline, score bearish when the candles are below the current trendline
○ Any: Score if any of the previously mentioned conditions are true
○ All: Score if all of the previously mentioned conditions are true
• S - Source: Choose an alternative data source for the Moving average calculation.
• T - Timeframe: Select an alternative timeframe for the Moving average calculation.
• C - Candletype: Choose a candletype for the alternative source.
■ Scoring functionality
• For each moving average you'll be able to score Bullish, Bearish or Neutral for each of the conditions as mentioned in the filter above.
█ PLOTTING
• Standard: Symbols (EL, XS, ES, XL) Moving average lines are plotted with bearish, bullish and neutral zones, in the visuals section you can enable plotting by weight which will only show moving average lines to which weight is addressed.
• Conditional Settings: A larger icon appears if global conditions are met. For instance, with a Threshold(⥇) of 12, Signal Period (SP) of 3, and Scoring Condition (SC) set to "EVERY", a moving average signaling over two times in 3 candles (scoring 6 each) triggers a larger icon.
█ USAGE OF CONNECTABLE INDICATORS
■ Connectable chaining mechanism
Connectable indicators can be connected directly to the signal monitor, signal filter or strategy , or they can be daisy chained to each other while the last indicator in the chain connects to the signal monitor, signal filter or strategy. When using a signal filter you can chain the filter to the strategy input to make your chain complete.
• Direct chaining: Connect an indicator directly to the signal monitor, signal filter or strategy through the provided inputs (→).
• Daisy chaining: Connect indicators using the indicator input (→). The first in a daisy chain should have a flow (⌥) set to 'Indicator only'. Subsequent indicators use 'Both' to pass the previous weight. The final indicator connects to the signal monitor, signal filter, or strategy.
■ Set up this indicator with a signal filter and strategy
The indicator provides visual cues based on signal conditions. However, its weight system is best utilized when paired with a connectable signal filter, monitor, or strategy .
Let's connect the MA - Plus to a connectable signal filter and a strategy :
1. Load all relevant indicators
• Load MA - Plus / Connectable
• Load Signal filter / Connectable
• Load Strategy / Connectable
2. Signal Filter: Connect the MA - Plus to the Signal Filter
• Open the signal filter settings
• Choose one of the five input dropdowns (1→, 2→, 3→, 4→, 5→) and choose : MA - Plus / Connectable: Signal Connector
• Toggle the enable box before the connected input to enable the incoming signal
3. Signal Filter: Update the filter settings if needed
• The default filter mode for the trading direction is SWING, and is compatible with the default settings in the strategy and indicators.
4. Signal Filter: Update the weight threshold settings if needed
• All connectable indicators load by default with a score of 6 for each direction (EL, XL, ES, XS)
• By default, weight threshold is 'ABOVE' Threshold 1 (TH1) and Threshold 2 (TH2), both set at 5. This allows each occurrence to score, as the default score is 1 point above the threshold.
5. Strategy: Connect the strategy to the signal filter in the strategy settings
• Select a strategy input → and select the Signal filter: Signal connector
6. Strategy: Enable filter compatible directions
• As the default setting of the filter is SWING, we should also set the SM (Strategy mode) to SWING.
Now that everything is connected, you'll notice green spikes in the signal filter representing long signals, and red spikes indicating short signals. Trades will also appear on the chart, complemented by a performance overview. Your journey is just beginning: delve into different scoring mechanisms, merge diverse connectable indicators, and craft unique chains. Instantly test your results and discover the potential of your configurations. Dive deep and enjoy the process!
█ BENEFITS
• Adaptable Modular Design: Arrange indicators in diverse structures via direct or daisy chaining, allowing tailored configurations to align with your analysis approach.
• Streamlined Backtesting: Simplify the iterative process of testing and adjusting combinations, facilitating a smoother exploration of potential setups.
• Intuitive Interface: Navigate TradingView with added ease. Integrate desired indicators, adjust settings, and establish alerts without delving into complex code.
• Signal Weight Precision: Leverage granular weight allocation among signals, offering a deeper layer of customization in strategy formulation.
• Advanced Signal Filtering: Define entry and exit conditions with more clarity, granting an added layer of strategy precision.
• Clear Visual Feedback: Distinct visual signals and cues enhance the readability of charts, promoting informed decision-making.
• Standardized Defaults: Indicators are equipped with universally recognized preset settings, ensuring consistency in initial setups across different types like momentum or volatility.
• Reliability: Our indicators are meticulously developed to prevent repainting. We strictly adhere to TradingView's coding conventions, ensuring our code is both performant and clean.
█ COMPATIBLE INDICATORS
Each indicator that incorporates our open-source 'azLibConnector' library and adheres to our conventions can be effortlessly integrated and used as detailed above.
For clarity and recognition within the TradingView platform, we append the suffix ' / Connectable' to every compatible indicator.
█ COMMON MISTAKES, CLARIFICATIONS AND TIPS
• Removing an indicator from a chain: Deleting a linked indicator and confirming the "remove study tree" alert will also remove all underlying indicators in the object tree. Before removing one, disconnect the adjacent indicators and move it to the object stack's bottom.
• Point systems: The azLibConnector provides 500 points for each direction (EL: Enter long, XL: Exit long, ES: Enter short, XS: Exit short) Remember this cap when devising a point structure.
• Flow misconfiguration: In daisy chains the first indicator should always have a flow (⌥) setting of 'indicator only' while other indicator should have a flow (⌥) setting of 'both'.
• Hide attributes: As connectable indicators send through quite some information you'll notice all the arguments are taking up some screenwidth and cause some visual clutter. You can disable arguments in Chart Settings / Status line.
• Layout and abbreviations: To maintain a consistent structure, we use abbreviations for each input. While this may initially seem complex, you'll quickly become familiar with them. Each abbreviation is also explained in the inline tooltips.
• Inputs: Connecting a connectable indicator directly to the strategy delivers the raw signal without a weight threshold, meaning every signal will trigger a trade.
█ A NOTE OF GRATITUDE
Through years of exploring TradingView and Pine Script, we've drawn immense inspiration from the community's knowledge and innovation. Thank you for being a constant source of motivation and insight.
█ RISK DISCLAIMER
Azullian's content, tools, scripts, articles, and educational offerings are presented purely for educational and informational uses. Please be aware that past performance should not be considered a predictor of future results.
MBAND 200 4H BTC/USDT - By MGS-TradingMBAND 200 4H BTC/USDT with RSI and Volume by MGS-Trading: A Neural Network-Inspired Indicator
Introduction:
The MBAND 200 4H BTC/USDT with RSI and Volume represents a groundbreaking achievement in the integration of artificial intelligence (AI) into cryptocurrency market analysis. Developed by MGS-Trading, this indicator is the culmination of extensive research and development efforts aimed at leveraging AI's power to enhance trading strategies. By synthesizing neural network concepts with traditional technical analysis, the MBAND indicator offers a dynamic, multi-dimensional view of the market, providing traders with unparalleled insights and actionable signals.
Innovative Approach:
Our journey to create the MBAND indicator began with a simple question: How can we mimic the decision-making prowess of a neural network in a trading indicator? The answer lay in the weighted aggregation of Exponential Moving Averages (EMAs) from multiple timeframes, each serving as a unique input akin to a neuron in a neural network. These weights are not arbitrary; they were painstakingly optimized through backtesting across various market conditions to ensure they reflect the significance of each timeframe’s contribution to overall market dynamics.
Core Features:
Neural Network-Inspired Weights: The heart of the MBAND indicator lies in its AI-inspired weighting system, which treats each timeframe’s EMA as an input node in a neural network. This allows the indicator to process complex market data in a nuanced and sophisticated manner, leading to more refined and informed trading signals.
Multi-Timeframe EMA Analysis: By analyzing EMAs from 15 minutes to 3 days, the MBAND indicator captures a comprehensive snapshot of market trends, enabling traders to make informed decisions based on a broad spectrum of data.
RSI and Volume Integration: The inclusion of the Relative Strength Index (RSI) and volume data adds layers of confirmation to the signals generated by the EMA bands. This multi-indicator approach helps in identifying high-probability setups, reinforcing the neural network’s concept of leveraging multiple data points for decision-making.
Usage Guidelines:
Signal Interpretation: The MBAND bands provide a visual representation of the market’s momentum and direction. A price moving above the upper band signals strength and potential continuation of an uptrend, while a move below the lower band suggests weakness and a possible downtrend.
Overbought/Oversold Conditions: The RSI component identifies when the asset is potentially overbought (>70) or oversold (<30). Traders should watch for these conditions near the MBAND levels for potential reversal opportunities.
Volume Confirmation: An increase in volume accompanying a price move towards or beyond an MBAND level serves as confirmation of the strength behind the move. This can indicate whether a breakout is likely to sustain or if a reversal has substantial backing.
Strategic Entry and Exit Points: Combine the MBAND readings with RSI and volume indicators to pinpoint strategic entry and exit points. For example, consider entering a long position when the price is near the lower MBAND, RSI indicates oversold conditions, and there is a notable volume increase.
About MGS-Trading:
At MGS-Trading, we are passionate about harnessing the transformative power of AI to revolutionize cryptocurrency trading. Our indicators and tools are designed to provide traders with advanced analytics and insights, drawing on the latest AI techniques and methodologies. The MBAND 200 4H BTC/USDT with RSI and Volume indicator is a prime example of our commitment to innovation, offering traders a sophisticated, AI-enhanced tool for navigating the complexities of the cryptocurrency markets.
Disclaimer:
The MBAND indicator is provided for informational purposes only and does not constitute investment advice. Trading cryptocurrencies involves significant risk and can result in the loss of your investment. We recommend conducting your own research and consulting with a qualified financial advisor before making any trading decisions.
SMA Angular Trends [Yosiet]This indicator uses two specific SMA configurations conditioned by an angular slope that is always repeated in trend markets, which are usually beneficial in swing or long-term strategies.
SETTINGS
- Fast Angle Threshold: Is the value in degrees for the condition of the fast sma
- Slow Angle Threshold: Is the value in degrees for the condition of the slow sma
- Linear Mode: When is active, it shows the sma curves only when the condition is satisfied. When is inactive, it shows color of the trends
HOW TO USE
This indicator it helps to see clearly the trends and the oppotunities to entry/exit in breakouts and retests
WHY THOSE SMAs
The SMAs are sma(7, low) and sma(30, high), those setups came from analyze several others indicators with machine learning searching for convergence points in 2018.
THOUGHTS
This indicator only pretends to help traders to take decissions with extra data confirmation
IMPROVEMENTS
You can comment your ideas and sugestions to improve this indicator
Kalman Filtered RSI Oscillator [BackQuant]Kalman Filtered RSI Oscillator
The Kalman Filtered RSI Oscillator is BackQuants new free indicator designed for traders seeking an advanced, empirical approach to trend detection and momentum analysis. By integrating the robustness of a Kalman filter with the adaptability of the Relative Strength Index (RSI), this tool offers a sophisticated method to capture market dynamics. This indicator is crafted to provide a clearer, more responsive insight into price trends and momentum shifts, enabling traders to make informed decisions in fast-moving markets.
Core Principles
Kalman Filter Dynamics:
At its core, the Kalman Filtered RSI Oscillator leverages the Kalman filter, renowned for its efficiency in predicting the state of linear dynamic systems amidst uncertainties. By applying it to the RSI calculation, the tool adeptly filters out market noise, offering a smoothed price source that forms the basis for more accurate momentum analysis. The inclusion of customizable parameters like process noise, measurement noise, and filter order allows traders to fine-tune the filter’s sensitivity to market changes, making it a versatile tool for various trading environments.
RSI Adaptation:
The RSI is a widely used momentum oscillator that measures the speed and change of price movements. By integrating the RSI with the Kalman filter, the oscillator not only identifies the prevailing trend but also provides a smoothed representation of momentum. This synergy enhances the indicator's ability to signal potential reversals and trend continuations with a higher degree of reliability.
Advanced Smoothing Techniques:
The indicator further offers an optional smoothing feature for the RSI, employing a selection of moving averages (HMA, THMA, EHMA, SMA, EMA, WMA, TEMA, VWMA) for traders seeking to reduce volatility and refine signal clarity. This advanced smoothing mechanism is pivotal for traders looking to mitigate the effects of short-term price fluctuations on the RSI's accuracy.
Empirical Significance:
Empirically, the Kalman Filtered RSI Oscillator stands out for its dynamic adjustment to market conditions. Unlike static indicators, the Kalman filter continuously updates its estimates based on incoming price data, making it inherently more responsive to new market information. This dynamic adaptation, combined with the RSI's momentum analysis, offers a powerful approach to understanding market trends and momentum with a depth not available in traditional indicators.
Trend Identification and Momentum Analysis:
Traders can use the Kalman Filtered RSI Oscillator to identify strong trends and momentum shifts. The color-coded RSI columns provide immediate visual cues on the market's direction and strength, aiding in quick decision-making.
Optimal for Various Market Conditions:
The flexibility in tuning the Kalman filter parameters makes this indicator suitable for a wide range of assets and market conditions, from volatile to stable markets. Traders can adjust the settings based on empirical testing to find the optimal configuration for their trading strategy.
Complementary to Other Analytical Tools:
While powerful on its own, the Kalman Filtered RSI Oscillator is best used in conjunction with other analytical tools and indicators. Combining it with volume analysis, price action patterns, or other trend-following indicators can provide a comprehensive view of the market, allowing for more nuanced and informed trading decisions.
The Kalman Filtered RSI Oscillator is a groundbreaking tool that marries empirical precision with advanced trend analysis techniques. Its innovative use of the Kalman filter to enhance the RSI's performance offers traders an unparalleled ability to navigate the complexities of modern financial markets. Whether you're a novice looking to refine your trading approach or a seasoned professional seeking advanced analytical tools, the Kalman Filtered RSI Oscillator represents a significant step forward in technical analysis capabilities.
Thus following all of the key points here are some sample backtests on the 1D Chart
Disclaimer: Backtests are based off past results, and are not indicative of the future.
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
Kyrie Crossover ( @zaytradellc )Unlocking Market Dynamics: Kyrie Crossover Script by @zaytradellc
personalized trading success with the "Kyrie Crossover" script, meticulously crafted by @zaytrade. This innovative Pine Script, tailored to the birthdays of Kyrie and the script creator, combines the power of technical analysis with a touch of personalization to revolutionize your trading experience.
**Exponential Moving Average (EMA) Crossover Strategy:**
At the heart of the "Kyrie Crossover" script lies a sophisticated EMA crossover strategy. By utilizing a 10-period EMA and a 323-period EMA (symbolizing long term price action ), the strategy effectively captures market trends with precision and insight.
- **Short-Term EMA (10-period):** This EMA reacts swiftly to recent price changes, offering heightened sensitivity to short-term fluctuations. It excels in identifying immediate shifts in market sentiment, making it invaluable for pinpointing short-lived trends and potential reversal points.
- **Long-Term EMA (323-period):** In contrast, the long-term EMA provides a broader perspective by smoothing out short-term noise and focusing on longer-term trend direction. Its extended length filters out market noise effectively, providing a clear representation of the underlying trend's momentum and sustainability.
**Directional Movement Index (DMI) Metrics:**
The "Kyrie Crossover" script goes beyond traditional indicators by incorporating DMI metrics across multiple timeframes. By assessing trend strength and direction, traders gain valuable insights into market dynamics, allowing for informed decision-making.
**Simple Instructions to Profit:**
1. **Identify EMA Crossovers:** Look for instances where the short-term EMA (10-period) crosses above the long-term EMA (323-period) for a bullish signal, indicating a potential buying opportunity. Conversely, a crossover where the short-term EMA crosses below the long-term EMA signals a bearish trend and a potential selling opportunity.
2. **Confirm with DMI Metrics:** Validate EMA crossovers by checking DMI metrics across different timeframes (5 minutes, 15 minutes, 30 minutes, and 1 hour). Pay attention to color-coded indicators, with green indicating a bullish trend, red indicating a bearish trend, and white indicating no clear trend.
3. **Manage Risk:** Implement proper risk management techniques, such as setting stop-loss orders and position sizing based on your risk tolerance and trading objectives.
4. **Stay Informed:** Regularly monitor market conditions and adjust your trading strategy accordingly based on new signals and emerging trends.
Cauchy Distribution Trend AnalysisThis custom Pine Script indicator is designed to analyze assets, including cryptocurrencies, through a lens inspired by the Cauchy distribution's characteristics. It focuses on identifying potential long and short opportunities by evaluating the asset's price position relative to a dynamically calculated median price and a scale parameter. Here's a breakdown of its components and how to use it:
Components
Median Length: The period over which the median price is calculated. The median price acts as a proxy for the Cauchy distribution's location parameter, representing a central value around which the market price fluctuates.
MA Length: The length for calculating the moving average, which is used to determine the scale parameter. The scale parameter estimates the average volatility around the median price, adjusted for the selected averaging method.
Moving Average Type: Offers a choice between HMA (Hull Moving Average), SMA (Simple Moving Average), and EMA (Exponential Moving Average) to calculate the scale parameter. This flexibility allows users to tailor the sensitivity of the scale parameter to the asset's price volatility.
Median Price Calculation: Uses the close price (by default) to calculate the median price over the specified period.
Scale Parameter Calculation: A function that calculates the scale parameter based on the chosen average source. This parameter is used to identify the threshold for long and short conditions.
Strategy Logic
Long Condition: Triggered when the asset's close price is greater than the sum of the median price and the scale parameter. This indicates that the asset's price has moved significantly above the median price, suggesting bullish momentum.
Short Condition: Triggered when the asset's close price is less than the difference between the median price and the scale parameter. This indicates that the asset's price has moved significantly below the median price, suggesting bearish momentum.
Adaptive Fisher [BackQuant]Adaptive Fisher
What is it at its core:
Custom Kaufman Adaptive Moving Average Smoothed Price Data, Fisher Transformation.
Why did we choose to make an Adaptive Fisher ?
The Adaptive Fisher Transformation Indicator is an advanced technical tool designed to signal potential turning points in market prices by transforming asset price data into a nearly Gaussian normal distribution. This transformation, initially conceptualized by John F. Ehlers, aims to make extreme price behavior, which could indicate potential market reversals, more identifiable. Unlike the standard distribution of asset prices, the Gaussian normal distribution provides a clearer framework for identifying price extremes and trends.
With that being considered there are key things to take into consideration:
As the transformation seeks to normalize price data, it's crucial to remember that asset prices inherently do not follow a normal distribution. Thus, traders should use this tool in conjunction with other analyses to confirm potential trading signals. The effectiveness can vary across different assets and market conditions, underscoring the importance of customization and adaptation to specific trading strategies. As the same for all tools, all must be backtested. Past performance is not a guarantee for future results.
Now for the Key Features
Normalization of Prices: The Adaptive Fisher Transformation normalizes price data, enhancing the visibility of turning points. This normalization is critical for identifying moments when the price movement is statistically significant, thereby aiding in decision-making.
Adaptivity through Kaufman's Adaptive Moving Average (KAMA): Unlike traditional indicators, this version employs KAMA to dynamically adjust to market volatility. By doing so, it smoothens the price data more effectively, providing signals that are more responsive to current market conditions.
Divergence Detection: It includes the capability to detect divergences between the indicator and price movement, a powerful signal of potential trend reversals. Traders can specify the length over which divergences are calculated, allowing for customization based on their trading strategy.
Visual Enhancements: The indicator features color gradients to delineate strength levels and extreme values, improving readability and the quick assessment of market conditions.
Customizable Smoothing Mechanism: To accommodate different assets and timeframes, the indicator includes an option to select from various moving averages for smoothing, with an Exponential Moving Average (EMA) recommended for its effectiveness.
Application and Interpretation:
Traders can utilise this tool to identify potential reversal points by looking for extreme values in the transformed price data. Changes in the direction of the indicator can also signal shifts in market trends.
The inclusion of a normalized Relative Strength Index (RSI) provides additional confluence, aiding traders in recognizing overbought and oversold conditions through color-coded background hues in the chart.
Alert conditions are programmed for various scenarios, including trend shifts, Fisher Transform crossings over the midline, and both regular and hidden divergences, enabling traders to react promptly to potential market movements.
Empirical Soundness
Mathematical Foundation in Gaussian Distribution: At its core, the Fisher Transformation's application to financial markets is based on transforming prices to conform more closely to a Gaussian normal distribution, which is a fundamental concept in statistics. This transformation aims to make the identification of price extremes more reliable. Empirical studies have shown that while raw financial data may not follow a normal distribution, the application of transformations can facilitate the identification of critical turning points in market data (Ehlers, John F., "Cybernetic Analysis for Stocks and Futures", Wiley & Sons, 2004).
Adaptivity through KAMA: The use of Kaufman's Adaptive Moving Average introduces a dynamic element to the indicator, allowing it to adjust to market volatility automatically. This adaptivity is particularly relevant in today's financial markets, where volatility patterns can shift rapidly due to economic news, geopolitical events, and changes in market sentiment. The empirical strength of KAMA lies in its foundational logic, designed to account for market noise and smoothing price data more effectively than traditional moving averages (Kaufman, Perry J., "Trading Systems and Methods", Wiley & Sons, 2013).
Innovative Divergence Detection Mechanism: Divergence detection adds an empirical layer to the Adaptive Fisher Transformation by highlighting discrepancies between price action and the indicator's performance. This feature is grounded in the principle that divergences can often precede reversals, providing early warning signs of potential shifts in market direction. The ability to customize the calculation length for divergences enables the indicator to be fine-tuned to the characteristics of specific assets or market conditions, enhancing its practical application.
User Inputs Explained:
Calculation Source (price): This input determines the base price used for calculations, typically the closing price (close). Traders can adjust this to open, high, low, or another average, tailoring the indicator to focus on specific aspects of price action.
Fisher Lookback (ftPeriod): Defines the period over which the Fisher Transform is calculated. A shorter period makes the indicator more sensitive to price movements, while a longer period smoothens the output, reducing sensitivity.
Make Fisher Adaptive (adapt): A boolean input that enables the adaptation feature of the Fisher Transform using KAMA. When set to true, it dynamically adjusts the Fisher Transform according to market volatility, enhancing its responsiveness to recent price changes.
Adaptive Period (length), Fast Length (fast), Slow Length (slow): These inputs configure the KAMA calculation, affecting its sensitivity to price movements. The length determines the lookback period for volatility calculation, while fast and slow set the speed of adjustment to market conditions.
Smooth Fisher (smooth): Allows for additional smoothing of the Fisher Transform output to reduce noise. This is particularly useful in highly volatile markets or when the indicator is too reactive to price changes.
Smoothing Type (modeSwitch) and Smooth Period (smoothlen): Determine the method and period for smoothing. Options include various moving averages (EMA, SMA, etc.), providing flexibility in how the smoothing is applied.
Show Fisher, Show Fisher Moving Average, Moving Average Period (malen): These inputs control the visibility of the Fisher Transform and its moving average on the chart, as well as the period of the moving average. This helps in identifying trends and the direction of the market.
Show Detected Trend Shifts (trendshift): Enables the highlighting of moments when the indicator suggests a potential shift in market trend, providing early signals for traders.
Show Fisher Strength levels (showextreme): Displays predefined levels indicating extreme values of the Fisher Transform, which could suggest overbought or oversold conditions.
Show Confluence RSI (showrsi), RSI Period (rsiPeriod): These inputs add a normalized Relative Strength Index to the chart for additional analysis, offering a secondary measure of market conditions.
Show Overbought and Oversold Signals: When enabled, the background color changes to highlight overbought or oversold conditions based on the RSI, aiding in visual identification of potential trading opportunities.
Use Case of Midline Crossover Fisher:
Midline Crossover Fisher: The Fisher Transform's midline crossover is a critical signal for traders. A crossover above the midline indicates a bullish market sentiment, suggesting that it might be a good time to consider entering a long position. Conversely, a crossover below the midline suggests bearish sentiment, potentially signaling an opportunity to go short. This is based on the principle that the Fisher Transform makes turning points more evident, and crossing the midline reflects a change in momentum.
Overbought and Oversold Hues:
RSI Overbought and Oversold Background Color: The background color feature for RSI OB (overbought) and OS (oversold) conditions enhances visual cues for market extremes. When the RSI exceeds upper thresholds (Above 70), indicating overbought conditions, the background will turn to warn traders of potential price reversals. Similarly, when the RSI falls below lower thresholds (Below 30), suggesting oversold conditions, green can highlight potential opportunities for buying.
Thus following all of the key points here are some sample backtests on the 1D Chart
Disclaimer: Backtests are based off past results, and are not indicative of the future.
This is using the Midline Crossover:
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
