GKD-V Average Directional Index (ADX) [Loxx]Giga Kaleidoscope Average Directional Index (ADX) is a Volatility/Volume module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
█ Giga Kaleidoscope Modularized Trading System
What is Loxx's "Giga Kaleidoscope Modularized Trading System"?
The Giga Kaleidoscope Modularized Trading System is a trading system built on the philosophy of the NNFX (No Nonsense Forex) algorithmic trading.
What is 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.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v1.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data between modules. Data is passed between each module as described below:
GKD-B => GKD-V => GKD-C(1) => GKD-C(2) => GKD-C(Continuation) => GKD-E => GKD-BT
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Strategy with 1-3 take profits, trailing stop loss, multiple types of PnL volatility, and 2 backtesting styles
Baseline: Leader Exponential Moving Average
Volatility/Volume: Average Directional Index (ADX) as shown on the chart above
Confirmation 1: Double Smoothed Stochastic of Momentum
Confirmation 2: Jurik Turning Point Oscillator
Continuation: Fisher Transform
Exit: Rex Oscillator
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD protocol chain.
Giga Kaleidoscope Modularized Trading System Signals (based on the NNFX algorithm)
Standard Entry
1. GKD-C Confirmation 1 Signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
6. GKD-C Confirmation 1 signal was less than 7 candles prior
Continuation Entry
1. Standard Entry, Baseline Entry, or Pullback; entry triggered previously
2. GKD-B Baseline hasn't crossed since entry signal trigger
3. GKD-C Confirmation Continuation Indicator signals
4. GKD-C Confirmation 1 agrees
5. GKD-B Baseline agrees
6. GKD-C Confirmation 2 agrees
1-Candle Rule Standard Entry
1. GKD-C Confirmation 1 signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
1-Candle Rule Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 1 signal was less than 7 candles prior
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume Agrees
PullBack Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is beyond 1.0x Volatility of Baseline
Next Candle:
1. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume Agrees
█ Average Directional Index (ADX)
What is Average Directional Index (ADX)
Trading in the direction of a strong trend reduces risk and increases profit potential. The average directional index (ADX) is used to determine when the price is trending strongly. In many cases, it is the ultimate trend indicator. After all, the trend may be your friend, but it sure helps to know who your friends are.
ADX is used to quantify trend strength. ADX calculations are based on a moving average of price range expansion over a given period of time. The default setting is 14 bars, although other time periods can be used. ADX can be used on any trading vehicle such as stocks, mutual funds, exchange-traded funds and futures.
ADX is plotted as a single line with values ranging from a low of zero to a high of 100. ADX is non-directional; it registers trend strength whether price is trending up or down. The indicator is usually plotted in the same window as the two directional movement indicator (DMI) lines, but for our purposes here, we are only concerned with the ADX itself.
Signals
Traditional: ADX is above the threshold cutoff; both longs/shorts triggered when ADX is above the threshold cutoff
Crossing: ADX crosses above/below the threshold cutoff; longs or shorts are only valid on the candle where the cross happens. Both cross-ups and cross-downs are valid for both shorts and longs
Signal Modifiers
X-Bar Rule: If signals occur within XX bars, then the signal is still valid
Bars Rising: This is for traditional signals only. This requires that an upward slop of ADX be present over XX bars
Other things to note
The GKD trading system requires that a GKD-V indicator be present in the indicator chain, but the GKD-V indicator doesn't need to be active. You can turn on/off the Volatility Ratio as you wish so you can backtest your trading strategy with the filter on or off.
Additional features will be added in future releases.
This indicator is only available to ALGX Trading VIP group members . You can see the Author's Instructions below to get more information on how to get access.
Loxx
GKD-V Loxx Volty [Loxx]Giga Kaleidoscope Loxx Volty is a Volatility/Volume module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
█ Giga Kaleidoscope Modularized Trading System
What is Loxx's "Giga Kaleidoscope Modularized Trading System"?
The Giga Kaleidoscope Modularized Trading System is a trading system built on the philosophy of the NNFX (No Nonsense Forex) algorithmic trading.
What is 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.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v1.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data between modules. Data is passed between each module as described below:
GKD-B => GKD-V => GKD-C(1) => GKD-C(2) => GKD-C(Continuation) => GKD-E => GKD-BT
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Strategy with 1-3 take profits, trailing stop loss, multiple types of PnL volatility, and 2 backtesting styles
Baseline: Leader Exponential Moving Average
Volatility/Volume: Loxx Volty as shown on the chart above
Confirmation 1: Double Smoothed Stochastic of Momentum
Confirmation 2: Jurik Turning Point Oscillator
Continuation: Fisher Transform
Exit: Rex Oscillator
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD protocol chain.
Giga Kaleidoscope Modularized Trading System Signals (based on the NNFX algorithm)
Standard Entry
1. GKD-C Confirmation 1 Signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
6. GKD-C Confirmation 1 signal was less than 7 candles prior
Continuation Entry
1. Standard Entry, Baseline Entry, or Pullback; entry triggered previously
2. GKD-B Baseline hasn't crossed since entry signal trigger
3. GKD-C Confirmation Continuation Indicator signals
4. GKD-C Confirmation 1 agrees
5. GKD-B Baseline agrees
6. GKD-C Confirmation 2 agrees
1-Candle Rule Standard Entry
1. GKD-C Confirmation 1 signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
1-Candle Rule Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 1 signal was less than 7 candles prior
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume Agrees
PullBack Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is beyond 1.0x Volatility of Baseline
Next Candle:
1. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume Agrees
█ Loxx Volty
What is Loxx Volty
One of the lesser known qualities of Loxx smoothing is that the Loxx smoothing process is adaptive. "Loxx Volty" (a sort of market volatility) is what makes Loxx smoothing adaptive. The Loxx Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive.
Other things to note
The GKD trading system requires that a GKD-V indicator be present in the indicator chain, but the GKD-V indicator doesn't need to be active. You can turn on/off the Volatility Ratio as you wish so you can backtest your trading strategy with the filter on or off.
Additional features will be added in future releases.
This indicator is only available to ALGX Trading VIP group members . You can see the Author's Instructions below to get more information on how to get access.
GKD-V Finite Volume Elements [Loxx]Giga Kaleidoscope Finite Volume Elements is a Volatility/Volume module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
█ Giga Kaleidoscope Modularized Trading System
What is Loxx's "Giga Kaleidoscope Modularized Trading System"?
The Giga Kaleidoscope Modularized Trading System is a trading system built on the philosophy of the NNFX (No Nonsense Forex) algorithmic trading.
What is 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.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v1.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 5 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data between modules. Data is passed between each module as described below:
GKD-B => GKD-V => GKD-C(1) => GKD-C(2) => GKD-C(Continuation) => GKD-E => GKD-BT
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Strategy with 1-3 take profits, trailing stop loss, multiple types of PnL volatility, and 2 backtesting styles
Baseline: Leader Exponential Moving Average
Volatility/Volume: Finite Volume Elements as shown on the chart above
Confirmation 1: Double Smoothed Stochastic of Momentum
Confirmation 2: Jurik Turning Point Oscillator
Continuation: Fisher Transform
Exit: Rex Oscillator
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD protocol chain.
Giga Kaleidoscope Modularized Trading System Signals (based on the NNFX algorithm)
Standard Entry
1. GKD-C Confirmation 1 Signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
6. GKD-C Confirmation 1 signal was less than 7 candles prior
Continuation Entry
1. Standard Entry, Baseline Entry, or Pullback; entry triggered previously
2. GKD-B Baseline hasn't crossed since entry signal trigger
3. GKD-C Confirmation Continuation Indicator signals
4. GKD-C Confirmation 1 agrees
5. GKD-B Baseline agrees
6. GKD-C Confirmation 2 agrees
1-Candle Rule Standard Entry
1. GKD-C Confirmation 1 signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
1-Candle Rule Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 1 signal was less than 7 candles prior
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume Agrees
PullBack Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is beyond 1.0x Volatility of Baseline
Next Candle:
1. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume Agrees
█ Finite Volume Elements
What is Finite Volume Elements
The Finite Volume Element Indicator ( FVE ) was developed by Markos Katsanos and introduced in the April 2003 issue of Technical Analysis of Stocks & Commodities magazine. It was modified for volatility in the September 2003 issue of TASC.
FVE is a money flow indicator but with two important differences from existing money flow indicators:
It resolves contradictions between intraday money flow indicators (such as Chaikin’s money flow ) and intraday money flow indicators (like On Balance Volume ) by taking into account both intra- and intraday price action.
Unlike other money flow indicators which add or subtract all volume even if the security closed just 1 cent higher than the previous close, FVE uses a volatility threshold to take into account minimal price changes
Other things to note
The GKD trading system requires that a GKD-V indicator be present in the indicator chain, but the GKD-V indicator doesn't need to be active. You can turn on/off the Volatility Ratio as you wish so you can backtest your trading strategy with the filter on or off.
Additional features will be added in future releases.
This indicator is only available to ALGX Trading VIP group members . You can see the Author's Instructions below to get more information on how to get access.
GKD-C Double Smoothed Stochastic of Momentum [Loxx]Giga Kaleidoscope Double Smoothed Stochastic of Momentum Confirmation is a Confirmation module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
What is Loxx's "Giga Kaleidoscope Modularized Trading System"?
The Giga Kaleidoscope Modularized Trading System is a trading system built on the philosophy of the NNFX (No Nonsense Forex) algorithmic trading.
What is 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 (such as "Baseline" shown on the chart above)
3. Confirmation 1 - a technical indicator used to identify trends. This should agree with the "Baseline"
4. Confirmation 2 - a technical indicator used to identify trends. This filters/verifies the trend identified by "Baseline" and "Confirmation 1"
5. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown.
6. Exit - a technical indicator used to determine when a trend is exhausted.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v1.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 module (Confirmation 1/2, Numbers 3 and 4 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 5 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 6 in the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data between modules. Data is passed between each module as described below:
GKD-B => GKD-V => GKD-C(1) => GKD-C(2) => GKD-E => GKD-BT
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Strategy with 1-3 take profits, trailing stop loss, multiple types of PnL volatility, and 2 backtesting styles
Baseline: Leader Exponential Moving Average as shown on chart
Volatility/Volume: Volatility Ratio as shown on chart
Confirmation 1: Double Smoothed Stochastic of Momentum as shown on the chart above
Confirmation 2: Jurik Turning Point Oscillator
Exit: Rex Oscillator
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD protocol chain.
Now that you have a general understanding of the NNFX algorithm and the GKD trading system. Let's go over what's inside the GKD-E Double Smoothed Stochastic of Momentum itself.
What is Double Smoothed Stochastic of Momentum?
The Double Smoothed Stochastic of Momentum demonstrates smoother indicators and therefore gives fewer false signals in comparison with the traditional oscillator.
The indicator is written in accordance with the description given in the book by Joe Dinapoli "Trading With DiNapoli Levels". This oscillator smoothing method leads to a filtering of the most "noise" component of the price movement.
The Double Smoothed Stochastic of Momentum indicator can be used in the strategies oriented to a standard stochastic. However, the stronger smoothing can lead to the loss of an array of signals. It is recommended to apply any trend indicator for more efficient use of the indicator and its signals filtering.
Signals
A GKD-C Confirmation indicator can be used as either a Confirmation 1, Confirmation 2, or Solo Confirmation indicator. See step 3 & 4 of the NNFX algorithm above to understand how this indicator fits into the GKD trading system. The Solo Confirmation setting allows you to test this indicator by itself without an additional GKD-C indicator present in the GKD protocol chain.
On the chart shown above, this indicator is shown as GKD-C Double Smoothed Stochastic of Momentum and is set to Solo Confirmation. The GKD-B Baseline, GKD-V Volatility Ratio, and this indicator satisfy the first three steps in the GKD trading system chain: GKD-B => GKD-V => GKD-C(solo).
The signals from each of these settings are as follows:
Confirmation 1 Signal
Initial Long (L): Double Smoothed Stochastic of Momentum crosses-up over middle-line*
Initial Short (S): Double Smoothed Stochastic of Momentum crosses-down under middle-line*
Continuation Long (CL): Double Smoothed Stochastic of Momentum is over middle-line, then crosses-up over the signal**
Continuation Short (CS): Double Smoothed Stochastic of Momentum is under middle-line, then crosses-down under the signal**
Post Baseline Cross Long (BL): Double Smoothed Stochastic of Momentum crossed-up over middle-line but Baseline is still in downtrend, then Baseline turns to uptrend within XX bars***
Post Baseline Cross Short (BS): Double Smoothed Stochastic of Momentum crossed-down under middle-line but Baseline is still in uptrend, then Baseline turns to downtrend within XX bars***
BL Recovery Continuation Long (RL): Double Smoothed Stochastic of Momentum is above middle-line. Baseline already crossed down into downtrend, then baseline crosses back up to uptrend; then, Double Smoothed Stochastic of Momentum crosses-up over the signal****
BL Recovery Continuation Short (RS): Double Smoothed Stochastic of Momentum is below middle-line. Baseline already crossed up into uptrend, then baseline crosses back down to downtrend; then, Double Smoothed Stochastic of Momentum crosses-down under the signal****
*All signals are shown regardless of Baseline and Volatility/Volume qualification
**All signals are shown regardless of Baseline qualification; however, when Baseline filter is active, only true continuations are shown. When the Baseline filter is not active, then all continuations are shown. True continuations are when the Baseline is active and maintains its uptrend/downtrend after the initial cross-up/cross-down over the middle-line respectively. This means that if the Baseline trend then moves against the Double Smoothed Stochastic of Momentum then any continuation signals are voided until another initial Long/Short. All continuations are will either show as regular continuations or be converted into recovery continuations
***All signals are shown regardless of Volatility/Volume qualification
****When the Baseline filter is active, some regular continuations are converted to recovery continuations and are shown. When the Baseline filter is not active, then these signals are not shown.
Confirmation 2 Signal
Initial Long (L): Double Smoothed Stochastic of Momentum crosses-up over middle-line*
Initial Short (S): Double Smoothed Stochastic of Momentum crosses-down under middle-line*
Continuation Long (CL): Double Smoothed Stochastic of Momentum is over middle-line, then crosses-up over the signal**
Continuation Short (CS): Double Smoothed Stochastic of Momentum is under middle-line, then crosses-down under the signal**
Post Baseline Cross Long (BL): Double Smoothed Stochastic of Momentum crossed-up over middle-line but Baseline is still in downtrend, then Baseline turns to uptrend within XX bars***
Post Baseline Cross Short (BS): Double Smoothed Stochastic of Momentum crossed-down under middle-line but Baseline is still in uptrend, then Baseline turns to downtrend within XX bars***
BL Recovery Continuation Long (RL): Double Smoothed Stochastic of Momentum is above middle-line. Baseline already crossed down into downtrend, then baseline crosses back up to uptrend while Double Smoothed Stochastic of Momentum is still above middle-line; then, Double Smoothed Stochastic of Momentum crosses-up over the signal****
BL Recovery Continuation Short (RS): Double Smoothed Stochastic of Momentum is below middle-line. Baseline already crossed up into uptrend, then baseline crosses back down to downtrend while Double Smoothed Stochastic of Momentum is still below middle-line; then, Double Smoothed Stochastic of Momentum crosses-down under the signal****
*All signals are shown regardless of Baseline and Volatility/Volume qualification
**All signals are shown regardless of Baseline qualification; however, when Baseline filter is active, only true continuations are shown. When the Baseline filter is not active, then all continuations are shown. True continuations are when the Baseline is active and maintains its uptrend/downtrend after the initial cross-up/cross-down over the middle-line respectively. This means that if the Baseline trend then moves against the Double Smoothed Stochastic of Momentum then any continuation signals are voided until another initial Long/Short. All continuations are will either show as regular continuations or be converted into recovery continuations
***All signals are shown regardless of Volatility/Volume qualification
****When the Baseline filter is active, some regular continuations are converted to recovery continuations and are shown. When the Baseline filter is not active, then these signals are not shown.
Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
Initial Long (L): The imported GKD-C Confirmation 1 indicator crosses-up over middle-line, then Double Smoothed Stochastic of Momentum crosses-up over the middle-line on the same bar or "Number of Bars Confirmation" bars in the future (see X-bar rule below)
Initial Short (S): The imported GKD-C Confirmation 1 indicator crosses-down under middle-line, then Double Smoothed Stochastic of Momentum crosses-down under the middle-line on the same bar or "Number of Bars Confirmation" bars in the future (see X-bar rule below)
Continuation Long Confirmation 1 (CL): The imported GKD-C Confirmation 1 indicator is over middle-line, then crosses-up over the signal
Continuation Short Confirmation 1 (CS): The imported GKD-C Confirmation 1 indicator is under middle-line, then crosses-down under the signal
Post Baseline Cross Long (BL): The imported GKD-C Confirmation 1 crossed-up over middle-line but Baseline is still in downtrend; and Double Smoothed Stochastic of Momentum crossed-up over middle-line on the same bar or XX bars in the future but Baseline is still in downtrend; then Baseline turns to uptrend within "Maximum Allowable PSBC Bars Back" bars (see X-bar rule below)
Post Baseline Cross Short (BS): The imported GKD-C Confirmation 1 crossed-down under middle-line but Baseline is still in uptrend; and, Double Smoothed Stochastic of Momentum crossed-down under middle-line on the same bar or XX bars in the future but Baseline is still in uptrend; then Baseline turns to downtrend within "Maximum Allowable PSBC Bars Back" bars (see X-bar rule below)
BL Recovery Continuation Long (RL): The imported GKD-C Confirmation 1 indicator is above middle-line. Baseline already crossed down into downtrend, then baseline crosses back up to uptrend while Double Smoothed Stochastic of Momentum is still above middle-line; then, The imported GKD-C Confirmation 1 crosses-up over the signal
BL Recovery Continuation Short (RS): The imported GKD-C Confirmation 1 indicator is below middle-line. Baseline already crossed up into uptrend, then baseline crosses back down to downtrend while Double Smoothed Stochastic of Momentum is still below middle-line; then, The imported GKD-C Confirmation 1 crosses-down under the signal
Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 2
Initial Long (L): same as Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
Initial Short (S): same as Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
Continuation Long Confirmation 2 (CL): Double Smoothed Stochastic of Momentum is over middle-line, then crosses-up over the signal
Continuation Short Confirmation 2 (CS): Double Smoothed Stochastic of Momentum is under middle-line, then crosses-down under the signal
Post Baseline Cross Long (BL): same as Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
Post Baseline Cross Short (BS): same as Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
BL Recovery Continuation Long (RL): Double Smoothed Stochastic of Momentum is above middle-line. Baseline already crossed down into downtrend, then baseline crosses back up to uptrend; then, Double Smoothed Stochastic of Momentum crosses-up over the signal
BL Recovery Continuation Short (RS): Double Smoothed Stochastic of Momentum is below middle-line. Baseline already crossed up into uptrend, then baseline crosses back down to downtrend; then, Double Smoothed Stochastic of Momentum crosses-down under the signal
Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Both
Initial Long (L): same as Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
Initial Short (S): same as Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
Continuation Long Confirmation 2 (CL): The imported GKD-C Confirmation 1 indicator is over middle-line, then crosses-up over the signal; Double Smoothed Stochastic of Momentum is over middle-line, then crosses-up over the signal within "Number of Bars Confirmation" bars in the future
Continuation Short Confirmation 2 (CS): The imported GKD-C Confirmation 1 indicator is under middle-line, then crosses-down under the signal; Double Smoothed Stochastic of Momentum is under middle-line, then crosses-down under the signal within "Number of Bars Confirmation" bars in the future
Post Baseline Cross Long (BL): same as Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
Post Baseline Cross Short (BS): same as Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
BL Recovery Continuation Long (RL): The imported GKD-C Confirmation 1 indicator is above middle-line and Double Smoothed Stochastic of Momentum is above middle-line. Baseline already crossed down into downtrend, then baseline crosses back up to uptrend; then, the imported GKD-C Confirmation 1 crosses-up over its signal, and Double Smoothed Stochastic of Momentum crosses-up over its signal within "Number of Bars Confirmation" bars in the future
BL Recovery Continuation Short (RS): The imported GKD-C Confirmation 1 indicator is below middle-line and Double Smoothed Stochastic of Momentum is below middle-line. Baseline already crossed up into uptrend, then baseline crosses back down to downtrend; then, the imported GKD-C Confirmation 1 crosses-down under its signal, and Double Smoothed Stochastic of Momentum crosses-down under its signal within "Number of Bars Confirmation" bars in the future
Confirmation 2 Confluence Background Color Signals; Confirmation Order: Both; Confirmation Type: (continuations don't change from the variations above)
Initial Long (L): The imported GKD-C Confirmation 1 indicator crosses-up over middle-line, then Double Smoothed Stochastic of Momentum crosses-up over the middle-line on the same bar or "Number of Bars Confirmation" bars in the future (see X-bar rule below); OR, Double Smoothed Stochastic of Momentum crosses-up over middle-line, then the imported GKD-C Confirmation 1 indicator crosses-up over the middle-line on the same bar or "Number of Bars Confirmation" bars in the future (see X-bar rule below)
Initial Short (S): The imported GKD-C Confirmation 1 indicator crosses-down under middle-line, then Double Smoothed Stochastic of Momentum crosses-down under the middle-line on the same bar or "Number of Bars Confirmation" bars in the future (see X-bar rule below); OR, Double Smoothed Stochastic of Momentum crosses-down under middle-line, then the imported GKD-C Confirmation 1 indicator crosses-down under the middle-line on the same bar or "Number of Bars Confirmation" bars in the future (see X-bar rule below)
Post Baseline Cross Long (BL): The imported GKD-C Confirmation 1 crossed-down under middle-line but Baseline is still in uptrend; and, Double Smoothed Stochastic of Momentum crossed-down under middle-line on the same bar or XX bars in the future but Baseline is still in uptrend; then Baseline turns to downtrend within "Maximum Allowable PSBC Bars Back" bars (see X-bar rule below); OR, Double Smoothed Stochastic of Momentum crossed-down under middle-line but Baseline is still in uptrend; and, the imported GKD-C Confirmation 1 crossed-down under middle-line on the same bar or XX bars in the future but Baseline is still in uptrend; then Baseline turns to downtrend within "Maximum Allowable PSBC Bars Back" bars (see X-bar rule below)
Post Baseline Cross Short (BS): The imported GKD-C Confirmation 1 crossed-down under middle-line but Baseline is still in uptrend; and, Double Smoothed Stochastic of Momentum crossed-down under middle-line on the same bar or XX bars in the future but Baseline is still in uptrend; then Baseline turns to downtrend within "Maximum Allowable PSBC Bars Back" bars (see X-bar rule below); OR, Double Smoothed Stochastic of Momentum crossed-down under middle-line but Baseline is still in uptrend; and, the imported GKD-C Confirmation 1 crossed-down under middle-line on the same bar or XX bars in the future but Baseline is still in uptrend; then Baseline turns to downtrend within "Maximum Allowable PSBC Bars Back" bars (see X-bar rule below)
Solo Confirmation Signals
Initial Long (L): Double Smoothed Stochastic of Momentum crosses-up over middle-line
Initial Short (S): Double Smoothed Stochastic of Momentum crosses-down under middle-line
Continuation Long (CL): Double Smoothed Stochastic of Momentum is over middle-line, then crosses-up over the signal
Continuation Short (CS): Double Smoothed Stochastic of Momentum is under middle-line, then crosses-down under the signal
Post Baseline Cross Long (BL): Double Smoothed Stochastic of Momentum crossed-up over middle-line but Baseline is still in downtrend, then Baseline turns to uptrend within XX bars
Post Baseline Cross Short (BS): Double Smoothed Stochastic of Momentum crossed-down under middle-line but Baseline is still in uptrend, then Baseline turns to downtrend within XX bars
BL Recovery Continuation Long (RL): Double Smoothed Stochastic of Momentum above middle-line. Baseline already crossed down into downtrend, then baseline crosses back up to uptrend while Double Smoothed Stochastic of Momentum is still above middle-line
BL Recovery Continuation Short (RS): Double Smoothed Stochastic of Momentum below middle-line. Baseline already crossed up into uptrend, then baseline crosses back down to downtrend while Double Smoothed Stochastic of Momentum is still below middle-line
X-bar Rule settings
This rule only applies when this indicator "Confirmation Type" set to "Confirmation 2"
Requirements
Inputs: Confirmation 1 and Solo Confirmation: GKD-V Volatility/Volume indicator; Confirmation 2: GKD-C Confirmation indicator
Output: Confirmation 2 and Solo Confirmation: GKD-E Exit indicator; Confirmation 1: GKD-C Confirmation indicator
Additional features will be added in future releases.
This indicator is only available to ALGX Trading VIP group members . You can see the Author's Instructions below to get more information on how to get access.
GKD-C Double Smoothed Stochastic [Loxx]Giga Kaleidoscope Double Smoothed Stochastic Confirmation is a Confirmation module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
What is Loxx's "Giga Kaleidoscope Modularized Trading System"?
The Giga Kaleidoscope Modularized Trading System is a trading system built on the philosophy of the NNFX (No Nonsense Forex) algorithmic trading.
What is 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 (such as "Baseline" shown on the chart above)
3. Confirmation 1 - a technical indicator used to identify trends. This should agree with the "Baseline"
4. Confirmation 2 - a technical indicator used to identify trends. This filters/verifies the trend identified by "Baseline" and "Confirmation 1"
5. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown.
6. Exit - a technical indicator used to determine when a trend is exhausted.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v1.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 module (Confirmation 1/2, Numbers 3 and 4 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 5 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 6 in the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data between modules. Data is passed between each module as described below:
GKD-B => GKD-V => GKD-C(1) => GKD-C(2) => GKD-E => GKD-BT
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Strategy with 1-3 take profits, trailing stop loss, multiple types of PnL volatility, and 2 backtesting styles
Baseline: Leader Exponential Moving Average as shown on chart
Volatility/Volume: Volatility Ratio as shown on chart
Confirmation 1: Double Smoothed Stochastic as shown on the chart above
Confirmation 2: Jurik Turning Point Oscillator
Exit: Rex Oscillator
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD protocol chain.
Now that you have a general understanding of the NNFX algorithm and the GKD trading system. Let's go over what's inside the GKD-E Double Smoothed Stochastic itself.
What is Double Smoothed Stochastic?
The Double Smoothed Stochastic demonstrates smoother indicators and therefore gives fewer false signals in comparison with the traditional oscillator.
The indicator is written in accordance with the description given in the book by Joe Dinapoli "Trading With DiNapoli Levels". This oscillator smoothing method leads to a filtering of the most "noise" component of the price movement.
The Double Smoothed Stochastic indicator can be used in the strategies oriented to a standard stochastic. However, the stronger smoothing can lead to the loss of an array of signals. It is recommended to apply any trend indicator for more efficient use of the indicator and its signals filtering.
Signals
A GKD-C Confirmation indicator can be used as either a Confirmation 1, Confirmation 2, or Solo Confirmation indicator. See step 3 & 4 of the NNFX algorithm above to understand how this indicator fits into the GKD trading system. The Solo Confirmation setting allows you to test this indicator by itself without an additional GKD-C indicator present in the GKD protocol chain.
On the chart shown above, this indicator is shown as GKD-C Double Smoothed Stochastic and is set to Solo Confirmation. The GKD-B Baseline, GKD-V Volatility Ratio, and this indicator satisfy the first three steps in the GKD trading system chain: GKD-B => GKD-V => GKD-C(solo).
The signals from each of these settings are as follows:
Confirmation 1 Signal
Initial Long (L): Double Smoothed Stochastic crosses-up over middle-line*
Initial Short (S): Double Smoothed Stochastic crosses-down under middle-line*
Continuation Long (CL): Double Smoothed Stochastic is over middle-line, then crosses-up over the signal**
Continuation Short (CS): Double Smoothed Stochastic is under middle-line, then crosses-down under the signal**
Post Baseline Cross Long (BL): Double Smoothed Stochastic crossed-up over middle-line but Baseline is still in downtrend, then Baseline turns to uptrend within XX bars***
Post Baseline Cross Short (BS): Double Smoothed Stochastic crossed-down under middle-line but Baseline is still in uptrend, then Baseline turns to downtrend within XX bars***
BL Recovery Continuation Long (RL): Double Smoothed Stochastic is above middle-line. Baseline already crossed down into downtrend, then baseline crosses back up to uptrend; then, Double Smoothed Stochastic crosses-up over the signal****
BL Recovery Continuation Short (RS): Double Smoothed Stochastic is below middle-line. Baseline already crossed up into uptrend, then baseline crosses back down to downtrend; then, Double Smoothed Stochastic crosses-down under the signal****
*All signals are shown regardless of Baseline and Volatility/Volume qualification
**All signals are shown regardless of Baseline qualification; however, when Baseline filter is active, only true continuations are shown. When the Baseline filter is not active, then all continuations are shown. True continuations are when the Baseline is active and maintains its uptrend/downtrend after the initial cross-up/cross-down over the middle-line respectively. This means that if the Baseline trend then moves against the Double Smoothed Stochastic then any continuation signals are voided until another initial Long/Short. All continuations are will either show as regular continuations or be converted into recovery continuations
***All signals are shown regardless of Volatility/Volume qualification
****When the Baseline filter is active, some regular continuations are converted to recovery continuations and are shown. When the Baseline filter is not active, then these signals are not shown.
Confirmation 2 Signal
Initial Long (L): Double Smoothed Stochastic crosses-up over middle-line*
Initial Short (S): Double Smoothed Stochastic crosses-down under middle-line*
Continuation Long (CL): Double Smoothed Stochastic is over middle-line, then crosses-up over the signal**
Continuation Short (CS): Double Smoothed Stochastic is under middle-line, then crosses-down under the signal**
Post Baseline Cross Long (BL): Double Smoothed Stochastic crossed-up over middle-line but Baseline is still in downtrend, then Baseline turns to uptrend within XX bars***
Post Baseline Cross Short (BS): Double Smoothed Stochastic crossed-down under middle-line but Baseline is still in uptrend, then Baseline turns to downtrend within XX bars***
BL Recovery Continuation Long (RL): Double Smoothed Stochastic is above middle-line. Baseline already crossed down into downtrend, then baseline crosses back up to uptrend while Double Smoothed Stochastic is still above middle-line; then, Double Smoothed Stochastic crosses-up over the signal****
BL Recovery Continuation Short (RS): Double Smoothed Stochastic is below middle-line. Baseline already crossed up into uptrend, then baseline crosses back down to downtrend while Double Smoothed Stochastic is still below middle-line; then, Double Smoothed Stochastic crosses-down under the signal****
*All signals are shown regardless of Baseline and Volatility/Volume qualification
**All signals are shown regardless of Baseline qualification; however, when Baseline filter is active, only true continuations are shown. When the Baseline filter is not active, then all continuations are shown. True continuations are when the Baseline is active and maintains its uptrend/downtrend after the initial cross-up/cross-down over the middle-line respectively. This means that if the Baseline trend then moves against the Double Smoothed Stochastic then any continuation signals are voided until another initial Long/Short. All continuations are will either show as regular continuations or be converted into recovery continuations
***All signals are shown regardless of Volatility/Volume qualification
****When the Baseline filter is active, some regular continuations are converted to recovery continuations and are shown. When the Baseline filter is not active, then these signals are not shown.
Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
Initial Long (L): The imported GKD-C Confirmation 1 indicator crosses-up over middle-line, then Double Smoothed Stochastic crosses-up over the middle-line on the same bar or "Number of Bars Confirmation" bars in the future (see X-bar rule below)
Initial Short (S): The imported GKD-C Confirmation 1 indicator crosses-down under middle-line, then Double Smoothed Stochastic crosses-down under the middle-line on the same bar or "Number of Bars Confirmation" bars in the future (see X-bar rule below)
Continuation Long Confirmation 1 (CL): The imported GKD-C Confirmation 1 indicator is over middle-line, then crosses-up over the signal
Continuation Short Confirmation 1 (CS): The imported GKD-C Confirmation 1 indicator is under middle-line, then crosses-down under the signal
Post Baseline Cross Long (BL): The imported GKD-C Confirmation 1 crossed-up over middle-line but Baseline is still in downtrend; and Double Smoothed Stochastic crossed-up over middle-line on the same bar or XX bars in the future but Baseline is still in downtrend; then Baseline turns to uptrend within "Maximum Allowable PSBC Bars Back" bars (see X-bar rule below)
Post Baseline Cross Short (BS): The imported GKD-C Confirmation 1 crossed-down under middle-line but Baseline is still in uptrend; and, Double Smoothed Stochastic crossed-down under middle-line on the same bar or XX bars in the future but Baseline is still in uptrend; then Baseline turns to downtrend within "Maximum Allowable PSBC Bars Back" bars (see X-bar rule below)
BL Recovery Continuation Long (RL): The imported GKD-C Confirmation 1 indicator is above middle-line. Baseline already crossed down into downtrend, then baseline crosses back up to uptrend while Double Smoothed Stochastic is still above middle-line; then, The imported GKD-C Confirmation 1 crosses-up over the signal
BL Recovery Continuation Short (RS): The imported GKD-C Confirmation 1 indicator is below middle-line. Baseline already crossed up into uptrend, then baseline crosses back down to downtrend while Double Smoothed Stochastic is still below middle-line; then, The imported GKD-C Confirmation 1 crosses-down under the signal
Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 2
Initial Long (L): same as Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
Initial Short (S): same as Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
Continuation Long Confirmation 2 (CL): Double Smoothed Stochastic is over middle-line, then crosses-up over the signal
Continuation Short Confirmation 2 (CS): Double Smoothed Stochastic is under middle-line, then crosses-down under the signal
Post Baseline Cross Long (BL): same as Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
Post Baseline Cross Short (BS): same as Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
BL Recovery Continuation Long (RL): Double Smoothed Stochastic is above middle-line. Baseline already crossed down into downtrend, then baseline crosses back up to uptrend; then, Double Smoothed Stochastic crosses-up over the signal
BL Recovery Continuation Short (RS): Double Smoothed Stochastic is below middle-line. Baseline already crossed up into uptrend, then baseline crosses back down to downtrend; then, Double Smoothed Stochastic crosses-down under the signal
Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Both
Initial Long (L): same as Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
Initial Short (S): same as Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
Continuation Long Confirmation 2 (CL): The imported GKD-C Confirmation 1 indicator is over middle-line, then crosses-up over the signal; Double Smoothed Stochastic is over middle-line, then crosses-up over the signal within "Number of Bars Confirmation" bars in the future
Continuation Short Confirmation 2 (CS): The imported GKD-C Confirmation 1 indicator is under middle-line, then crosses-down under the signal; Double Smoothed Stochastic is under middle-line, then crosses-down under the signal within "Number of Bars Confirmation" bars in the future
Post Baseline Cross Long (BL): same as Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
Post Baseline Cross Short (BS): same as Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
BL Recovery Continuation Long (RL): The imported GKD-C Confirmation 1 indicator is above middle-line and Double Smoothed Stochastic is above middle-line. Baseline already crossed down into downtrend, then baseline crosses back up to uptrend; then, the imported GKD-C Confirmation 1 crosses-up over its signal, and Double Smoothed Stochastic crosses-up over its signal within "Number of Bars Confirmation" bars in the future
BL Recovery Continuation Short (RS): The imported GKD-C Confirmation 1 indicator is below middle-line and Double Smoothed Stochastic is below middle-line. Baseline already crossed up into uptrend, then baseline crosses back down to downtrend; then, the imported GKD-C Confirmation 1 crosses-down under its signal, and Double Smoothed Stochastic crosses-down under its signal within "Number of Bars Confirmation" bars in the future
Confirmation 2 Confluence Background Color Signals; Confirmation Order: Both; Confirmation Type: (continuations don't change from the variations above)
Initial Long (L): The imported GKD-C Confirmation 1 indicator crosses-up over middle-line, then Double Smoothed Stochastic crosses-up over the middle-line on the same bar or "Number of Bars Confirmation" bars in the future (see X-bar rule below); OR, Double Smoothed Stochastic crosses-up over middle-line, then the imported GKD-C Confirmation 1 indicator crosses-up over the middle-line on the same bar or "Number of Bars Confirmation" bars in the future (see X-bar rule below)
Initial Short (S): The imported GKD-C Confirmation 1 indicator crosses-down under middle-line, then Double Smoothed Stochastic crosses-down under the middle-line on the same bar or "Number of Bars Confirmation" bars in the future (see X-bar rule below); OR, Double Smoothed Stochastic crosses-down under middle-line, then the imported GKD-C Confirmation 1 indicator crosses-down under the middle-line on the same bar or "Number of Bars Confirmation" bars in the future (see X-bar rule below)
Post Baseline Cross Long (BL): The imported GKD-C Confirmation 1 crossed-down under middle-line but Baseline is still in uptrend; and, Double Smoothed Stochastic crossed-down under middle-line on the same bar or XX bars in the future but Baseline is still in uptrend; then Baseline turns to downtrend within "Maximum Allowable PSBC Bars Back" bars (see X-bar rule below); OR, Double Smoothed Stochastic crossed-down under middle-line but Baseline is still in uptrend; and, the imported GKD-C Confirmation 1 crossed-down under middle-line on the same bar or XX bars in the future but Baseline is still in uptrend; then Baseline turns to downtrend within "Maximum Allowable PSBC Bars Back" bars (see X-bar rule below)
Post Baseline Cross Short (BS): The imported GKD-C Confirmation 1 crossed-down under middle-line but Baseline is still in uptrend; and, Double Smoothed Stochastic crossed-down under middle-line on the same bar or XX bars in the future but Baseline is still in uptrend; then Baseline turns to downtrend within "Maximum Allowable PSBC Bars Back" bars (see X-bar rule below); OR, Double Smoothed Stochastic crossed-down under middle-line but Baseline is still in uptrend; and, the imported GKD-C Confirmation 1 crossed-down under middle-line on the same bar or XX bars in the future but Baseline is still in uptrend; then Baseline turns to downtrend within "Maximum Allowable PSBC Bars Back" bars (see X-bar rule below)
Solo Confirmation Signals
Initial Long (L): Double Smoothed Stochastic crosses-up over middle-line
Initial Short (S): Double Smoothed Stochastic crosses-down under middle-line
Continuation Long (CL): Double Smoothed Stochastic is over middle-line, then crosses-up over the signal
Continuation Short (CS): Double Smoothed Stochastic is under middle-line, then crosses-down under the signal
Post Baseline Cross Long (BL): Double Smoothed Stochastic crossed-up over middle-line but Baseline is still in downtrend, then Baseline turns to uptrend within XX bars
Post Baseline Cross Short (BS): Double Smoothed Stochastic crossed-down under middle-line but Baseline is still in uptrend, then Baseline turns to downtrend within XX bars
BL Recovery Continuation Long (RL): Double Smoothed Stochastic above middle-line. Baseline already crossed down into downtrend, then baseline crosses back up to uptrend while Double Smoothed Stochastic is still above middle-line
BL Recovery Continuation Short (RS): Double Smoothed Stochastic below middle-line. Baseline already crossed up into uptrend, then baseline crosses back down to downtrend while Double Smoothed Stochastic is still below middle-line
X-bar Rule settings
This rule only applies when this indicator "Confirmation Type" set to "Confirmation 2"
Requirements
Inputs: Confirmation 1 and Solo Confirmation: GKD-V Volatility/Volume indicator; Confirmation 2: GKD-C Confirmation indicator
Output: Confirmation 2 and Solo Confirmation: GKD-E Exit indicator; Confirmation 1: GKD-C Confirmation indicator
Additional features will be added in future releases.
This indicator is only available to ALGX Trading VIP group members . You can see the Author's Instructions below to get more information on how to get access.
GKD-C DiNapoli Stochastic [Loxx]Giga Kaleidoscope DiNapoli Stochastic Confirmation is a Confirmation module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
What is Loxx's "Giga Kaleidoscope Modularized Trading System"?
The Giga Kaleidoscope Modularized Trading System is a trading system built on the philosophy of the NNFX (No Nonsense Forex) algorithmic trading.
What is 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 (such as "Baseline" shown on the chart above)
3. Confirmation 1 - a technical indicator used to identify trends. This should agree with the "Baseline"
4. Confirmation 2 - a technical indicator used to identify trends. This filters/verifies the trend identified by "Baseline" and "Confirmation 1"
5. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown.
6. Exit - a technical indicator used to determine when a trend is exhausted.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v1.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 module (Confirmation 1/2, Numbers 3 and 4 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 5 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 6 in the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data between modules. Data is passed between each module as described below:
GKD-B => GKD-V => GKD-C(1) => GKD-C(2) => GKD-E => GKD-BT
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Strategy with 1-3 take profits, trailing stop loss, multiple types of PnL volatility, and 2 backtesting styles
Baseline: Leader Exponential Moving Average as shown on chart
Volatility/Volume: Volatility Ratio as shown on chart
Confirmation 1: DiNapoli Stochastic as shown on the chart above
Confirmation 2: Jurik Turning Point Oscillator
Exit: Rex Oscillator
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD protocol chain.
Now that you have a general understanding of the NNFX algorithm and the GKD trading system. Let's go over what's inside the GKD-E DiNapoli Stochastic itself.
What is DiNapoli Stochastic?
The DiNapoli Stochastic demonstrates smoother indicators and therefore gives fewer false signals in comparison with the traditional oscillator.
The indicator is written in accordance with the description given in the book by Joe Dinapoli "Trading With DiNapoli Levels". This oscillator smoothing method leads to a filtering of the most "noise" component of the price movement.
The DiNapoli Stochastic indicator can be used in the strategies oriented to a standard stochastic. However, the stronger smoothing can lead to the loss of an array of signals. It is recommended to apply any trend indicator for more efficient use of the indicator and its signals filtering.
Signals
A GKD-C Confirmation indicator can be used as either a Confirmation 1, Confirmation 2, or Solo Confirmation indicator. See step 3 & 4 of the NNFX algorithm above to understand how this indicator fits into the GKD trading system. The Solo Confirmation setting allows you to test this indicator by itself without an additional GKD-C indicator present in the GKD protocol chain.
On the chart shown above, this indicator is shown as GKD-C DiNapoli Stochastic and is set to Solo Confirmation. The GKD-B Baseline, GKD-V Volatility Ratio, and this indicator satisfy the first three steps in the GKD trading system chain: GKD-B => GKD-V => GKD-C(solo).
The signals from each of these settings are as follows:
Confirmation 1 Signal
Initial Long (L): DiNapoli Stochastic crosses-up over middle-line*
Initial Short (S): DiNapoli Stochastic crosses-down under middle-line*
Continuation Long (CL): DiNapoli Stochastic is over middle-line, then crosses-up over the signal**
Continuation Short (CS): DiNapoli Stochastic is under middle-line, then crosses-down under the signal**
Post Baseline Cross Long (BL): DiNapoli Stochastic crossed-up over middle-line but Baseline is still in downtrend, then Baseline turns to uptrend within XX bars***
Post Baseline Cross Short (BS): DiNapoli Stochastic crossed-down under middle-line but Baseline is still in uptrend, then Baseline turns to downtrend within XX bars***
BL Recovery Continuation Long (RL): DiNapoli Stochastic is above middle-line. Baseline already crossed down into downtrend, then baseline crosses back up to uptrend; then, DiNapoli Stochastic crosses-up over the signal****
BL Recovery Continuation Short (RS): DiNapoli Stochastic is below middle-line. Baseline already crossed up into uptrend, then baseline crosses back down to downtrend; then, DiNapoli Stochastic crosses-down under the signal****
*All signals are shown regardless of Baseline and Volatility/Volume qualification
**All signals are shown regardless of Baseline qualification; however, when Baseline filter is active, only true continuations are shown. When the Baseline filter is not active, then all continuations are shown. True continuations are when the Baseline is active and maintains its uptrend/downtrend after the initial cross-up/cross-down over the middle-line respectively. This means that if the Baseline trend then moves against the DiNapoli Stochastic then any continuation signals are voided until another initial Long/Short. All continuations are will either show as regular continuations or be converted into recovery continuations
***All signals are shown regardless of Volatility/Volume qualification
****When the Baseline filter is active, some regular continuations are converted to recovery continuations and are shown. When the Baseline filter is not active, then these signals are not shown.
Confirmation 2 Signal
Initial Long (L): DiNapoli Stochastic crosses-up over middle-line*
Initial Short (S): DiNapoli Stochastic crosses-down under middle-line*
Continuation Long (CL): DiNapoli Stochastic is over middle-line, then crosses-up over the signal**
Continuation Short (CS): DiNapoli Stochastic is under middle-line, then crosses-down under the signal**
Post Baseline Cross Long (BL): DiNapoli Stochastic crossed-up over middle-line but Baseline is still in downtrend, then Baseline turns to uptrend within XX bars***
Post Baseline Cross Short (BS): DiNapoli Stochastic crossed-down under middle-line but Baseline is still in uptrend, then Baseline turns to downtrend within XX bars***
BL Recovery Continuation Long (RL): DiNapoli Stochastic is above middle-line. Baseline already crossed down into downtrend, then baseline crosses back up to uptrend while DiNapoli Stochastic is still above middle-line; then, DiNapoli Stochastic crosses-up over the signal****
BL Recovery Continuation Short (RS): DiNapoli Stochastic is below middle-line. Baseline already crossed up into uptrend, then baseline crosses back down to downtrend while DiNapoli Stochastic is still below middle-line; then, DiNapoli Stochastic crosses-down under the signal****
*All signals are shown regardless of Baseline and Volatility/Volume qualification
**All signals are shown regardless of Baseline qualification; however, when Baseline filter is active, only true continuations are shown. When the Baseline filter is not active, then all continuations are shown. True continuations are when the Baseline is active and maintains its uptrend/downtrend after the initial cross-up/cross-down over the middle-line respectively. This means that if the Baseline trend then moves against the DiNapoli Stochastic then any continuation signals are voided until another initial Long/Short. All continuations are will either show as regular continuations or be converted into recovery continuations
***All signals are shown regardless of Volatility/Volume qualification
****When the Baseline filter is active, some regular continuations are converted to recovery continuations and are shown. When the Baseline filter is not active, then these signals are not shown.
Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
Initial Long (L): The imported GKD-C Confirmation 1 indicator crosses-up over middle-line, then DiNapoli Stochastic crosses-up over the middle-line on the same bar or "Number of Bars Confirmation" bars in the future (see X-bar rule below)
Initial Short (S): The imported GKD-C Confirmation 1 indicator crosses-down under middle-line, then DiNapoli Stochastic crosses-down under the middle-line on the same bar or "Number of Bars Confirmation" bars in the future (see X-bar rule below)
Continuation Long Confirmation 1 (CL): The imported GKD-C Confirmation 1 indicator is over middle-line, then crosses-up over the signal
Continuation Short Confirmation 1 (CS): The imported GKD-C Confirmation 1 indicator is under middle-line, then crosses-down under the signal
Post Baseline Cross Long (BL): The imported GKD-C Confirmation 1 crossed-up over middle-line but Baseline is still in downtrend; and DiNapoli Stochastic crossed-up over middle-line on the same bar or XX bars in the future but Baseline is still in downtrend; then Baseline turns to uptrend within "Maximum Allowable PSBC Bars Back" bars (see X-bar rule below)
Post Baseline Cross Short (BS): The imported GKD-C Confirmation 1 crossed-down under middle-line but Baseline is still in uptrend; and, DiNapoli Stochastic crossed-down under middle-line on the same bar or XX bars in the future but Baseline is still in uptrend; then Baseline turns to downtrend within "Maximum Allowable PSBC Bars Back" bars (see X-bar rule below)
BL Recovery Continuation Long (RL): The imported GKD-C Confirmation 1 indicator is above middle-line. Baseline already crossed down into downtrend, then baseline crosses back up to uptrend while DiNapoli Stochastic is still above middle-line; then, The imported GKD-C Confirmation 1 crosses-up over the signal
BL Recovery Continuation Short (RS): The imported GKD-C Confirmation 1 indicator is below middle-line. Baseline already crossed up into uptrend, then baseline crosses back down to downtrend while DiNapoli Stochastic is still below middle-line; then, The imported GKD-C Confirmation 1 crosses-down under the signal
Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 2
Initial Long (L): same as Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
Initial Short (S): same as Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
Continuation Long Confirmation 2 (CL): DiNapoli Stochastic is over middle-line, then crosses-up over the signal
Continuation Short Confirmation 2 (CS): DiNapoli Stochastic is under middle-line, then crosses-down under the signal
Post Baseline Cross Long (BL): same as Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
Post Baseline Cross Short (BS): same as Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
BL Recovery Continuation Long (RL): DiNapoli Stochastic is above middle-line. Baseline already crossed down into downtrend, then baseline crosses back up to uptrend; then, DiNapoli Stochastic crosses-up over the signal
BL Recovery Continuation Short (RS): DiNapoli Stochastic is below middle-line. Baseline already crossed up into uptrend, then baseline crosses back down to downtrend; then, DiNapoli Stochastic crosses-down under the signal
Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Both
Initial Long (L): same as Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
Initial Short (S): same as Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
Continuation Long Confirmation 2 (CL): The imported GKD-C Confirmation 1 indicator is over middle-line, then crosses-up over the signal; DiNapoli Stochastic is over middle-line, then crosses-up over the signal within "Number of Bars Confirmation" bars in the future
Continuation Short Confirmation 2 (CS): The imported GKD-C Confirmation 1 indicator is under middle-line, then crosses-down under the signal; DiNapoli Stochastic is under middle-line, then crosses-down under the signal within "Number of Bars Confirmation" bars in the future
Post Baseline Cross Long (BL): same as Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
Post Baseline Cross Short (BS): same as Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
BL Recovery Continuation Long (RL): The imported GKD-C Confirmation 1 indicator is above middle-line and DiNapoli Stochastic is above middle-line. Baseline already crossed down into downtrend, then baseline crosses back up to uptrend; then, the imported GKD-C Confirmation 1 crosses-up over its signal, and DiNapoli Stochastic crosses-up over its signal within "Number of Bars Confirmation" bars in the future
BL Recovery Continuation Short (RS): The imported GKD-C Confirmation 1 indicator is below middle-line and DiNapoli Stochastic is below middle-line. Baseline already crossed up into uptrend, then baseline crosses back down to downtrend; then, the imported GKD-C Confirmation 1 crosses-down under its signal, and DiNapoli Stochastic crosses-down under its signal within "Number of Bars Confirmation" bars in the future
Confirmation 2 Confluence Background Color Signals; Confirmation Order: Both; Confirmation Type: (continuations don't change from the variations above)
Initial Long (L): The imported GKD-C Confirmation 1 indicator crosses-up over middle-line, then DiNapoli Stochastic crosses-up over the middle-line on the same bar or "Number of Bars Confirmation" bars in the future (see X-bar rule below); OR, DiNapoli Stochastic crosses-up over middle-line, then the imported GKD-C Confirmation 1 indicator crosses-up over the middle-line on the same bar or "Number of Bars Confirmation" bars in the future (see X-bar rule below)
Initial Short (S): The imported GKD-C Confirmation 1 indicator crosses-down under middle-line, then DiNapoli Stochastic crosses-down under the middle-line on the same bar or "Number of Bars Confirmation" bars in the future (see X-bar rule below); OR, DiNapoli Stochastic crosses-down under middle-line, then the imported GKD-C Confirmation 1 indicator crosses-down under the middle-line on the same bar or "Number of Bars Confirmation" bars in the future (see X-bar rule below)
Post Baseline Cross Long (BL): The imported GKD-C Confirmation 1 crossed-down under middle-line but Baseline is still in uptrend; and, DiNapoli Stochastic crossed-down under middle-line on the same bar or XX bars in the future but Baseline is still in uptrend; then Baseline turns to downtrend within "Maximum Allowable PSBC Bars Back" bars (see X-bar rule below); OR, DiNapoli Stochastic crossed-down under middle-line but Baseline is still in uptrend; and, the imported GKD-C Confirmation 1 crossed-down under middle-line on the same bar or XX bars in the future but Baseline is still in uptrend; then Baseline turns to downtrend within "Maximum Allowable PSBC Bars Back" bars (see X-bar rule below)
Post Baseline Cross Short (BS): The imported GKD-C Confirmation 1 crossed-down under middle-line but Baseline is still in uptrend; and, DiNapoli Stochastic crossed-down under middle-line on the same bar or XX bars in the future but Baseline is still in uptrend; then Baseline turns to downtrend within "Maximum Allowable PSBC Bars Back" bars (see X-bar rule below); OR, DiNapoli Stochastic crossed-down under middle-line but Baseline is still in uptrend; and, the imported GKD-C Confirmation 1 crossed-down under middle-line on the same bar or XX bars in the future but Baseline is still in uptrend; then Baseline turns to downtrend within "Maximum Allowable PSBC Bars Back" bars (see X-bar rule below)
Solo Confirmation Signals
Initial Long (L): DiNapoli Stochastic crosses-up over middle-line
Initial Short (S): DiNapoli Stochastic crosses-down under middle-line
Continuation Long (CL): DiNapoli Stochastic is over middle-line, then crosses-up over the signal
Continuation Short (CS): DiNapoli Stochastic is under middle-line, then crosses-down under the signal
Post Baseline Cross Long (BL): DiNapoli Stochastic crossed-up over middle-line but Baseline is still in downtrend, then Baseline turns to uptrend within XX bars
Post Baseline Cross Short (BS): DiNapoli Stochastic crossed-down under middle-line but Baseline is still in uptrend, then Baseline turns to downtrend within XX bars
BL Recovery Continuation Long (RL): DiNapoli Stochastic above middle-line. Baseline already crossed down into downtrend, then baseline crosses back up to uptrend while DiNapoli Stochastic is still above middle-line
BL Recovery Continuation Short (RS): DiNapoli Stochastic below middle-line. Baseline already crossed up into uptrend, then baseline crosses back down to downtrend while DiNapoli Stochastic is still below middle-line
X-bar Rule settings
This rule only applies when this indicator "Confirmation Type" set to "Confirmation 2"
Requirements
Inputs: Confirmation 1 and Solo Confirmation: GKD-V Volatility/Volume indicator; Confiration 2: GKD-C Confirmation indicator
Output: Confirmation 2 and Solo Confirmation: GKD-E Exit indicator; Confiration 1: GKD-C Confirmation indicator
Additional features will be added in future releases.
This indicator is only available to ALGX Trading VIP group members . You can see the Author's Instructions below to get more information on how to get access.
GKD-C Universal Oscillator [Loxx]Giga Kaleidoscope Universal Oscillator Confirmation is a Confirmation module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
What is Loxx's "Giga Kaleidoscope Modularized Trading System"?
The Giga Kaleidoscope Modularized Trading System is a trading system built on the philosophy of the NNFX (No Nonsense Forex) algorithmic trading.
What is 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 (such as "Baseline" shown on the chart above)
3. Confirmation 1 - a technical indicator used to identify trends. This should agree with the "Baseline"
4. Confirmation 2 - a technical indicator used to identify trends. This filters/verifies the trend identified by "Baseline" and "Confirmation 1"
5. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown.
6. Exit - a technical indicator used to determine when a trend is exhausted.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v1.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 module (Confirmation 1/2, Numbers 3 and 4 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 5 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 6 in the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data between modules. Data is passed between each module as described below:
GKD-B => GKD-V => GKD-C(1) => GKD-C(2) => GKD-E => GKD-BT
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Strategy with 1-3 take profits, trailing stop loss, multiple types of PnL volatility, and 2 backtesting styles
Baseline: Hull Moving Average
Volatility/Volume: Volatility Ratio
Confirmation 1: Universal Oscillator as shown on the chart above
Confirmation 2: Vortex
Exit: Universal Oscillator
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD protocol chain.
Now that you have a general understanding of the NNFX algorithm and the GKD trading system. Let's go over what's inside the GKD-E Universal Oscillator itself.
What is Universal Oscillator?
In his article, "Whiter is Brighter," Dr. Ehlers discusses that market data is akin to "pink noise" (a scientific term that refers to a type of noise where the power spectral density is stronger at lower frequencies). Isolating the white spectrum (whose power spectral density is the same at all frequencies) is said to output data that can be transformed into a zero-lag oscillator.
The isolation of the white spectrum data is done via a momentum-based equation. This data is further subjected to Ehlers Super Smoother so that undesirable wave components are eliminated. The filtered data is then transformed into an oscillator by using the automatic gain control algorithm.
What's different in this version?
This version also includes Loxx's Exotic Source Types. You can read about these sources here:
Signals
A GKD-C Confirmation indicator can be used as either a Confirmation 1, Confirmation 2, or Solo Confirmation indicator. See step 3 & 4 of the NNFX algorithm above to understand how this indicator fits into the GKD trading system. The Solo Confirmation setting allows you to test this indicator by itself without an additional GKD-C indicator present in the GKD protocol chain.
On the chart shown above, this indicator is shown as GKD-C Universal Oscillator and is set to Solo Confirmation. The GKD-B Baseline, GKD-V Volatility Ratio, and this indicator satisfy the first three steps in the GKD trading system chain: GKD-B => GKD-V => GKD-C(solo).
Overbought and oversold levels are included for a point of reference and have no bearing on the generated signals.
The signals from each of these settings are as follows:
Confirmation 1 Signal
Initial Long (L): Universal Oscillator crosses-up over zero-line*
Initial Short (S): Universal Oscillator crosses-down under zero-line*
Continuation Long (CL): Universal Oscillator is over zero-line, then crosses-up over the signal**
Continuation Short (CS): Universal Oscillator is under zero-line, then crosses-down under the signal**
Post Baseline Cross Long (BL): Universal Oscillator crossed-up over zero-line but Baseline is still in downtrend, then Baseline turns to uptrend within XX bars***
Post Baseline Cross Short (BS): Universal Oscillator crossed-down under zero-line but Baseline is still in uptrend, then Baseline turns to downtrend within XX bars***
BL Recovery Continuation Long (RL): Universal Oscillator is above zero-line. Baseline already crossed down into downtrend, then baseline crosses back up to uptrend; then, Universal Oscillator crosses-up over the signal****
BL Recovery Continuation Short (RS): Universal Oscillator is below zero-line. Baseline already crossed up into uptrend, then baseline crosses back down to downtrend; then, Universal Oscillator crosses-down under the signal****
*All signals are shown regardless of Baseline and Volatility/Volume qualification
**All signals are shown regardless of Baseline qualification; however, when Baseline filter is active, only true continuations are shown. When the Baseline filter is not active, then all continuations are shown. True continuations are when the Baseline is active and maintains its uptrend/downtrend after the initial cross-up/cross-down over the zero-line respectively. This means that if the Baseline trend then moves against the Universal Oscillator then any continuation signals are voided until another initial Long/Short. All continuations are will either show as regular continuations or be converted into recovery continuations
***All signals are shown regardless of Volatility/Volume qualification
****When the Baseline filter is active, some regular continuations are converted to recovery continuations and are shown. When the Baseline filter is not active, then these signals are not shown.
Confirmation 2 Signal
Initial Long (L): Universal Oscillator crosses-up over zero-line*
Initial Short (S): Universal Oscillator crosses-down under zero-line*
Continuation Long (CL): Universal Oscillator is over zero-line, then crosses-up over the signal**
Continuation Short (CS): Universal Oscillator is under zero-line, then crosses-down under the signal**
Post Baseline Cross Long (BL): Universal Oscillator crossed-up over zero-line but Baseline is still in downtrend, then Baseline turns to uptrend within XX bars***
Post Baseline Cross Short (BS): Universal Oscillator crossed-down under zero-line but Baseline is still in uptrend, then Baseline turns to downtrend within XX bars***
BL Recovery Continuation Long (RL): Universal Oscillator is above zero-line. Baseline already crossed down into downtrend, then baseline crosses back up to uptrend while Universal Oscillator is still above zero-line; then, Universal Oscillator crosses-up over the signal****
BL Recovery Continuation Short (RS): Universal Oscillator is below zero-line. Baseline already crossed up into uptrend, then baseline crosses back down to downtrend while Universal Oscillator is still below zero-line; then, Universal Oscillator crosses-down under the signal****
*All signals are shown regardless of Baseline and Volatility/Volume qualification
**All signals are shown regardless of Baseline qualification; however, when Baseline filter is active, only true continuations are shown. When the Baseline filter is not active, then all continuations are shown. True continuations are when the Baseline is active and maintains its uptrend/downtrend after the initial cross-up/cross-down over the zero-line respectively. This means that if the Baseline trend then moves against the Universal Oscillator then any continuation signals are voided until another initial Long/Short. All continuations are will either show as regular continuations or be converted into recovery continuations
***All signals are shown regardless of Volatility/Volume qualification
****When the Baseline filter is active, some regular continuations are converted to recovery continuations and are shown. When the Baseline filter is not active, then these signals are not shown.
Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
Initial Long (L): The imported GKD-C Confirmation 1 indicator crosses-up over zero-line, then Universal Oscillator crosses-up over the zero-line on the same bar or "Number of Bars Confirmation" bars in the future (see X-bar rule below)
Initial Short (S): The imported GKD-C Confirmation 1 indicator crosses-down under zero-line, then Universal Oscillator crosses-down under the zero-line on the same bar or "Number of Bars Confirmation" bars in the future (see X-bar rule below)
Continuation Long Confirmation 1 (CL): The imported GKD-C Confirmation 1 indicator is over zero-line, then crosses-up over the signal
Continuation Short Confirmation 1 (CS): The imported GKD-C Confirmation 1 indicator is under zero-line, then crosses-down under the signal
Post Baseline Cross Long (BL): The imported GKD-C Confirmation 1 crossed-up over zero-line but Baseline is still in downtrend; and Universal Oscillator crossed-up over zero-line on the same bar or XX bars in the future but Baseline is still in downtrend; then Baseline turns to uptrend within "Maximum Allowable PSBC Bars Back" bars (see X-bar rule below)
Post Baseline Cross Short (BS): The imported GKD-C Confirmation 1 crossed-down under zero-line but Baseline is still in uptrend; and, Universal Oscillator crossed-down under zero-line on the same bar or XX bars in the future but Baseline is still in uptrend; then Baseline turns to downtrend within "Maximum Allowable PSBC Bars Back" bars (see X-bar rule below)
BL Recovery Continuation Long (RL): The imported GKD-C Confirmation 1 indicator is above zero-line. Baseline already crossed down into downtrend, then baseline crosses back up to uptrend while Universal Oscillator is still above zero-line; then, The imported GKD-C Confirmation 1 crosses-up over the signal
BL Recovery Continuation Short (RS): The imported GKD-C Confirmation 1 indicator is below zero-line. Baseline already crossed up into uptrend, then baseline crosses back down to downtrend while Universal Oscillator is still below zero-line; then, The imported GKD-C Confirmation 1 crosses-down under the signal
Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 2
Initial Long (L): same as Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
Initial Short (S): same as Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
Continuation Long Confirmation 2 (CL): Universal Oscillator is over zero-line, then crosses-up over the signal
Continuation Short Confirmation 2 (CS): Universal Oscillator is under zero-line, then crosses-down under the signal
Post Baseline Cross Long (BL): same as Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
Post Baseline Cross Short (BS): same as Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
BL Recovery Continuation Long (RL): Universal Oscillator is above zero-line. Baseline already crossed down into downtrend, then baseline crosses back up to uptrend; then, Universal Oscillator crosses-up over the signal
BL Recovery Continuation Short (RS): Universal Oscillator is below zero-line. Baseline already crossed up into uptrend, then baseline crosses back down to downtrend; then, Universal Oscillator crosses-down under the signal
Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Both
Initial Long (L): same as Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
Initial Short (S): same as Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
Continuation Long Confirmation 2 (CL): The imported GKD-C Confirmation 1 indicator is over zero-line, then crosses-up over the signal; Universal Oscillator is over zero-line, then crosses-up over the signal within "Number of Bars Confirmation" bars in the future
Continuation Short Confirmation 2 (CS): The imported GKD-C Confirmation 1 indicator is under zero-line, then crosses-down under the signal; Universal Oscillator is under zero-line, then crosses-down under the signal within "Number of Bars Confirmation" bars in the future
Post Baseline Cross Long (BL): same as Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
Post Baseline Cross Short (BS): same as Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
BL Recovery Continuation Long (RL): The imported GKD-C Confirmation 1 indicator is above zero-line and Universal Oscillator is above zero-line. Baseline already crossed down into downtrend, then baseline crosses back up to uptrend; then, the imported GKD-C Confirmation 1 crosses-up over its signal, and Universal Oscillator crosses-up over its signal within "Number of Bars Confirmation" bars in the future
BL Recovery Continuation Short (RS): The imported GKD-C Confirmation 1 indicator is below zero-line and Universal Oscillator is below zero-line. Baseline already crossed up into uptrend, then baseline crosses back down to downtrend; then, the imported GKD-C Confirmation 1 crosses-down under its signal, and Universal Oscillator crosses-down under its signal within "Number of Bars Confirmation" bars in the future
Confirmation 2 Confluence Background Color Signals; Confirmation Order: Both; Confirmation Type: (continuations don't change from the variations above)
Initial Long (L): The imported GKD-C Confirmation 1 indicator crosses-up over zero-line, then Universal Oscillator crosses-up over the zero-line on the same bar or "Number of Bars Confirmation" bars in the future (see X-bar rule below); OR, Universal Oscillator crosses-up over zero-line, then the imported GKD-C Confirmation 1 indicator crosses-up over the zero-line on the same bar or "Number of Bars Confirmation" bars in the future (see X-bar rule below)
Initial Short (S): The imported GKD-C Confirmation 1 indicator crosses-down under zero-line, then Universal Oscillator crosses-down under the zero-line on the same bar or "Number of Bars Confirmation" bars in the future (see X-bar rule below); OR, Universal Oscillator crosses-down under zero-line, then the imported GKD-C Confirmation 1 indicator crosses-down under the zero-line on the same bar or "Number of Bars Confirmation" bars in the future (see X-bar rule below)
Post Baseline Cross Long (BL): The imported GKD-C Confirmation 1 crossed-down under zero-line but Baseline is still in uptrend; and, Universal Oscillator crossed-down under zero-line on the same bar or XX bars in the future but Baseline is still in uptrend; then Baseline turns to downtrend within "Maximum Allowable PSBC Bars Back" bars (see X-bar rule below); OR, Universal Oscillator crossed-down under zero-line but Baseline is still in uptrend; and, the imported GKD-C Confirmation 1 crossed-down under zero-line on the same bar or XX bars in the future but Baseline is still in uptrend; then Baseline turns to downtrend within "Maximum Allowable PSBC Bars Back" bars (see X-bar rule below)
Post Baseline Cross Short (BS): The imported GKD-C Confirmation 1 crossed-down under zero-line but Baseline is still in uptrend; and, Universal Oscillator crossed-down under zero-line on the same bar or XX bars in the future but Baseline is still in uptrend; then Baseline turns to downtrend within "Maximum Allowable PSBC Bars Back" bars (see X-bar rule below); OR, Universal Oscillator crossed-down under zero-line but Baseline is still in uptrend; and, the imported GKD-C Confirmation 1 crossed-down under zero-line on the same bar or XX bars in the future but Baseline is still in uptrend; then Baseline turns to downtrend within "Maximum Allowable PSBC Bars Back" bars (see X-bar rule below)
Solo Confirmation Signals
Initial Long (L): Universal Oscillator crosses-up over zero-line
Initial Short (S): Universal Oscillator crosses-down under zero-line
Continuation Long (CL): Universal Oscillator is over zero-line, then crosses-up over the signal
Continuation Short (CS): Universal Oscillator is under zero-line, then crosses-down under the signal
Post Baseline Cross Long (BL): Universal Oscillator crossed-up over zero-line but Baseline is still in downtrend, then Baseline turns to uptrend within XX bars
Post Baseline Cross Short (BS): Universal Oscillator crossed-down under zero-line but Baseline is still in uptrend, then Baseline turns to downtrend within XX bars
BL Recovery Continuation Long (RL): Universal Oscillator above zero-line. Baseline already crossed down into downtrend, then baseline crosses back up to uptrend while Universal Oscillator is still above zero-line
BL Recovery Continuation Short (RS): Universal Oscillator below zero-line. Baseline already crossed up into uptrend, then baseline crosses back down to downtrend while Universal Oscillator is still below zero-line
X-bar Rule settings
This rule only applies when this indicator "Confirmation Type" set to "Confirmation 2"
Requirements
Inputs: Confirmation 1 and Solo Confirmation: GKD-V Volatility/Volume indicator; Confiration 2: GKD-C Confirmation indicator
Output: Confirmation 2 and Solo Confirmation: GKD-E Exit indicator; Confiration 1: GKD-C Confirmation indicator
Additional features will be added in future releases.
This indicator is only available to ALGX Trading VIP group members . You can see the Author's Instructions below to get more information on how to get access.
GKD-C Fisher Transform [Loxx]Giga Kaleidoscope Fisher Transform Confirmation is a Confirmation module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
What is Loxx's "Giga Kaleidoscope Modularized Trading System"?
The Giga Kaleidoscope Modularized Trading System is a trading system built on the philosophy of the NNFX (No Nonsense Forex) algorithmic trading.
What is 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 (such as "Baseline" shown on the chart above)
3. Confirmation 1 - a technical indicator used to identify trends. This should agree with the "Baseline"
4. Confirmation 2 - a technical indicator used to identify trends. This filters/verifies the trend identified by "Baseline" and "Confirmation 1"
5. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown.
6. Exit - a technical indicator used to determine when a trend is exhausted.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v1.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 module (Confirmation 1/2, Numbers 3 and 4 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 5 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 6 in the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data between modules. Data is passed between each module as described below:
GKD-B => GKD-V => GKD-C(1) => GKD-C(2) => GKD-E => GKD-BT
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Strategy with 1-3 take profits, trailing stop loss, multiple types of PnL volatility, and 2 backtesting styles
Baseline: Hull Moving Average
Volatility/Volume: Volatility Ratio
Confirmation 1: Fisher Transform as shown on the chart above
Confirmation 2: Vortex
Exit: Fisher Transform
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD protocol chain.
Now that you have a general understanding of the NNFX algorithm and the GKD trading system. Let's go over what's inside the GKD-E Fisher Transform itself.
What is Fisher Transform?
The Fisher Transform is a technical indicator created by John F. Ehlers that converts prices into a Gaussian normal distribution. The indicator highlights when prices have moved to an extreme, based on recent prices. This may help in spotting turning points in the price of an asset.
What's different in this version?
This version also includes Loxx's Exotic Source Types. You can read about these sources here:
Signals
A GKD-C Confirmation indicator can be used as either a Confirmation 1, Confirmation 2, or Solo Confirmation indicator. See step 3 & 4 of the NNFX algorithm above to understand how this indicator fits into the GKD trading system. The Solo Confirmation setting allows you to test this indicator by itself without an additional GKD-C indicator present in the GKD protocol chain.
On the chart shown above, this indicator is shown as GKD-C Fisher Transform and is set to Solo Confirmation. The GKD-B Baseline, GKD-V Volatility Ratio, and this indicator satisfy the first three steps in the GKD trading system chain: GKD-B => GKD-V => GKD-C(solo).
The signals from each of these settings are as follows:
Confirmation 1 Signal
Initial Long (L): Fisher crosses-up over zero-line*
Initial Short (S): Fisher crosses-down under zero-line*
Continuation Long (CL): Fisher is over zero-line, then crosses-up over the signal**
Continuation Short (CS): Fisher is under zero-line, then crosses-down under the signal**
Post Baseline Cross Long (BL): Fisher crossed-up over zero-line but Baseline is still in downtrend, then Baseline turns to uptrend within XX bars***
Post Baseline Cross Short (BS): Fisher crossed-down under zero-line but Baseline is still in uptrend, then Baseline turns to downtrend within XX bars***
BL Recovery Continuation Long (RL): Fisher is above zero-line. Baseline already crossed down into downtrend, then baseline crosses back up to uptrend; then, Fisher crosses-up over the signal****
BL Recovery Continuation Short (RS): Fisher is below zero-line. Baseline already crossed up into uptrend, then baseline crosses back down to downtrend; then, Fisher crosses-down under the signal****
*All signals are shown regardless of Baseline and Volatility/Volume qualification
**All signals are shown regardless of Baseline qualification; however, when Baseline filter is active, only true continuations are shown. When the Baseline filter is not active, then all continuations are shown. True continuations are when the Baseline is active and maintains its uptrend/downtrend after the initial cross-up/cross-down over the zero-line respectively. This means that if the Baseline trend then moves against the Fisher Transform then any continuation signals are voided until another initial Long/Short. All continuations are will either show as regular continuations or be converted into recovery continuations
***All signals are shown regardless of Volatility/Volume qualification
****When the Baseline filter is active, some regular continuations are converted to recovery continuations and are shown. When the Baseline filter is not active, then these signals are not shown.
Confirmation 2 Signal
Initial Long (L): Fisher crosses-up over zero-line*
Initial Short (S): Fisher crosses-down under zero-line*
Continuation Long (CL): Fisher is over zero-line, then crosses-up over the signal**
Continuation Short (CS): Fisher is under zero-line, then crosses-down under the signal**
Post Baseline Cross Long (BL): Fisher crossed-up over zero-line but Baseline is still in downtrend, then Baseline turns to uptrend within XX bars***
Post Baseline Cross Short (BS): Fisher crossed-down under zero-line but Baseline is still in uptrend, then Baseline turns to downtrend within XX bars***
BL Recovery Continuation Long (RL): Fisher is above zero-line. Baseline already crossed down into downtrend, then baseline crosses back up to uptrend while Fisher is still above zero-line; then, Fisher crosses-up over the signal****
BL Recovery Continuation Short (RS): Fisher is below zero-line. Baseline already crossed up into uptrend, then baseline crosses back down to downtrend while Fisher is still below zero-line; then, Fisher crosses-down under the signal****
*All signals are shown regardless of Baseline and Volatility/Volume qualification
**All signals are shown regardless of Baseline qualification; however, when Baseline filter is active, only true continuations are shown. When the Baseline filter is not active, then all continuations are shown. True continuations are when the Baseline is active and maintains its uptrend/downtrend after the initial cross-up/cross-down over the zero-line respectively. This means that if the Baseline trend then moves against the Fisher Transform then any continuation signals are voided until another initial Long/Short. All continuations are will either show as regular continuations or be converted into recovery continuations
***All signals are shown regardless of Volatility/Volume qualification
****When the Baseline filter is active, some regular continuations are converted to recovery continuations and are shown. When the Baseline filter is not active, then these signals are not shown.
Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
Initial Long (L): The imported GKD-C Confirmation 1 indicator crosses-up over zero-line, then Fisher Transform crosses-up over the zero-line on the same bar or "Number of Bars Confirmation" bars in the future (see X-bar rule below)
Initial Short (S): The imported GKD-C Confirmation 1 indicator crosses-down under zero-line, then Fisher Transform crosses-down under the zero-line on the same bar or "Number of Bars Confirmation" bars in the future (see X-bar rule below)
Continuation Long Confirmation 1 (CL): The imported GKD-C Confirmation 1 indicator is over zero-line, then crosses-up over the signal
Continuation Short Confirmation 1 (CS): The imported GKD-C Confirmation 1 indicator is under zero-line, then crosses-down under the signal
Post Baseline Cross Long (BL): The imported GKD-C Confirmation 1 crossed-up over zero-line but Baseline is still in downtrend; and Fisher crossed-up over zero-line on the same bar or XX bars in the future but Baseline is still in downtrend; then Baseline turns to uptrend within "Maximum Allowable PSBC Bars Back" bars (see X-bar rule below)
Post Baseline Cross Short (BS): The imported GKD-C Confirmation 1 crossed-down under zero-line but Baseline is still in uptrend; and, Fisher crossed-down under zero-line on the same bar or XX bars in the future but Baseline is still in uptrend; then Baseline turns to downtrend within "Maximum Allowable PSBC Bars Back" bars (see X-bar rule below)
BL Recovery Continuation Long (RL): The imported GKD-C Confirmation 1 indicator is above zero-line. Baseline already crossed down into downtrend, then baseline crosses back up to uptrend while Fisher is still above zero-line; then, The imported GKD-C Confirmation 1 crosses-up over the signal
BL Recovery Continuation Short (RS): The imported GKD-C Confirmation 1 indicator is below zero-line. Baseline already crossed up into uptrend, then baseline crosses back down to downtrend while Fisher is still below zero-line; then, The imported GKD-C Confirmation 1 crosses-down under the signal
Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 2
Initial Long (L): same as Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
Initial Short (S): same as Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
Continuation Long Confirmation 2 (CL): Fisher is over zero-line, then crosses-up over the signal
Continuation Short Confirmation 2 (CS): Fisher is under zero-line, then crosses-down under the signal
Post Baseline Cross Long (BL): same as Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
Post Baseline Cross Short (BS): same as Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
BL Recovery Continuation Long (RL): Fisher is above zero-line. Baseline already crossed down into downtrend, then baseline crosses back up to uptrend; then, Fisher crosses-up over the signal
BL Recovery Continuation Short (RS): Fisher is below zero-line. Baseline already crossed up into uptrend, then baseline crosses back down to downtrend; then, Fisher crosses-down under the signal
Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Both
Initial Long (L): same as Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
Initial Short (S): same as Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
Continuation Long Confirmation 2 (CL): The imported GKD-C Confirmation 1 indicator is over zero-line, then crosses-up over the signal; Fisher is over zero-line, then crosses-up over the signal within "Number of Bars Confirmation" bars in the future
Continuation Short Confirmation 2 (CS): The imported GKD-C Confirmation 1 indicator is under zero-line, then crosses-down under the signal; Fisher is under zero-line, then crosses-down under the signal within "Number of Bars Confirmation" bars in the future
Post Baseline Cross Long (BL): same as Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
Post Baseline Cross Short (BS): same as Confirmation 2 Confluence Background Color Signals; Confirmation Order: Regular; Confirmation Type: Confirmation 1
BL Recovery Continuation Long (RL): The imported GKD-C Confirmation 1 indicator is above zero-line and Fisher is above zero-line. Baseline already crossed down into downtrend, then baseline crosses back up to uptrend; then, the imported GKD-C Confirmation 1 crosses-up over its signal, and Fisher crosses-up over its signal within "Number of Bars Confirmation" bars in the future
BL Recovery Continuation Short (RS): The imported GKD-C Confirmation 1 indicator is below zero-line and Fisher is below zero-line. Baseline already crossed up into uptrend, then baseline crosses back down to downtrend; then, the imported GKD-C Confirmation 1 crosses-down under its signal, and Fisher crosses-down under its signal within "Number of Bars Confirmation" bars in the future
Confirmation 2 Confluence Background Color Signals; Confirmation Order: Both; Confirmation Type: (continuations don't change from the variations above)
Initial Long (L): The imported GKD-C Confirmation 1 indicator crosses-up over zero-line, then Fisher Transform crosses-up over the zero-line on the same bar or "Number of Bars Confirmation" bars in the future (see X-bar rule below); OR, Fisher crosses-up over zero-line, then the imported GKD-C Confirmation 1 indicator crosses-up over the zero-line on the same bar or "Number of Bars Confirmation" bars in the future (see X-bar rule below)
Initial Short (S): The imported GKD-C Confirmation 1 indicator crosses-down under zero-line, then Fisher Transform crosses-down under the zero-line on the same bar or "Number of Bars Confirmation" bars in the future (see X-bar rule below); OR, Fisher crosses-down under zero-line, then the imported GKD-C Confirmation 1 indicator crosses-down under the zero-line on the same bar or "Number of Bars Confirmation" bars in the future (see X-bar rule below)
Post Baseline Cross Long (BL): The imported GKD-C Confirmation 1 crossed-down under zero-line but Baseline is still in uptrend; and, Fisher crossed-down under zero-line on the same bar or XX bars in the future but Baseline is still in uptrend; then Baseline turns to downtrend within "Maximum Allowable PSBC Bars Back" bars (see X-bar rule below); OR, Fisher crossed-down under zero-line but Baseline is still in uptrend; and, the imported GKD-C Confirmation 1 crossed-down under zero-line on the same bar or XX bars in the future but Baseline is still in uptrend; then Baseline turns to downtrend within "Maximum Allowable PSBC Bars Back" bars (see X-bar rule below)
Post Baseline Cross Short (BS): The imported GKD-C Confirmation 1 crossed-down under zero-line but Baseline is still in uptrend; and, Fisher crossed-down under zero-line on the same bar or XX bars in the future but Baseline is still in uptrend; then Baseline turns to downtrend within "Maximum Allowable PSBC Bars Back" bars (see X-bar rule below); OR, Fisher crossed-down under zero-line but Baseline is still in uptrend; and, the imported GKD-C Confirmation 1 crossed-down under zero-line on the same bar or XX bars in the future but Baseline is still in uptrend; then Baseline turns to downtrend within "Maximum Allowable PSBC Bars Back" bars (see X-bar rule below)
Solo Confirmation Signals
Initial Long (L): Fisher crosses-up over zero-line
Initial Short (S): Fisher crosses-down under zero-line
Continuation Long (CL): Fisher is over zero-line, then crosses-up over the signal
Continuation Short (CS): Fisher is under zero-line, then crosses-down under the signal
Post Baseline Cross Long (BL): Fisher crossed-up over zero-line but Baseline is still in downtrend, then Baseline turns to uptrend within XX bars
Post Baseline Cross Short (BS): Fisher crossed-down under zero-line but Baseline is still in uptrend, then Baseline turns to downtrend within XX bars
BL Recovery Continuation Long (RL): Fisher above zero-line. Baseline already crossed down into downtrend, then baseline crosses back up to uptrend while Fisher is still above zero-line
BL Recovery Continuation Short (RS): Fisher below zero-line. Baseline already crossed up into uptrend, then baseline crosses back down to downtrend while Fisher is still below zero-line
X-bar Rule settings
This rule only applies when this indicator "Confirmation Type" set to "Confirmation 2"
Requirements
Inputs: Confirmation 1 and Solo Confirmation: GKD-V Volatility/Volume indicator; Confirmation 2: GKD-C Confirmation indicator
Output: Confirmation 2 and Solo Confirmation: GKD-E Exit indicator; Confirmation 1: GKD-C Confirmation indicator
Additional features will be added in future releases.
This indicator is only available to ALGX Trading VIP group members . You can see the Author's Instructions below to get more information on how to get access.
GKD-E Fisher Transform [Loxx]Giga Kaleidoscope Fisher Transform Exit is an Exit module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
What is Loxx's "Giga Kaleidoscope Modularized Trading System"?
The Giga Kaleidoscope Modularized Trading System is a trading system built on the philosophy of the NNFX (No Nonsense Forex) algorithmic trading.
What is 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 (such as "Baseline" shown on the chart above)
3. Confirmation 1 - a technical indicator used to identify trends. This should agree with the "Baseline"
4. Confirmation 2 - a technical indicator used to identify trends. This filters/verifies the trend identified by "Baseline" and "Confirmation 1"
5. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown.
6. Exit - a technical indicator used to determine when a trend is exhausted.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v1.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 module (Confirmation 1/2, Numbers 3 and 4 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 5 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 6 in the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data between modules. Data is passed between each module as described below:
GKD-B => GKD-V => GKD-C(1) => GKD-C(2) => GKD-E => GKD-BT
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Strategy with 1-3 take profits, trailing stop loss, multiple types of PnL volatility, and 2 backtesting styles
Baseline: Hull Moving Average
Volatility/Volume: Volatility Ratio
Confirmation 1: Vortex
Confirmation 2: Fisher Transform
Exit: Fisher Transform as shown on the chart above
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD protocol chain.
Now that you have a general understanding of the NNFX algorithm and the GKD trading system. Let's go over what's inside the GKD-E Fisher Transform itself.
What is Fisher Transform?
The Fisher Transform is a technical indicator created by John F. Ehlers that converts prices into a Gaussian normal distribution. The indicator highlights when prices have moved to an extreme, based on recent prices. This may help in spotting turning points in the price of an asset.
What's different in this version?
This version also includes Loxx's Exotic Source Types. You can read about these sources here:
Exit signals
Exit Long type 1: Fisher is above zero and crosses down under the Fisher signal
Exit Long type 2: Fisher is above overbought level and crosses down the Fisher signal
Exit Short type 1: Fisher is below zero and crosses up over the Fisher signal
Exit Short type 2: Fisher is below oversold level and crosses up over the Fisher signal
Requirements
Input: Any Confirmation 2 indicator
Output: Export to "GKD-BT Backtest"
Other things to note
A GKD Exit indicator is required to complete the GKD trading system chain, but you are not requried to activate the Exits. You can turn on/off the exits inside this indicator, but an exit indiator is sitll required to be present in the GKD protocol chain.
Additional features will be added in future releases.
This indicator is only available to ALGX Trading VIP group members . You can see the Author's Instructions below to get more information on how to get access.
GKD-V Volatility Ratio [Loxx]Giga Kaleidoscope Volatility Ratio is a Volatility/Volume module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
What is Loxx's "Giga Kaleidoscope Modularized Trading System"?
The Giga Kaleidoscope Modularized Trading System is a trading system built on the philosophy of the NNFX (No Nonsense Forex) algorithmic trading.
What is 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 (such as "Baseline" shown on the chart above)
3. Confirmation 1 - a technical indicator used to identify trends. This should agree with the "Baseline"
4. Confirmation 2 - a technical indicator used to identify trends. This filters/verifies the trend identified by "Baseline" and "Confirmation 1"
5. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown.
6. Exit - a technical indicator used to determine when a trend is exhausted.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v1.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 module (Confirmation 1/2, Numbers 3 and 4 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 5 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 6 in the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data between modules. Data is passed between each module as described below:
GKD-B => GKD-V => GKD-C(1) => GKD-C(2) => GKD-E => GKD-BT
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Strategy with 1-3 take profits, trailing stop loss, multiple types of PnL volatility, and 2 backtesting styles
Baseline: Hull Moving Average
Volatility/Volume: Volatility Ratio as shown on the chart above
Confirmation 1: Vortex
Confirmation 2: Fisher Transform
Exit: Rex Oscillator
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD protocol chain.
Now that you have a general understanding of the NNFX algorithm and the GKD trading system. Let's go over what's inside the GKD-V Volatility Ratio itself.
What is Volatility Ratio?
Volatility Ratio is a comparison between volatility and its moving average. This indicator includes 11 different types of volatility as well as 63 different moving averages.
You can read about the moving average types here:
Volatility Types Included
v1.0 Included Volatility
Close-to-Close
Close-to-Close volatility is a classic and most commonly used volatility measure, sometimes referred to as historical volatility .
Volatility is an indicator of the speed of a stock price change. A stock with high volatility is one where the price changes rapidly and with a bigger amplitude. The more volatile a stock is, the riskier it is.
Close-to-close historical volatility calculated using only stock's closing prices. It is the simplest volatility estimator. But in many cases, it is not precise enough. Stock prices could jump considerably during a trading session, and return to the open value at the end. That means that a big amount of price information is not taken into account by close-to-close volatility .
Despite its drawbacks, Close-to-Close volatility is still useful in cases where the instrument doesn't have intraday prices. For example, mutual funds calculate their net asset values daily or weekly, and thus their prices are not suitable for more sophisticated volatility estimators.
Parkinson
Parkinson volatility is a volatility measure that uses the stock’s high and low price of the day.
The main difference between regular volatility and Parkinson volatility is that the latter uses high and low prices for a day, rather than only the closing price. That is useful as close to close prices could show little difference while large price movements could have happened during the day. Thus Parkinson's volatility is considered to be more precise and requires less data for calculation than the close-close volatility .
One drawback of this estimator is that it doesn't take into account price movements after market close. Hence it systematically undervalues volatility . That drawback is taken into account in the Garman-Klass's volatility estimator.
Garman-Klass
Garman Klass is a volatility estimator that incorporates open, low, high, and close prices of a security.
Garman-Klass volatility extends Parkinson's volatility by taking into account the opening and closing price. As markets are most active during the opening and closing of a trading session, it makes volatility estimation more accurate.
Garman and Klass also assumed that the process of price change is a process of continuous diffusion (Geometric Brownian motion). However, this assumption has several drawbacks. The method is not robust for opening jumps in price and trend movements.
Despite its drawbacks, the Garman-Klass estimator is still more effective than the basic formula since it takes into account not only the price at the beginning and end of the time interval but also intraday price extremums.
Researchers Rogers and Satchel have proposed a more efficient method for assessing historical volatility that takes into account price trends. See Rogers-Satchell Volatility for more detail.
Rogers-Satchell
Rogers-Satchell is an estimator for measuring the volatility of securities with an average return not equal to zero.
Unlike Parkinson and Garman-Klass estimators, Rogers-Satchell incorporates drift term (mean return not equal to zero). As a result, it provides a better volatility estimation when the underlying is trending.
The main disadvantage of this method is that it does not take into account price movements between trading sessions. It means an underestimation of volatility since price jumps periodically occur in the market precisely at the moments between sessions.
A more comprehensive estimator that also considers the gaps between sessions was developed based on the Rogers-Satchel formula in the 2000s by Yang-Zhang. See Yang Zhang Volatility for more detail.
Yang-Zhang
Yang Zhang is a historical volatility estimator that handles both opening jumps and the drift and has a minimum estimation error.
We can think of the Yang-Zhang volatility as the combination of the overnight (close-to-open volatility ) and a weighted average of the Rogers-Satchell volatility and the day’s open-to-close volatility . It considered being 14 times more efficient than the close-to-close estimator.
Garman-Klass-Yang-Zhang
Garman-Klass-Yang-Zhang (GKYZ) volatility estimator consists of using the returns of open, high, low, and closing prices in its calculation.
GKYZ volatility estimator takes into account overnight jumps but not the trend, i.e. it assumes that the underlying asset follows a GBM process with zero drift. Therefore the GKYZ volatility estimator tends to overestimate the volatility when the drift is different from zero. However, for a GBM process, this estimator is eight times more efficient than the close-to-close volatility estimator.
Exponential Weighted Moving Average
The Exponentially Weighted Moving Average (EWMA) is a quantitative or statistical measure used to model or describe a time series. The EWMA is widely used in finance, the main applications being technical analysis and volatility modeling.
The moving average is designed as such that older observations are given lower weights. The weights fall exponentially as the data point gets older – hence the name exponentially weighted.
The only decision a user of the EWMA must make is the parameter lambda. The parameter decides how important the current observation is in the calculation of the EWMA. The higher the value of lambda, the more closely the EWMA tracks the original time series.
Standard Deviation of Log Returns
This is the simplest calculation of volatility . It's the standard deviation of ln(close/close(1))
Pseudo GARCH(2,2)
This is calculated using a short- and long-run mean of variance multiplied by θ.
θavg(var ;M) + (1 − θ) avg (var ;N) = 2θvar/(M+1-(M-1)L) + 2(1-θ)var/(M+1-(M-1)L)
Solving for θ can be done by minimizing the mean squared error of estimation; that is, regressing L^-1var - avg (var; N) against avg (var; M) - avg (var; N) and using the resulting beta estimate as θ.
Average True Range
The average true range (ATR) is a technical analysis indicator, introduced by market technician J. Welles Wilder Jr. in his book New Concepts in Technical Trading Systems, that measures market volatility by decomposing the entire range of an asset price for that period.
The true range indicator is taken as the greatest of the following: current high less the current low; the absolute value of the current high less the previous close; and the absolute value of the current low less the previous close. The ATR is then a moving average, generally using 14 days, of the true ranges.
True Range Double
A special case of ATR that attempts to correct for volatility skew.
Signals
1. Traditional: The traditional signal is volatility is either high or low. This is non-directional. When the Volatility Ratio is above 1, then there is enough volatility to trade long or short. This signal type has a bar risings option that requires that the Volatility Ratio is not only above 1 but also rising for the last XX bars.
2. Crossing: This is experimental. When a cross-up above 1 or cross-down below one occurs then, and only then, is there enough volatility to trade long or short. This is also non-directional.
3. Both Traditional and Crossing
X-bar Rule
If a signal registers XX bars ago, then the signal is still valid. This is an optional feature.
Other things to note
The GKD trading system requires that a GKD-V indicator be present in the indicator chain, but the GKD-V indicator doesn't need to be active. You can turn on/off the Volatility Ratio as you wish so you can backtest your trading strategy with the filter on or off.
Additional features will be added in future releases.
This indicator is only available to ALGX Trading VIP group members . You can see the Author's Instructions below to get more information on how to get access.
GKD-B Baseline [Loxx]Giga Kaleidoscope Baseline is a Baseline module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
What is Loxx's "Giga Kaleidoscope Modularized Trading System"?
The Giga Kaleidoscope Modularized Trading System is a trading system built on the philosophy of the NNFX (No Nonsense Forex) algorithmic trading.
What is 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 (such as "Baseline" shown on the chart above)
3. Confirmation 1 - a technical indicator used to identify trend. This should agree with the "Baseline"
4. Confirmation 2 - a technical indicator used to identify trend. This filters/verifies the trend identified by "Baseline" and "Confirmation 1"
5. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown.
6. Exit - a technical indicator used to determine when trend is exhausted.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v1.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 module (Confirmation 1/2, Numbers 3 and 4 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 5 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 6 in the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data between modules. Data is passed between each module as described below:
GKD-B => GKD-V => GKD-C(1) => GKD-C(2) => GKD-E => GKD-BT
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Strategy with 1-3 take profits, trailing stop loss, multiple types of PnL volatility, and 2 backtesting styles
Baseline: Hull Moving Average as shown on the chart above
Volatility/Volume: Jurik Volty
Confirmation 1: Vortex
Confirmation 2: Fisher Transform
Exit: Rex Oscillator
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, or GKD-E. This allows traders understand to which module each indicator belongs and where each indicator fits into the GKD protocol chain.
Now that you have a general understanding of the NNFX algorithm and the GKD trading system. let's go over what's inside the GKD-B Baseline itself.
GKD Baseline Special Features and Notable Inputs
GKD Baseline v1.0 includes 63 different moving averages:
Adaptive Moving Average - AMA
ADXvma - Average Directional Volatility Moving Average
Ahrens Moving Average
Alexander Moving Average - ALXMA
Deviation Scaled Moving Average - DSMA
Donchian
Double Exponential Moving Average - DEMA
Double Smoothed Exponential Moving Average - DSEMA
Double Smoothed FEMA - DSFEMA
Double Smoothed Range Weighted EMA - DSRWEMA
Double Smoothed Wilders EMA - DSWEMA
Double Weighted Moving Average - DWMA
Ehlers Optimal Tracking Filter - EOTF
Exponential Moving Average - EMA
Fast Exponential Moving Average - FEMA
Fractal Adaptive Moving Average - FRAMA
Generalized DEMA - GDEMA
Generalized Double DEMA - GDDEMA
Hull Moving Average (Type 1) - HMA1
Hull Moving Average (Type 2) - HMA2
Hull Moving Average (Type 3) - HMA3
Hull Moving Average (Type 4) - HMA4
IE /2 - Early T3 by Tim Tilson
Integral of Linear Regression Slope - ILRS
Instantaneous Trendline
Kalman Filter
Kaufman Adaptive Moving Average - KAMA
Laguerre Filter
Leader Exponential Moving Average
Linear Regression Value - LSMA ( Least Squares Moving Average )
Linear Weighted Moving Average - LWMA
McGinley Dynamic
McNicholl EMA
Non-Lag Moving Average
Ocean NMA Moving Average - ONMAMA
Parabolic Weighted Moving Average
Probability Density Function Moving Average - PDFMA
Quadratic Regression Moving Average - QRMA
Regularized EMA - REMA
Range Weighted EMA - RWEMA
Recursive Moving Trendline
Simple Decycler - SDEC
Simple Jurik Moving Average - SJMA
Simple Moving Average - SMA
Sine Weighted Moving Average
Smoothed LWMA - SLWMA
Smoothed Moving Average - SMMA
Smoother
Super Smoother
T3
Three-pole Ehlers Butterworth
Three-pole Ehlers Smoother
Triangular Moving Average - TMA
Triple Exponential Moving Average - TEMA
Two-pole Ehlers Butterworth
Two-pole Ehlers smoother
Variable Index Dynamic Average - VIDYA
Variable Moving Average - VMA
Volume Weighted EMA - VEMA
Volume Weighted Moving Average - VWMA
Zero-Lag DEMA - Zero Lag Exponential Moving Average
Zero-Lag Moving Average
Zero Lag TEMA - Zero Lag Triple Exponential Moving Average
Adaptive Moving Average - AMA
Description. The Adaptive Moving Average (AMA) is a moving average that changes its sensitivity to price moves depending on the calculated volatility. It becomes more sensitive during periods when the price is moving smoothly in a certain direction and becomes less sensitive when the price is volatile.
ADXvma - Average Directional Volatility Moving Average
Linnsoft's ADXvma formula is a volatility-based moving average, with the volatility being determined by the value of the ADX indicator.
The ADXvma has the SMA in Chande's CMO replaced with an EMA , it then uses a few more layers of EMA smoothing before the "Volatility Index" is calculated.
A side effect is, those additional layers slow down the ADXvma when you compare it to Chande's Variable Index Dynamic Average VIDYA .
The ADXVMA provides support during uptrends and resistance during downtrends and will stay flat for longer, but will create some of the most accurate market signals when it decides to move.
Ahrens Moving Average
Richard D. Ahrens's Moving Average promises "Smoother Data" that isn't influenced by the occasional price spike. It works by using the Open and the Close in his formula so that the only time the Ahrens Moving Average will change is when the candlestick is either making new highs or new lows.
Alexander Moving Average - ALXMA
This Moving Average uses an elaborate smoothing formula and utilizes a 7 period Moving Average. It corresponds to fitting a second-order polynomial to seven consecutive observations. This moving average is rarely used in trading but is interesting as this Moving Average has been applied to diffusion indexes that tend to be very volatile.
Deviation Scaled Moving Average - DSMA
The Deviation-Scaled Moving Average is a data smoothing technique that acts like an exponential moving average with a dynamic smoothing coefficient. The smoothing coefficient is automatically updated based on the magnitude of price changes. In the Deviation-Scaled Moving Average, the standard deviation from the mean is chosen to be the measure of this magnitude. The resulting indicator provides substantial smoothing of the data even when price changes are small while quickly adapting to these changes.
Donchian
Donchian Channels are three lines generated by moving average calculations that comprise an indicator formed by upper and lower bands around a midrange or median band. The upper band marks the highest price of a security over N periods while the lower band marks the lowest price of a security over N periods.
Double Exponential Moving Average - DEMA
The Double Exponential Moving Average ( DEMA ) combines a smoothed EMA and a single EMA to provide a low-lag indicator. It's primary purpose is to reduce the amount of "lagging entry" opportunities, and like all Moving Averages, the DEMA confirms uptrends whenever price crosses on top of it and closes above it, and confirms downtrends when the price crosses under it and closes below it - but with significantly less lag.
Double Smoothed Exponential Moving Average - DSEMA
The Double Smoothed Exponential Moving Average is a lot less laggy compared to a traditional EMA . It's also considered a leading indicator compared to the EMA , and is best utilized whenever smoothness and speed of reaction to market changes are required.
Double Smoothed FEMA - DSFEMA
Same as the Double Exponential Moving Average (DEMA), but uses a faster version of EMA for its calculation.
Double Smoothed Range Weighted EMA - DSRWEMA
Range weighted exponential moving average (EMA) is, unlike the "regular" range weighted average calculated in a different way. Even though the basis - the range weighting - is the same, the way how it is calculated is completely different. By definition this type of EMA is calculated as a ratio of EMA of price*weight / EMA of weight. And the results are very different and the two should be considered as completely different types of averages. The higher than EMA to price changes responsiveness when the ranges increase remains in this EMA too and in those cases this EMA is clearly leading the "regular" EMA. This version includes double smoothing.
Double Smoothed Wilders EMA - DSWEMA
Welles Wilder was frequently using one "special" case of EMA (Exponential Moving Average) that is due to that fact (that he used it) sometimes called Wilder's EMA. This version is adding double smoothing to Wilder's EMA in order to make it "faster" (it is more responsive to market prices than the original) and is still keeping very smooth values.
Double Weighted Moving Average - DWMA
Double weighted moving average is an LWMA (Linear Weighted Moving Average). Instead of doing one cycle for calculating the LWMA, the indicator is made to cycle the loop 2 times. That produces a smoother values than the original LWMA
Ehlers Optimal Tracking Filter - EOTF
The Elher's Optimum Tracking Filter quickly adjusts rapid shifts in the price and yet is relatively smooth when the price has a sideways action. The operation of this filter is similar to Kaufman’s Adaptive Moving
Average
Exponential Moving Average - EMA
The EMA places more significance on recent data points and moves closer to price than the SMA ( Simple Moving Average ). It reacts faster to volatility due to its emphasis on recent data and is known for its ability to give greater weight to recent and more relevant data. The EMA is therefore seen as an enhancement over the SMA .
Fast Exponential Moving Average - FEMA
An Exponential Moving Average with a short look-back period.
Fractal Adaptive Moving Average - FRAMA
The Fractal Adaptive Moving Average by John Ehlers is an intelligent adaptive Moving Average which takes the importance of price changes into account and follows price closely enough to display significant moves whilst remaining flat if price ranges. The FRAMA does this by dynamically adjusting the look-back period based on the market's fractal geometry.
Generalized DEMA - GDEMA
The double exponential moving average (DEMA), was developed by Patrick Mulloy in an attempt to reduce the amount of lag time found in traditional moving averages. It was first introduced in the February 1994 issue of the magazine Technical Analysis of Stocks & Commodities in Mulloy's article "Smoothing Data with Faster Moving Averages.". Instead of using fixed multiplication factor in the final DEMA formula, the generalized version allows you to change it. By varying the "volume factor" form 0 to 1 you apply different multiplications and thus producing DEMA with different "speed" - the higher the volume factor is the "faster" the DEMA will be (but also the slope of it will be less smooth). The volume factor is limited in the calculation to 1 since any volume factor that is larger than 1 is increasing the overshooting to the extent that some volume factors usage makes the indicator unusable.
Generalized Double DEMA - GDDEMA
The double exponential moving average (DEMA), was developed by Patrick Mulloy in an attempt to reduce the amount of lag time found in traditional moving averages. It was first introduced in the February 1994 issue of the magazine Technical Analysis of Stocks & Commodities in Mulloy's article "Smoothing Data with Faster Moving Averages''. This is an extension of the Generalized DEMA using Tim Tillsons (the inventor of T3) idea, and is using GDEMA of GDEMA for calculation (which is the "middle step" of T3 calculation). Since there are no versions showing that middle step, this version covers that too. The result is smoother than Generalized DEMA, but is less smooth than T3 - one has to do some experimenting in order to find the optimal way to use it, but in any case, since it is "faster" than the T3 (Tim Tillson T3) and still smooth, it looks like a good compromise between speed and smoothness.
Hull Moving Average (Type 1) - HMA1
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses SMA for smoothing.
Hull Moving Average (Type 2) - HMA2
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses EMA for smoothing.
Hull Moving Average (Type 3) - HMA3
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses LWMA for smoothing.
Hull Moving Average (Type 4) - HMA4
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses SMMA for smoothing.
IE /2 - Early T3 by Tim Tilson and T3 new
T3 is basically an EMA on steroids, You can read about T3 here:
Integral of Linear Regression Slope - ILRS
A Moving Average where the slope of a linear regression line is simply integrated as it is fitted in a moving window of length N (natural numbers in maths) across the data. The derivative of ILRS is the linear regression slope. ILRS is not the same as a SMA ( Simple Moving Average ) of length N, which is actually the midpoint of the linear regression line as it moves across the data.
Instantaneous Trendline
The Instantaneous Trendline is created by removing the dominant cycle component from the price information which makes this Moving Average suitable for medium to long-term trading.
Kalman Filter
Kalman filter is an algorithm that uses a series of measurements observed over time, containing statistical noise and other inaccuracies. This means that the filter was originally designed to work with noisy data. Also, it is able to work with incomplete data. Another advantage is that it is designed for and applied in dynamic systems; our price chart belongs to such systems. This version is true to the original design of the trade-ready Kalman Filter where velocity is the triggering mechanism.
Kalman Filter is a more accurate smoothing/prediction algorithm than the moving average because it is adaptive: it accounts for estimation errors and tries to adjust its predictions from the information it learned in the previous stage. Theoretically, Kalman Filter consists of measurement and transition components.
Kaufman Adaptive Moving Average - KAMA
Developed by Perry Kaufman, Kaufman's Adaptive Moving Average (KAMA) is a moving average designed to account for market noise or volatility. KAMA will closely follow prices when the price swings are relatively small and the noise is low.
Laguerre Filter
The Laguerre Filter is a smoothing filter which is based on Laguerre polynomials. The filter requires the current price, three prior prices, a user defined factor called Alpha to fill its calculation.
Adjusting the Alpha coefficient is used to increase or decrease its lag and its smoothness.
Leader Exponential Moving Average
The Leader EMA was created by Giorgos E. Siligardos who created a Moving Average which was able to eliminate lag altogether whilst maintaining some smoothness. It was first described during his research paper "MACD Leader" where he applied this to the MACD to improve its signals and remove its lagging issue. This filter uses his leading MACD's "modified EMA" and can be used as a zero lag filter.
Linear Regression Value - LSMA ( Least Squares Moving Average )
LSMA as a Moving Average is based on plotting the end point of the linear regression line. It compares the current value to the prior value and a determination is made of a possible trend, eg. the linear regression line is pointing up or down.
Linear Weighted Moving Average - LWMA
LWMA reacts to price quicker than the SMA and EMA . Although it's similar to the Simple Moving Average , the difference is that a weight coefficient is multiplied to the price which means the most recent price has the highest weighting, and each prior price has progressively less weight. The weights drop in a linear fashion.
McGinley Dynamic
John McGinley created this Moving Average to track prices better than traditional Moving Averages. It does this by incorporating an automatic adjustment factor into its formula, which speeds (or slows) the indicator in trending, or ranging, markets.
McNicholl EMA
Dennis McNicholl developed this Moving Average to use as his center line for his "Better Bollinger Bands" indicator and was successful because it responded better to volatility changes over the standard SMA and managed to avoid common whipsaws.
Non-lag moving average
The Non Lag Moving average follows price closely and gives very quick signals as well as early signals of price change. As a standalone Moving Average, it should not be used on its own, but as an additional confluence tool for early signals.
Ocean NMA Moving Average - ONMAMA
Created by Jim Sloman, the NMA is a moving average that automatically adjusts to volatility without being programmed to do so. For more info, read his guide "Ocean Theory, an Introduction"
Parabolic Weighted Moving Average
The Parabolic Weighted Moving Average is a variation of the Linear Weighted Moving Average . The Linear Weighted Moving Average calculates the average by assigning different weights to each element in its calculation. The Parabolic Weighted Moving Average is a variation that allows weights to be changed to form a parabolic curve. It is done simply by using the Power parameter of this indicator.
Probability Density Function Moving Average - PDFMA
Probability density function based MA is a sort of weighted moving average that uses probability density function to calculate the weights. By its nature it is similar to a lot of digital filters.
Quadratic Regression Moving Average - QRMA
A quadratic regression is the process of finding the equation of the parabola that best fits a set of data. This moving average is an obscure concept that was posted to Forex forums in around 2008.
Regularized EMA - REMA
The regularized exponential moving average (REMA) by Chris Satchwell is a variation on the EMA (see Exponential Moving Average) designed to be smoother but not introduce too much extra lag.
Range Weighted EMA - RWEMA
This indicator is a variation of the range weighted EMA. The variation comes from a possible need to make that indicator a bit less "noisy" when it comes to slope changes. The method used for calculating this variation is the method described by Lee Leibfarth in his article "Trading With An Adaptive Price Zone".
Recursive Moving Trendline
Dennis Meyers's Recursive Moving Trendline uses a recursive (repeated application of a rule) polynomial fit, a technique that uses a small number of past values estimations of price and today's price to predict tomorrow's price.
Simple Decycler - SDEC
The Ehlers Simple Decycler study is a virtually zero-lag technical indicator proposed by John F. Ehlers. The original idea behind this study (and several others created by John F. Ehlers) is that market data can be considered a continuum of cycle periods with different cycle amplitudes. Thus, trending periods can be considered segments of longer cycles, or, in other words, low-frequency segments. Applying the right filter might help identify these segments.
Simple Loxx Moving Average - SLMA
A three stage moving average combining an adaptive EMA, a Kalman Filter, and a Kauffman adaptive filter.
Simple Moving Average - SMA
The SMA calculates the average of a range of prices by adding recent prices and then dividing that figure by the number of time periods in the calculation average. It is the most basic Moving Average which is seen as a reliable tool for starting off with Moving Average studies. As reliable as it may be, the basic moving average will work better when it's enhanced into an EMA .
Sine Weighted Moving Average
The Sine Weighted Moving Average assigns the most weight at the middle of the data set. It does this by weighting from the first half of a Sine Wave Cycle and the most weighting is given to the data in the middle of that data set. The Sine WMA closely resembles the TMA (Triangular Moving Average).
Smoothed LWMA - SLWMA
A smoothed version of the LWMA
Smoothed Moving Average - SMMA
The Smoothed Moving Average is similar to the Simple Moving Average ( SMA ), but aims to reduce noise rather than reduce lag. SMMA takes all prices into account and uses a long lookback period. Due to this, it's seen as an accurate yet laggy Moving Average.
Smoother
The Smoother filter is a faster-reacting smoothing technique which generates considerably less lag than the SMMA ( Smoothed Moving Average ). It gives earlier signals but can also create false signals due to its earlier reactions. This filter is sometimes wrongly mistaken for the superior Jurik Smoothing algorithm.
Super Smoother
The Super Smoother filter uses John Ehlers’s “Super Smoother” which consists of a Two pole Butterworth filter combined with a 2-bar SMA ( Simple Moving Average ) that suppresses the 22050 Hz Nyquist frequency: A characteristic of a sampler, which converts a continuous function or signal into a discrete sequence.
Three-pole Ehlers Butterworth
The 3 pole Ehlers Butterworth (as well as the Two pole Butterworth) are both superior alternatives to the EMA and SMA . They aim at producing less lag whilst maintaining accuracy. The 2 pole filter will give you a better approximation for price, whereas the 3 pole filter has superior smoothing.
Three-pole Ehlers smoother
The 3 pole Ehlers smoother works almost as close to price as the above mentioned 3 Pole Ehlers Butterworth. It acts as a strong baseline for signals but removes some noise. Side by side, it hardly differs from the Three Pole Ehlers Butterworth but when examined closely, it has better overshoot reduction compared to the 3 pole Ehlers Butterworth.
Triangular Moving Average - TMA
The TMA is similar to the EMA but uses a different weighting scheme. Exponential and weighted Moving Averages will assign weight to the most recent price data. Simple moving averages will assign the weight equally across all the price data. With a TMA (Triangular Moving Average), it is double smoother (averaged twice) so the majority of the weight is assigned to the middle portion of the data.
Triple Exponential Moving Average - TEMA
The TEMA uses multiple EMA calculations as well as subtracting lag to create a tool which can be used for scalping pullbacks. As it follows price closely, its signals are considered very noisy and should only be used in extremely fast-paced trading conditions.
Two-pole Ehlers Butterworth
The 2 pole Ehlers Butterworth (as well as the three pole Butterworth mentioned above) is another filter that cuts out the noise and follows the price closely. The 2 pole is seen as a faster, leading filter over the 3 pole and follows price a bit more closely. Analysts will utilize both a 2 pole and a 3 pole Butterworth on the same chart using the same period, but having both on chart allows its crosses to be traded.
Two-pole Ehlers smoother
A smoother version of the Two pole Ehlers Butterworth. This filter is the faster version out of the 3 pole Ehlers Butterworth. It does a decent job at cutting out market noise whilst emphasizing a closer following to price over the 3 pole Ehlers .
Variable Index Dynamic Average - VIDYA
Variable Index Dynamic Average Technical Indicator ( VIDYA ) was developed by Tushar Chande. It is an original method of calculating the Exponential Moving Average ( EMA ) with the dynamically changing period of averaging.
Variable Moving Average - VMA
The Variable Moving Average (VMA) is a study that uses an Exponential Moving Average being able to automatically adjust its smoothing factor according to the market volatility.
Volume Weighted EMA - VEMA
An EMA that uses a volume and price weighted calculation instead of the standard price input.
Volume Weighted Moving Average - VWMA
A Volume Weighted Moving Average is a moving average where more weight is given to bars with heavy volume than with light volume. Thus the value of the moving average will be closer to where most trading actually happened than it otherwise would be without being volume weighted.
Zero-Lag DEMA - Zero Lag Double Exponential Moving Average
John Ehlers's Zero Lag DEMA's aim is to eliminate the inherent lag associated with all trend following indicators which average a price over time. Because this is a Double Exponential Moving Average with Zero Lag, it has a tendency to overshoot and create a lot of false signals for swing trading. It can however be used for quick scalping or as a secondary indicator for confluence.
Zero-Lag Moving Average
The Zero Lag Moving Average is described by its creator, John Ehlers , as a Moving Average with absolutely no delay. And it's for this reason that this filter will cause a lot of abrupt signals which will not be ideal for medium to long-term traders. This filter is designed to follow price as close as possible whilst de-lagging data instead of basing it on regular data. The way this is done is by attempting to remove the cumulative effect of the Moving Average.
Zero-Lag TEMA - Zero Lag Triple Exponential Moving Average
Just like the Zero Lag DEMA , this filter will give you the fastest signals out of all the Zero Lag Moving Averages. This is useful for scalping but dangerous for medium to long-term traders, especially during market Volatility and news events. Having no lag, this filter also has no smoothing in its signals and can cause some very bizarre behavior when applied to certain indicators.
Exotic Triggers
This version of Baseline allows the user to select from exotic or source triggers. An exotic trigger determines trend by either slope or some other mechanism that is special to each moving average. A source trigger is one of 32 different source types from Loxx's Exotic Source Types. You can read about these source types here:
Volatility Goldie Locks Zone
This volatility filter is the standard first pass filter that is used for all NNFX systems despite the additional volatility/volume filter used in step 5. For this filter, price must fall into a range of maximum and minimum values calculated using multiples of volatility. Unlike the standard NNFX systems, this version of volatility filtering is separated from the core Baseline and uses it's own moving average with Loxx's Exotic Source Types. The green and red dots at the top of the chart denote whether a candle qualifies for a either or long or short respectively. The green and red triangles at the bottom of the chart denote whether the trigger has crossed up or down and qualifies inside the Goldie Locks zone. White coloring of the Goldie Locks Zone mean line is where volatility is too low to trade.
Volatility Types Included
v1.0 Included Volatility
Close-to-Close
Close-to-Close volatility is a classic and most commonly used volatility measure, sometimes referred to as historical volatility .
Volatility is an indicator of the speed of a stock price change. A stock with high volatility is one where the price changes rapidly and with a bigger amplitude. The more volatile a stock is, the riskier it is.
Close-to-close historical volatility calculated using only stock's closing prices. It is the simplest volatility estimator. But in many cases, it is not precise enough. Stock prices could jump considerably during a trading session, and return to the open value at the end. That means that a big amount of price information is not taken into account by close-to-close volatility .
Despite its drawbacks, Close-to-Close volatility is still useful in cases where the instrument doesn't have intraday prices. For example, mutual funds calculate their net asset values daily or weekly, and thus their prices are not suitable for more sophisticated volatility estimators.
Parkinson
Parkinson volatility is a volatility measure that uses the stock’s high and low price of the day.
The main difference between regular volatility and Parkinson volatility is that the latter uses high and low prices for a day, rather than only the closing price. That is useful as close to close prices could show little difference while large price movements could have happened during the day. Thus Parkinson's volatility is considered to be more precise and requires less data for calculation than the close-close volatility .
One drawback of this estimator is that it doesn't take into account price movements after market close. Hence it systematically undervalues volatility . That drawback is taken into account in the Garman-Klass's volatility estimator.
Garman-Klass
Garman Klass is a volatility estimator that incorporates open, low, high, and close prices of a security.
Garman-Klass volatility extends Parkinson's volatility by taking into account the opening and closing price. As markets are most active during the opening and closing of a trading session, it makes volatility estimation more accurate.
Garman and Klass also assumed that the process of price change is a process of continuous diffusion (Geometric Brownian motion). However, this assumption has several drawbacks. The method is not robust for opening jumps in price and trend movements.
Despite its drawbacks, the Garman-Klass estimator is still more effective than the basic formula since it takes into account not only the price at the beginning and end of the time interval but also intraday price extremums.
Researchers Rogers and Satchel have proposed a more efficient method for assessing historical volatility that takes into account price trends. See Rogers-Satchell Volatility for more detail.
Rogers-Satchell
Rogers-Satchell is an estimator for measuring the volatility of securities with an average return not equal to zero.
Unlike Parkinson and Garman-Klass estimators, Rogers-Satchell incorporates drift term (mean return not equal to zero). As a result, it provides a better volatility estimation when the underlying is trending.
The main disadvantage of this method is that it does not take into account price movements between trading sessions. It means an underestimation of volatility since price jumps periodically occur in the market precisely at the moments between sessions.
A more comprehensive estimator that also considers the gaps between sessions was developed based on the Rogers-Satchel formula in the 2000s by Yang-Zhang. See Yang Zhang Volatility for more detail.
Yang-Zhang
Yang Zhang is a historical volatility estimator that handles both opening jumps and the drift and has a minimum estimation error.
We can think of the Yang-Zhang volatility as the combination of the overnight (close-to-open volatility ) and a weighted average of the Rogers-Satchell volatility and the day’s open-to-close volatility . It considered being 14 times more efficient than the close-to-close estimator.
Garman-Klass-Yang-Zhang
Garman-Klass-Yang-Zhang (GKYZ) volatility estimator consists of using the returns of open, high, low, and closing prices in its calculation.
GKYZ volatility estimator takes into account overnight jumps but not the trend, i.e. it assumes that the underlying asset follows a GBM process with zero drift. Therefore the GKYZ volatility estimator tends to overestimate the volatility when the drift is different from zero. However, for a GBM process, this estimator is eight times more efficient than the close-to-close volatility estimator.
Exponential Weighted Moving Average
The Exponentially Weighted Moving Average (EWMA) is a quantitative or statistical measure used to model or describe a time series. The EWMA is widely used in finance, the main applications being technical analysis and volatility modeling.
The moving average is designed as such that older observations are given lower weights. The weights fall exponentially as the data point gets older – hence the name exponentially weighted.
The only decision a user of the EWMA must make is the parameter lambda. The parameter decides how important the current observation is in the calculation of the EWMA. The higher the value of lambda, the more closely the EWMA tracks the original time series.
Standard Deviation of Log Returns
This is the simplest calculation of volatility . It's the standard deviation of ln(close/close(1))
Pseudo GARCH(2,2)
This is calculated using a short- and long-run mean of variance multiplied by θ.
θavg(var ;M) + (1 − θ) avg (var ;N) = 2θvar/(M+1-(M-1)L) + 2(1-θ)var/(M+1-(M-1)L)
Solving for θ can be done by minimizing the mean squared error of estimation; that is, regressing L^-1var - avg (var; N) against avg (var; M) - avg (var; N) and using the resulting beta estimate as θ.
Average True Range
The average true range (ATR) is a technical analysis indicator, introduced by market technician J. Welles Wilder Jr. in his book New Concepts in Technical Trading Systems, that measures market volatility by decomposing the entire range of an asset price for that period.
The true range indicator is taken as the greatest of the following: current high less the current low; the absolute value of the current high less the previous close; and the absolute value of the current low less the previous close. The ATR is then a moving average, generally using 14 days, of the true ranges.
True Range Double
A special case of ATR that attempts to correct for volatility skew.
Additional features will be added in future releases.
This indicator is only available to ALGX Trading VIP group members . You can see the Author's Instructions below to get more information on how to get access.
Stripped Baseline [Loxx]Stripped Baseline is a stripped down version of Loxx's Baseline indicator. This version includes the core baseline only to reduce processing overhead.
What is Baseline?
A core moving average used as part of a volatility-based trading system. This baseline includes 41 moving average types to choose from. See details here:
Also included are 35 different source types for price input. Read more about these source types here:
The full Baseline trading system can be found here:
v1.0 Included Moving Averages
Adaptive Moving Average - AMA
ADXvma - Average Directional Volatility Moving Average
Ahrens Moving Average
Alexander Moving Average - ALXMA
Double Exponential Moving Average - DEMA
Double Smoothed Exponential Moving Average - DSEMA
Exponential Moving Average - EMA
Fast Exponential Moving Average - FEMA
Fractal Adaptive Moving Average - FRAMA
Hull Moving Average - HMA
IE /2 - Early maout by Tim Tilson
Integral of Linear Regression Slope - ILRS
Instantaneous Trendline
Kalman Filter
Kaufman Adaptive Moving Average - KAMA
Laguerre Filter
Leader Exponential Moving Average
Linear Regression Value - LSMA ( Least Squares Moving Average )
Linear Weighted Moving Average - LWMA
McGinley Dynamic
McNicholl EMA
Non-Lag Moving Average
Parabolic Weighted Moving Average
Recursive Moving Trendline
Simple Moving Average - SMA
Sine Weighted Moving Average
Smoothed Moving Average - SMMA
Smoother
Super Smoother
T3
Three-pole Ehlers Butterworth
Three-pole Ehlers Smoother
Triangular Moving Average - TMA
Triple Exponential Moving Average - TEMA
Two-pole Ehlers Butterworth
Two-pole Ehlers smoother
Variable Index Dynamic Average - VIDYA
Volume Weighted EMA - VEMA
Zero-Lag DEMA - Zero Lag Double Exponential Moving Average
Zero-Lag Moving Average
Zero Lag TEMA - Zero Lag Triple Exponential Moving Average
Volatility Types
v1.0 Included Volatility
Average True Range (ATR)
True Range Double ( TRD )
Trading Rules
Post Baseline Cross Qualifier (PBCQ): If price crosses the baseline but the trade is invalid due to additional qualifiers, then the strategy doesn't enter a trade on that candle. This setting allows you override this disqualification in the following manner: If price crosses XX bars ago and is now qualified by other qualifiers, then the strategy enters a trade.
Volatility: If price crosses the baseline, we check to see how far it has moved in terms of multiples of volatility denoted in price (ATR x multiple). If price has moved by at least "Qualifier multiplier" and less than "Range Multiplier", then the strategy enters a trade. This range is shown on the chart with yellow area that tracks price above/blow the baseline. Also, see the dots at the top of the chart. If the dots are green, then price passes the volatility test for a long. If the dots are red, then price passes the volatility test for a short.
Additional moving averages, volatility types, qualifiers, and other advanced features will be added in future releases.
Baseline Backtest
Expected Move w/ Volatility Panel (advanced) [Loxx]This indicator shows the expected range of movement of price given the assumption that price is log-normally distributed. This includes 3 multiples of standard deviation and 1 user selected level input as a multiple of standard deviation. Expected assumes that volatility remains static on the next bar. In reality, this may or may not be the case, so use caution when making broad assumptions about the levels shown when using this indicator. However, these levels match the same levels on Loxx's backtests and Multi-Panel indicator. These static levels are used as the take profit targets and stoploss on all Loxx's scripts previously posted.
This indicator can be be used on all timeframes, but the internal timeframe must be higher than the current timeframe or an error is thrown. The purpose for internal MTF is so that you can track the deviation range from higher timeframes on lower timeframes. When "current bar" is selected, this indicator will change with live prices changes. This is useful if you wish to enter a trade before the current bar closes and need to know the deviation ranges before the close. Current bar is also useful to see the past ranges of literally that bar. When "past bar" is selected, then the values shown on the current bar are values that were calculated on the last bar. The previous bar setting is useful to track price changes with the assumption that you entered a trade at the close of the previous bar. The default set to the previous bar. (careful, this default setting won't match Loxx's Muti-Panel tool since the Multi-Panel is built using the current bar. To make them match, you must change this setting to current bar)
I've included the ability for you to smooth the output around a moving average. Included are Loxx's Moving Averages. There are 41 to choose from. See more details here:
Smoothing applied yielding Keltner Channels
Also included are various UI options to manipulate line styling and colors.
Volatility Panel
Shows information about user selected volatility included confidence range of the chosen volatility. The following volatility types are included with additional volatility types to added in future releases.
Close-to-Close
Close-to-Close volatility is a classic and most commonly used volatility measure, sometimes referred to as historical volatility .
Volatility is an indicator of the speed of a stock price change. A stock with high volatility is one where the price changes rapidly and with a bigger amplitude. The more volatile a stock is, the riskier it is.
Close-to-close historical volatility calculated using only stock's closing prices. It is the simplest volatility estimator. But in many cases, it is not precise enough. Stock prices could jump considerably during a trading session, and return to the open value at the end. That means that a big amount of price information is not taken into account by close-to-close volatility .
Despite its drawbacks, Close-to-Close volatility is still useful in cases where the instrument doesn't have intraday prices. For example, mutual funds calculate their net asset values daily or weekly, and thus their prices are not suitable for more sophisticated volatility estimators.
Parkinson
Parkinson volatility is a volatility measure that uses the stock’s high and low price of the day.
The main difference between regular volatility and Parkinson volatility is that the latter uses high and low prices for a day, rather than only the closing price. That is useful as close to close prices could show little difference while large price movements could have happened during the day. Thus Parkinson's volatility is considered to be more precise and requires less data for calculation than the close-close volatility .
One drawback of this estimator is that it doesn't take into account price movements after market close. Hence it systematically undervalues volatility . That drawback is taken into account in the Garman-Klass's volatility estimator.
Garman-Klass
Garman Klass is a volatility estimator that incorporates open, low, high, and close prices of a security.
Garman-Klass volatility extends Parkinson's volatility by taking into account the opening and closing price. As markets are most active during the opening and closing of a trading session, it makes volatility estimation more accurate.
Garman and Klass also assumed that the process of price change is a process of continuous diffusion (geometric Brownian motion). However, this assumption has several drawbacks. The method is not robust for opening jumps in price and trend movements.
Despite its drawbacks, the Garman-Klass estimator is still more effective than the basic formula since it takes into account not only the price at the beginning and end of the time interval but also intraday price extremums.
Researchers Rogers and Satchel have proposed a more efficient method for assessing historical volatility that takes into account price trends. See Rogers-Satchell Volatility for more detail.
Rogers-Satchell
Rogers-Satchell is an estimator for measuring the volatility of securities with an average return not equal to zero.
Unlike Parkinson and Garman-Klass estimators, Rogers-Satchell incorporates drift term (mean return not equal to zero). As a result, it provides a better volatility estimation when the underlying is trending.
The main disadvantage of this method is that it does not take into account price movements between trading sessions. It means an underestimation of volatility since price jumps periodically occur in the market precisely at the moments between sessions.
A more comprehensive estimator that also considers the gaps between sessions was developed based on the Rogers-Satchel formula in the 2000s by Yang-Zhang. See Yang Zhang Volatility for more detail.
Yang-Zhang
Yang Zhang is a historical volatility estimator that handles both opening jumps and the drift and has a minimum estimation error.
We can think of the Yang-Zhang volatility as the combination of the overnight (close-to-open volatility ) and a weighted average of the Rogers-Satchell volatility and the day’s open-to-close volatility . It considered being 14 times more efficient than the close-to-close estimator.
Garman-Klass-Yang-Zhang
Garman Klass is a volatility estimator that incorporates open, low, high, and close prices of a security.
Garman-Klass volatility extends Parkinson's volatility by taking into account the opening and closing price. As markets are most active during the opening and closing of a trading session, it makes volatility estimation more accurate.
Garman and Klass also assumed that the process of price change is a process of continuous diffusion (geometric Brownian motion). However, this assumption has several drawbacks. The method is not robust for opening jumps in price and trend movements.
Despite its drawbacks, the Garman-Klass estimator is still more effective than the basic formula since it takes into account not only the price at the beginning and end of the time interval but also intraday price extremums.
Researchers Rogers and Satchel have proposed a more efficient method for assessing historical volatility that takes into account price trends. See Rogers-Satchell Volatility for more detail.
Exponential Weighted Moving Average
The Exponentially Weighted Moving Average (EWMA) is a quantitative or statistical measure used to model or describe a time series. The EWMA is widely used in finance, the main applications being technical analysis and volatility modeling.
The moving average is designed as such that older observations are given lower weights. The weights fall exponentially as the data point gets older – hence the name exponentially weighted.
The only decision a user of the EWMA must make is the parameter lambda. The parameter decides how important the current observation is in the calculation of the EWMA. The higher the value of lambda, the more closely the EWMA tracks the original time series.
Standard Deviation of Log Returns
This is the simplest calculation of volatility . It's the standard deviation of ln(close/close(1))
Pseudo GARCH(2,2)
This is calculated using a short- and long-run mean of variance multiplied by θ.
θavg(var ;M) + (1 − θ) avg (var ;N) = 2θvar/(M+1-(M-1)L) + 2(1-θ)var/(M+1-(M-1)L)
Solving for θ can be done by minimizing the mean squared error of estimation; that is, regressing L^-1var - avg (var; N) against avg (var; M) - avg (var; N) and using the resulting beta estimate as θ.
Average True Range
The average true range (ATR) is a technical analysis indicator, introduced by market technician J. Welles Wilder Jr. in his book New Concepts in Technical Trading Systems, that measures market volatility by decomposing the entire range of an asset price for that period.
The true range indicator is taken as the greatest of the following: current high less the current low; the absolute value of the current high less the previous close; and the absolute value of the current low less the previous close. The ATR is then a moving average, generally using 14 days, of the true ranges.
True Range Double
A special case of ATR that attempts to correct for volatility skew.
Chi-squared Confidence Interval:
Confidence interval of volatility is calculated using an inverse CDF of a Chi-Squared Distribution. You can change the volatility input used to either realized, upper confidence interval, or lower confidence interval. This is included in case you'd like to see how far price can extend if volatility hits it's upper or lower confidence levels. Generally, you'd just used realized volatility , so I wouldn't change this setting.
Inverse CDF of a Chi-Squared Distribution
The chi-square distribution is a one-parameter family of curves. The parameter ν is the degrees of freedom.
The icdf of the chi-square distribution is
x=F^−1(p∣ν) = {x:F(x∣ν) = p}
where
p=F(x∣ν)= ∫ (t^(v-2)/2 * e^t/2) / (2^(v/2) / Γ(v/2))
ν is the degrees of freedom, and Γ( · ) is the Gamma function. The result p is the probability that a single observation from the chi-square distribution with ν degrees of freedom falls in the interval .
Related Indicators
Multi-Panel: Trade-Volatility-Probability
Variety Distribution Probability Cone
Multi-Panel: Trade-Volatility-Probability [Loxx]Multi-Panel: Trade-Volatility-Probability shows user selected and volatility-based price levels and probabilities on the chart. This is useful for both options and all styles of up/down trading methods that rely on volatility.
Trading Panel: Shows trading information to take profits and stop-loss based on multiples of volatility. Also shows equity inputs by the user to calculate optimal position size
Key things to note about the Trading Panel
-Trade side: Long or short. you change this this to change the take profit and SL levels in displayed on the table to be used w/ up/down trading styles that rely on volatility stops
-Account size: User enters total balance available for trade
-Risk: Total % of account size you're willing to lose should the SL be hit
-Position size: Size of the position given the SL and your preferred Risk
-Take profit/Stop loss levels: Based on multipliers selected by the user in settings. These shouldn't be changed unless you really know what you're doing with volatility stops
-Entry: Source price. can be 1 of 37 different prices. See Loxx's Expanded Source Types:
Volatility Panel: Shows information about the volatility the user selected to be used to take profit/stop-loss/range calculations. Volatility types included are:
Close-to-Close
Close-to-Close volatility is a classic and most commonly used volatility measure, sometimes referred to as historical volatility .
Volatility is an indicator of the speed of a stock price change. A stock with high volatility is one where the price changes rapidly and with a bigger amplitude. The more volatile a stock is, the riskier it is.
Close-to-close historical volatility calculated using only stock's closing prices. It is the simplest volatility estimator. But in many cases, it is not precise enough. Stock prices could jump considerably during a trading session, and return to the open value at the end. That means that a big amount of price information is not taken into account by close-to-close volatility .
Despite its drawbacks, Close-to-Close volatility is still useful in cases where the instrument doesn't have intraday prices. For example, mutual funds calculate their net asset values daily or weekly, and thus their prices are not suitable for more sophisticated volatility estimators.
Parkinson
Parkinson volatility is a volatility measure that uses the stock’s high and low price of the day.
The main difference between regular volatility and Parkinson volatility is that the latter uses high and low prices for a day, rather than only the closing price. That is useful as close to close prices could show little difference while large price movements could have happened during the day. Thus Parkinson's volatility is considered to be more precise and requires less data for calculation than the close-close volatility.
One drawback of this estimator is that it doesn't take into account price movements after market close. Hence it systematically undervalues volatility. That drawback is taken into account in the Garman-Klass's volatility estimator.
Garman-Klass
Garman Klass is a volatility estimator that incorporates open, low, high, and close prices of a security.
Garman-Klass volatility extends Parkinson's volatility by taking into account the opening and closing price. As markets are most active during the opening and closing of a trading session, it makes volatility estimation more accurate.
Garman and Klass also assumed that the process of price change is a process of continuous diffusion (geometric Brownian motion). However, this assumption has several drawbacks. The method is not robust for opening jumps in price and trend movements.
Despite its drawbacks, the Garman-Klass estimator is still more effective than the basic formula since it takes into account not only the price at the beginning and end of the time interval but also intraday price extremums.
Researchers Rogers and Satchel have proposed a more efficient method for assessing historical volatility that takes into account price trends. See Rogers-Satchell Volatility for more detail.
Rogers-Satchell
Rogers-Satchell is an estimator for measuring the volatility of securities with an average return not equal to zero.
Unlike Parkinson and Garman-Klass estimators, Rogers-Satchell incorporates drift term (mean return not equal to zero). As a result, it provides a better volatility estimation when the underlying is trending.
The main disadvantage of this method is that it does not take into account price movements between trading sessions. It means an underestimation of volatility since price jumps periodically occur in the market precisely at the moments between sessions.
A more comprehensive estimator that also considers the gaps between sessions was developed based on the Rogers-Satchel formula in the 2000s by Yang-Zhang. See Yang Zhang Volatility for more detail.
Yang-Zhang
Yang Zhang is a historical volatility estimator that handles both opening jumps and the drift and has a minimum estimation error.
We can think of the Yang-Zhang volatility as the combination of the overnight (close-to-open volatility ) and a weighted average of the Rogers-Satchell volatility and the day’s open-to-close volatility . It considered being 14 times more efficient than the close-to-close estimator.
Garman-Klass-Yang-Zhang
Garman Klass is a volatility estimator that incorporates open, low, high, and close prices of a security.
Garman-Klass volatility extends Parkinson's volatility by taking into account the opening and closing price. As markets are most active during the opening and closing of a trading session, it makes volatility estimation more accurate.
Garman and Klass also assumed that the process of price change is a process of continuous diffusion (geometric Brownian motion). However, this assumption has several drawbacks. The method is not robust for opening jumps in price and trend movements.
Despite its drawbacks, the Garman-Klass estimator is still more effective than the basic formula since it takes into account not only the price at the beginning and end of the time interval but also intraday price extremums.
Researchers Rogers and Satchel have proposed a more efficient method for assessing historical volatility that takes into account price trends. See Rogers-Satchell Volatility for more detail.
Exponential Weighted Moving Average
The Exponentially Weighted Moving Average (EWMA) is a quantitative or statistical measure used to model or describe a time series. The EWMA is widely used in finance, the main applications being technical analysis and volatility modeling.
The moving average is designed as such that older observations are given lower weights. The weights fall exponentially as the data point gets older – hence the name exponentially weighted.
The only decision a user of the EWMA must make is the parameter lambda. The parameter decides how important the current observation is in the calculation of the EWMA. The higher the value of lambda, the more closely the EWMA tracks the original time series.
Standard Deviation of Log Returns
This is the simplest calculation of volatility . It's the standard deviation of ln(close/close(1))
Pseudo GARCH(2,2)
This is calculated using a short- and long-run mean of variance multiplied by θ.
θavg(var ;M) + (1 − θ) avg (var ;N) = 2θvar/(M+1-(M-1)L) + 2(1-θ)var/(M+1-(M-1)L)
Solving for θ can be done by minimizing the mean squared error of estimation; that is, regressing L^-1var - avg (var; N) against avg (var; M) - avg (var; N) and using the resulting beta estimate as θ.
Average True Range
The average true range (ATR) is a technical analysis indicator, introduced by market technician J. Welles Wilder Jr. in his book New Concepts in Technical Trading Systems, that measures market volatility by decomposing the entire range of an asset price for that period.
The true range indicator is taken as the greatest of the following: current high less the current low; the absolute value of the current high less the previous close; and the absolute value of the current low less the previous close. The ATR is then a moving average, generally using 14 days, of the true ranges.
True Range Double
A special case of ATR that attempts to correct for volatility skew.
Chi-squared Confidence Interval:
Confidence interval of volatility is calculated using an inverse CDF of a Chi-Squared Distribution. You can change the volatility input used to either realized, upper confidence interval, or lower confidence interval. This is included in case you'd like to see how far price can extend if volatility hits it's upper or lower confidence levels. Generally, you'd just used realized volatility, so I wouldn't change this setting.
Inverse CDF of a Chi-Squared Distribution
The chi-square distribution is a one-parameter family of curves. The parameter ν is the degrees of freedom.
The icdf of the chi-square distribution is
x=F^−1(p∣ν) = {x:F(x∣ν) = p}
where
p=F(x∣ν)= ∫ (t^(v-2)/2 * e^t/2) / (2^(v/2) / Γ(v/2))
ν is the degrees of freedom, and Γ( · ) is the Gamma function. The result p is the probability that a single observation from the chi-square distribution with ν degrees of freedom falls in the interval .
Additional notes on Volatility Panel
-Shows both current timeframe volatility per candle at whatever date backward you select
-Shows annualized volatility basaed on selected days per year and per bar volatility; this is automaitcally caulculated no matter the timeframe used. This means that it'll calculate annualized volatility for the current candle even on the 1 second timeframe. Days per year should be 252 for everything but cryptocurrency; however, for all types of tradable assets, anything over the 3 day timeframe will calculate on 365 days.
Probability Panel
This panel shows the probability levels of a user selected upper and lower price boundary. This includes the inside range of volatility between the lower and upper price levels and the outside probability below the lower price level and above the upper price level. These values are calculated using the CDF (cumulative density function) of a normal distribution. In simpler terms, CDF returns area under a bell curve between two points left and right, or for our purposes, high and low. This yeilds the probabilities you see in the Probability Panel. See the following graphic to visualize how this works:
The red line is the entry bar; the yellow line is the "mean" but in this case just the chosen source price.
Other things to know
You can turn on/off all labels and levels and fills
Profit Bands [Loxx]Profit Bands is a supplementary indicator to be used with Loxx's backtests and combination indicators that use volatility-based take profits and stop loss. This indicator includes two types of volatility: Average True Range and True Range Double. Additional volatility sources will be added in the future. The lines painted on the screen are multiples of ATR for Take Profits and Stoploss for Long/Short positions that you can change in the settings. 3 Take Profits and 1 Stoploss is supported. You can turn on/off each UI element. Position size is determined by calculating the size of an investment where you'd lose only X% of your balance if the Stoploss is hit. You can enter your total balance available to trade and the desired % risk you'd be willing to lose at SL. Typically this number is 1-2% of total balance per trade.
Always remember to wait for bar close on a signal to and then peg this indicator to 1 bar backward to fix the price levels the then seed the exact levels you'll use for Take Profits and Stoploss. This indicator will match exactly the levels in other indicators in Loxx's scripts such as Kaleidoscope. You would overlay this script over any other script that uses volatility stops to see where to place your TPs and SL
Possible RSI [Loxx]Possible RSI is a normalized, variety second-pass normalized, Variety RSI with Dynamic Zones and optionl High-Pass IIR digital filtering of source price input. This indicator includes 7 types of RSI.
High-Pass Fitler (optional)
The Ehlers Highpass Filter is a technical analysis tool developed by John F. Ehlers. Based on aerospace analog filters, this filter aims at reducing noise from price data. Ehlers Highpass Filter eliminates wave components with periods longer than a certain value. This reduces lag and makes the oscialltor zero mean. This turns the RSI output into something more similar to Stochasitc RSI where it repsonds to price very quickly.
First Normalization Pass
RSI (Relative Strength Index) is already normalized. Hence, making a normalized RSI seems like a nonsense... if it was not for the "flattening" property of RSI. RSI tends to be flatter and flatter as we increase the calculating period--to the extent that it becomes unusable for levels trading if we increase calculating periods anywhere over the broadly recommended period 8 for RSI. In order to make that (calculating period) have less impact to significant levels usage of RSI trading style in this version a sort of a "raw stochastic" (min/max) normalization is applied.
Second-Pass Variety Normalization Pass
There are three options to choose from:
1. Gaussian (Fisher Transform), this is the default: The Fisher Transform is a function created by John F. Ehlers that converts prices into a Gaussian normal distribution. The normaliztion helps highlights when prices have moved to an extreme, based on recent prices. This may help in spotting turning points in the price of an asset. It also helps show the trend and isolate the price waves within a trend.
2. Softmax: The softmax function, also known as softargmax: or normalized exponential function, converts a vector of K real numbers into a probability distribution of K possible outcomes. It is a generalization of the logistic function to multiple dimensions, and used in multinomial logistic regression. The softmax function is often used as the last activation function of a neural network to normalize the output of a network to a probability distribution over predicted output classes, based on Luce's choice axiom.
3. Regular Normalization (devaitions about the mean): Converts a vector of K real numbers into a probability distribution of K possible outcomes without using log sigmoidal transformation as is done with Softmax. This is basically Softmax without the last step.
Dynamic Zones
As explained in "Stocks & Commodities V15:7 (306-310): Dynamic Zones by Leo Zamansky, Ph .D., and David Stendahl"
Most indicators use a fixed zone for buy and sell signals. Here’ s a concept based on zones that are responsive to past levels of the indicator.
One approach to active investing employs the use of oscillators to exploit tradable market trends. This investing style follows a very simple form of logic: Enter the market only when an oscillator has moved far above or below traditional trading lev- els. However, these oscillator- driven systems lack the ability to evolve with the market because they use fixed buy and sell zones. Traders typically use one set of buy and sell zones for a bull market and substantially different zones for a bear market. And therein lies the problem.
Once traders begin introducing their market opinions into trading equations, by changing the zones, they negate the system’s mechanical nature. The objective is to have a system automatically define its own buy and sell zones and thereby profitably trade in any market — bull or bear. Dynamic zones offer a solution to the problem of fixed buy and sell zones for any oscillator-driven system.
An indicator’s extreme levels can be quantified using statistical methods. These extreme levels are calculated for a certain period and serve as the buy and sell zones for a trading system. The repetition of this statistical process for every value of the indicator creates values that become the dynamic zones. The zones are calculated in such a way that the probability of the indicator value rising above, or falling below, the dynamic zones is equal to a given probability input set by the trader.
To better understand dynamic zones, let's first describe them mathematically and then explain their use. The dynamic zones definition:
Find V such that:
For dynamic zone buy: P{X <= V}=P1
For dynamic zone sell: P{X >= V}=P2
where P1 and P2 are the probabilities set by the trader, X is the value of the indicator for the selected period and V represents the value of the dynamic zone.
The probability input P1 and P2 can be adjusted by the trader to encompass as much or as little data as the trader would like. The smaller the probability, the fewer data values above and below the dynamic zones. This translates into a wider range between the buy and sell zones. If a 10% probability is used for P1 and P2, only those data values that make up the top 10% and bottom 10% for an indicator are used in the construction of the zones. Of the values, 80% will fall between the two extreme levels. Because dynamic zone levels are penetrated so infrequently, when this happens, traders know that the market has truly moved into overbought or oversold territory.
Calculating the Dynamic Zones
The algorithm for the dynamic zones is a series of steps. First, decide the value of the lookback period t. Next, decide the value of the probability Pbuy for buy zone and value of the probability Psell for the sell zone.
For i=1, to the last lookback period, build the distribution f(x) of the price during the lookback period i. Then find the value Vi1 such that the probability of the price less than or equal to Vi1 during the lookback period i is equal to Pbuy. Find the value Vi2 such that the probability of the price greater or equal to Vi2 during the lookback period i is equal to Psell. The sequence of Vi1 for all periods gives the buy zone. The sequence of Vi2 for all periods gives the sell zone.
In the algorithm description, we have: Build the distribution f(x) of the price during the lookback period i. The distribution here is empirical namely, how many times a given value of x appeared during the lookback period. The problem is to find such x that the probability of a price being greater or equal to x will be equal to a probability selected by the user. Probability is the area under the distribution curve. The task is to find such value of x that the area under the distribution curve to the right of x will be equal to the probability selected by the user. That x is the dynamic zone.
7 Types of RSI
See here to understand which RSI types are included:
Included:
Bar coloring
4 signal types
Alerts
Loxx's Expanded Source Types
Loxx's Variety RSI
Loxx's Dynamic Zones
STD-Filtered, Adaptive Exponential Hull Moving Average [Loxx]STD-Filtered, Adaptive Exponential Hull Moving Average is a Kaufman Efficiency Ratio Adaptive Hull Moving Average that uses EMA instead of WMA for its computation. I've also added standard deviation stepping to further smooth the signal. Using EMA instead of WMA turns the Hull into what's called the AEHMA. You can read more about the EHMA here: eceweb1.rutgers.edu
What is the traditional Hull Moving Average?
The Hull Moving Average (HMA) attempts to minimize the lag of a traditional moving average while retaining the smoothness of the moving average line. Developed by Alan Hull in 2005, this indicator makes use of weighted moving averages to prioritize more recent values and greatly reduce lag. The resulting average is more responsive and well-suited for identifying entry points.
What is Kaufman's Efficiency Ratio?
The Efficiency Ratio (ER) was first presented by Perry Kaufman in his 1995 book ‘Smarter Trading‘. It is calculated by dividing the price change over a period by the absolute sum of the price movements that occurred to achieve that change. The resulting ratio ranges between 0 and 1 with higher values representing a more efficient or trending market.
The value of the ER ranges between 0 and 1. It has the value of 1 when prices move in the same direction for the full time over which the indicator is calculated, e.g. n bars period. It has a value of 0 when prices are unchanged over the n periods. When prices move in wide swings within the interval, the sum of the denominator becomes very large compared to the numerator and ER approaches zero.
Some uses for ER:
A qualifier for a trend following trade; a trend is considered “persistent” only when RE is above a certain value, e.g. 0.3 or 0.4 .
A filter to screen out choppy stocks/markets, where breakouts are frequently “fakeouts”.
In an adaptive trading system, helping to determine whether to apply a trend following algorithm or a mean reversion algorithm.
It is used in the calculation of Kaufman’s Adaptive Moving Average (KAMA).
How to calculate the Hull Adaptive Moving Average (HAMA)
Find Signal to Noise ratio (SNR)
Normalize SNR from 0 to 1
Calculate adaptive alphas
Apply EMAs
Included
Bar coloring
Signals
Alerts
Loxx's Expanded Source Types
Ehlers Linear Extrapolation Predictor [Loxx]Ehlers Linear Extrapolation Predictor is a new indicator by John Ehlers. The translation of this indicator into PineScript™ is a collaborative effort between @cheatcountry and I.
The following is an excerpt from "PREDICTION" , by John Ehlers
Niels Bohr said “Prediction is very difficult, especially if it’s about the future.”. Actually, prediction is pretty easy in the context of technical analysis. All you have to do is to assume the market will behave in the immediate future just as it has behaved in the immediate past. In this article we will explore several different techniques that put the philosophy into practice.
LINEAR EXTRAPOLATION
Linear extrapolation takes the philosophical approach quite literally. Linear extrapolation simply takes the difference of the last two bars and adds that difference to the value of the last bar to form the prediction for the next bar. The prediction is extended further into the future by taking the last predicted value as real data and repeating the process of adding the most recent difference to it. The process can be repeated over and over to extend the prediction even further.
Linear extrapolation is an FIR filter, meaning it depends only on the data input rather than on a previously computed value. Since the output of an FIR filter depends only on delayed input data, the resulting lag is somewhat like the delay of water coming out the end of a hose after it supplied at the input. Linear extrapolation has a negative group delay at the longer cycle periods of the spectrum, which means water comes out the end of the hose before it is applied at the input. Of course the analogy breaks down, but it is fun to think of it that way. As shown in Figure 1, the actual group delay varies across the spectrum. For frequency components less than .167 (i.e. a period of 6 bars) the group delay is negative, meaning the filter is predictive. However, the filter has a positive group delay for cycle components whose periods are shorter than 6 bars.
Figure 1
Here’s the practical ramification of the group delay: Suppose we are projecting the prediction 5 bars into the future. This is fine as long as the market is continued to trend up in the same direction. But, when we get a reversal, the prediction continues upward for 5 bars after the reversal. That is, the prediction fails just when you need it the most. An interesting phenomenon is that, regardless of how far the extrapolation extends into the future, the prediction will always cross the signal at the same spot along the time axis. The result is that the prediction will have an overshoot. The amplitude of the overshoot is a function of how far the extrapolation has been carried into the future.
But the overshoot gives us an opportunity to make a useful prediction at the cyclic turning point of band limited signals (i.e. oscillators having a zero mean). If we reduce the overshoot by reducing the gain of the prediction, we then also move the crossing of the prediction and the original signal into the future. Since the group delay varies across the spectrum, the effect will be less effective for the shorter cycles in the data. Nonetheless, the technique is effective for both discretionary trading and automated trading in the majority of cases.
EXPLORING THE CODE
Before we predict, we need to create a band limited indicator from which to make the prediction. I have selected a “roofing filter” consisting of a High Pass Filter followed by a Low Pass Filter. The tunable parameter of the High Pass Filter is HPPeriod. Think of it as a “stone wall filter” where cycle period components longer than HPPeriod are completely rejected and cycle period components shorter than HPPeriod are passed without attenuation. If HPPeriod is set to be a large number (e.g. 250) the indicator will tend to look more like a trending indicator. If HPPeriod is set to be a smaller number (e.g. 20) the indicator will look more like a cycling indicator. The Low Pass Filter is a Hann Windowed FIR filter whose tunable parameter is LPPeriod. Think of it as a “stone wall filter” where cycle period components shorter than LPPeriod are completely rejected and cycle period components longer than LPPeriod are passed without attenuation. The purpose of the Low Pass filter is to smooth the signal. Thus, the combination of these two filters forms a “roofing filter”, named Filt, that passes spectrum components between LPPeriod and HPPeriod.
Since working into the future is not allowed in EasyLanguage variables, we need to convert the Filt variable to the data array XX . The data array is first filled with real data out to “Length”. I selected Length = 10 simply to have a convenient starting point for the prediction. The next block of code is the prediction into the future. It is easiest to understand if we consider the case where count = 0. Then, in English, the next value of the data array is equal to the current value of the data array plus the difference between the current value and the previous value. That makes the prediction one bar into the future. The process is repeated for each value of count until predictions up to 10 bars in the future are contained in the data array. Next, the selected prediction is converted from the data array to the variable “Prediction”. Filt is plotted in Red and Prediction is plotted in yellow.
The Predict Extrapolation indicator is shown above for the Emini S&P Futures contract using the default input parameters. Filt is plotted in red and Predict is plotted in yellow. The crossings of the Predict and Filt lines provide reliable buy and sell timing signals. There is some overshoot for the shorter cycle periods, for example in February and March 2021, but the only effect is a late timing signal. Further reducing the gain and/or reducing the BarsFwd inputs would provide better timing signals during this period.
ADDITIONS
Loxx's Expanded source types:
Library for expanded source types:
Explanation for expanded source types:
Three different signal types: 1) Prediction/Filter crosses; 2) Prediction middle crosses; and, 3) Filter middle crosses.
Bar coloring to color trend.
Signals, both Long and Short.
Alerts, both Long and Short.
