GKD-C Polychromatic Momentum [Loxx]Giga Kaleidoscope GKD-C Polychromatic Momentum is a Confirmation module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
█ GKD-C Polychromatic Momentum
Polychromatic Momentum: A Refined Approach to Momentum Calculation in Technical Analysis
In the world of finance and trading, technical analysis plays a crucial role in understanding price movements and making informed decisions. One popular method in technical analysis is calculating momentum, which indicates the strength of a trend by analyzing the rate of change in prices. The following explains a specific implementation of momentum calculation known as Polychromatic Momentum, highlighting its features and potential advantages over traditional momentum calculations.
Polychromatic Momentum Calculation
Polychromatic Momentum enhances the traditional momentum calculation by employing a weighted approach to momentum values. This method begins by initializing two variables to store the cumulative momentum values and their respective weights throughout the calculation process.
The calculation iterates through the range of the price data. For each iteration, a weight is calculated as the square root of the index plus one. The weight serves as a scaling factor, emphasizing more recent price changes over older ones. This allows the Polychromatic Momentum to account for the significance of recent trends in the market.
Next, the momentum value for the current index is calculated by finding the difference between the current source price and the source price at the previous index. This difference is then divided by the calculated weight. The momentum value is added to the cumulative sum, and the weight is added to the sum of weights.
Once the iteration is complete, the Polychromatic Momentum is obtained by dividing the cumulative sum of momentum values by the sum of weights. This calculation method provides a more nuanced understanding of the momentum by taking into account the varying importance of price changes over time.
Polychromatic Momentum offers a different approach to momentum calculation compared to regular momentum. While both methods aim to measure the strength of a trend by analyzing the rate of change in prices, their calculations differ in certain aspects, which may result in advantages for Polychromatic Momentum.
Regular momentum is calculated by subtracting the price value at a specific period in the past from the current price value. This method provides a simple and straightforward way to determine the price change over a fixed period.
Polychromatic Momentum, on the other hand, employs a weighted approach to momentum values. It calculates the momentum by considering a range of price changes over time and assigning weights to each change based on their recency. This approach aims to capture the varying importance of price changes over time, which can be beneficial in certain market conditions.
Some potential advantages of Polychromatic Momentum over regular momentum include:
1. Responsiveness: Polychromatic Momentum places greater emphasis on recent price changes, making it more responsive to new trends in the market. This responsiveness could provide timely signals for traders to capitalize on emerging trends.
2. Enhanced Trend Analysis: By considering a range of price changes over time and assigning weights to each change, Polychromatic Momentum can provide a more comprehensive analysis of the market trends. This can help traders better understand the overall momentum and make more informed decisions.
3. Flexibility: Polychromatic Momentum's weighted approach allows for greater flexibility in adapting to different market conditions and timeframes. Traders can experiment with different weighting schemes to optimize the momentum calculation for their specific trading strategies and goals.
In conclusion, Polychromatic Momentum offers a more refined approach to momentum calculation in technical analysis compared to traditional methods. By using a weighted approach, it effectively takes into account the varying importance of price changes over time, providing traders with a more insightful and responsive measure of market trends.
What is Double Smoothed Exponential Moving Average?
In financial markets and trading, technical analysis serves as a critical tool for evaluating price trends and making strategic decisions. A key component of technical analysis is the moving average, which averages price data over a specified period to smooth out fluctuations and identify market trends. While the Exponential Moving Average (EMA) is a popular moving average variant that emphasizes recent data points, the Double Smoothed Exponential Moving Average (DSEMA) takes it a step further by incorporating two layers of EMA calculations for more advanced smoothing. The following delve into the DSEMA methodology, explaining its working mechanism and the logic behind the technique without referring to specific code variables.
Double Smoothed Exponential Moving Average Explanation
DSEMA is a function that processes source price data and the length of the smoothing period as its inputs. Its primary objective is to minimize noise in the price data and generate a smoother output, which can be advantageous for detecting trends and making informed trading decisions.
The DSEMA calculation begins by determining the alpha value, which is the smoothing factor for the EMA. The alpha value is derived from the square root of the length of the smoothing period, ensuring that it falls between 0 and 1. A higher alpha value leads to a more responsive EMA, while a lower alpha value results in a slower-moving EMA that is less affected by recent price fluctuations.
The core of the DSEMA calculation involves applying two layers of EMA. The first layer calculates the initial EMA using the source price data and the alpha value. This first EMA places more weight on recent price data points, similar to a regular EMA.
The second layer calculates another EMA using the initial EMA values and the same alpha value. This second layer of EMA provides additional smoothing to the price data, resulting in a smoother output curve that is less prone to noise and sudden market changes. The final output of the DSEMA is the result of the second EMA layer.
In summary, the Double Smoothed Exponential Moving Average (DSEMA) offers an advanced approach to price data smoothing in technical analysis by applying two successive layers of EMA calculations. This technique enhances the detection of market trends and helps reduce the impact of noise in price data, providing traders with a more reliable representation of price movements to support their decision-making process.
Combining DSEMA and Polychromatic Momentum
DSEMA is an advanced smoothing technique that applies two layers of Exponential Moving Average (EMA) calculations to reduce noise in price data and produce a smoother representation of the market trends. On the other hand, Polychromatic Momentum is a momentum calculation method that employs a weighted approach to assess the strength of trends by analyzing the rate of change in prices over time.
By combining the two techniques, DSEMA can be used to smooth the source price data before inputting it into the Polychromatic Momentum calculation. This combination allows for a more accurate representation of price movements, as the smoothed price data provided by DSEMA minimizes the impact of sudden market fluctuations and noise on the momentum calculation.
The result is an enhanced technical analysis tool that leverages the benefits of advanced price smoothing from DSEMA and the refined trend assessment of Polychromatic Momentum. This integrated approach can help traders gain a deeper understanding of market dynamics and make more informed decisions based on reliable, noise-reduced price data and nuanced momentum calculations.
For our purposes here, only the source price can be smoothed and it's turned off by default. The smoothing period is zero by default. Any period above 0 and the smoothing will kick in. Try a period of 5.
Additional Features
This indicator allows you to select from 33 source types. They are as follows:
Close
Open
High
Low
Median
Typical
Weighted
Average
Average Median Body
Trend Biased
Trend Biased (Extreme)
HA Close
HA Open
HA High
HA Low
HA Median
HA Typical
HA Weighted
HA Average
HA Average Median Body
HA Trend Biased
HA Trend Biased (Extreme)
HAB Close
HAB Open
HAB High
HAB Low
HAB Median
HAB Typical
HAB Weighted
HAB Average
HAB Average Median Body
HAB Trend Biased
HAB Trend Biased (Extreme)
What are Heiken Ashi "better" candles?
Heiken Ashi "better" candles are a modified version of the standard Heiken Ashi candles, which are a popular charting technique used in technical analysis. Heiken Ashi candles help traders identify trends and potential reversal points by smoothing out price data and reducing market noise. The "better formula" was proposed by Sebastian Schmidt in an article published by BNP Paribas in Warrants & Zertifikate, a German magazine, in August 2004. The aim of this formula is to further improve the smoothing of the Heiken Ashi chart and enhance its effectiveness in identifying trends and reversals.
Standard Heiken Ashi candles are calculated using the following formulas:
Heiken Ashi Close = (Open + High + Low + Close) / 4
Heiken Ashi Open = (Previous Heiken Ashi Open + Previous Heiken Ashi Close) / 2
Heiken Ashi High = Max (High, Heiken Ashi Open, Heiken Ashi Close)
Heiken Ashi Low = Min (Low, Heiken Ashi Open, Heiken Ashi Close)
The "better formula" modifies the standard Heiken Ashi calculation by incorporating additional smoothing, which can help reduce noise and make it easier to identify trends and reversals. The modified formulas for Heiken Ashi "better" candles are as follows:
Better Heiken Ashi Close = (Open + High + Low + Close) / 4
Better Heiken Ashi Open = (Previous Better Heiken Ashi Open + Previous Better Heiken Ashi Close) / 2
Better Heiken Ashi High = Max (High, Better Heiken Ashi Open, Better Heiken Ashi Close)
Better Heiken Ashi Low = Min (Low, Better Heiken Ashi Open, Better Heiken Ashi Close)
Smoothing Factor = 2 / (N + 1), where N is the chosen period for smoothing
Smoothed Better Heiken Ashi Open = (Better Heiken Ashi Open * Smoothing Factor) + (Previous Smoothed Better Heiken Ashi Open * (1 - Smoothing Factor))
Smoothed Better Heiken Ashi Close = (Better Heiken Ashi Close * Smoothing Factor) + (Previous Smoothed Better Heiken Ashi Close * (1 - Smoothing Factor))
The smoothed Better Heiken Ashi Open and Close values are then used to calculate the smoothed Better Heiken Ashi High and Low values, resulting in "better" candles that provide a clearer representation of the market trend and potential reversal points.
It's important to note that, like any other technical analysis tool, Heiken Ashi "better" candles are not foolproof and should be used in conjunction with other indicators and analysis techniques to make well-informed trading decisions.
Heiken Ashi "better" candles, as mentioned previously, provide a clearer representation of market trends and potential reversal points by reducing noise and smoothing out price data. When using these candles in conjunction with other technical analysis tools and indicators, traders can gain valuable insights into market behavior and make more informed decisions.
To effectively use Heiken Ashi "better" candles in your trading strategy, consider the following tips:
Trend Identification: Heiken Ashi "better" candles can help you identify the prevailing trend in the market. When the majority of the candles are green (or another color, depending on your chart settings) and there are no or few lower wicks, it may indicate a strong uptrend. Conversely, when the majority of the candles are red (or another color) and there are no or few upper wicks, it may signal a strong downtrend.
Trend Reversals: Look for potential trend reversals when a change in the color of the candles occurs, especially when accompanied by longer wicks. For example, if a green candle with a long lower wick is followed by a red candle, it could indicate a bearish reversal. Similarly, a red candle with a long upper wick followed by a green candle may suggest a bullish reversal.
Support and Resistance: You can use Heiken Ashi "better" candles to identify potential support and resistance levels. When the candles are consistently moving in one direction and then suddenly change color with longer wicks, it could indicate the presence of a support or resistance level.
Stop-Loss and Take-Profit: Using Heiken Ashi "better" candles can help you manage risk by determining optimal stop-loss and take-profit levels. For instance, you can place your stop-loss below the low of the most recent green candle in an uptrend or above the high of the most recent red candle in a downtrend.
Confirming Signals: Heiken Ashi "better" candles should be used in conjunction with other technical indicators, such as moving averages, oscillators, or chart patterns, to confirm signals and improve the accuracy of your analysis.
In this implementation, you have the choice of AMA, KAMA, or T3 smoothing. These are as follows:
Kaufman Adaptive Moving Average (KAMA)
The Kaufman Adaptive Moving Average (KAMA) is a type of adaptive moving average used in technical analysis to smooth out price fluctuations and identify trends. The KAMA adjusts its smoothing factor based on the market's volatility, making it more responsive in volatile markets and smoother in calm markets. The KAMA is calculated using three different efficiency ratios that determine the appropriate smoothing factor for the current market conditions. These ratios are based on the noise level of the market, the speed at which the market is moving, and the length of the moving average. The KAMA is a popular choice among traders who prefer to use adaptive indicators to identify trends and potential reversals.
Adaptive Moving Average
The Adaptive Moving Average (AMA) is a type of moving average that adjusts its sensitivity to price movements based on market conditions. It uses a ratio between the current price and the highest and lowest prices over a certain lookback period to determine its level of smoothing. The AMA can help reduce lag and increase responsiveness to changes in trend direction, making it useful for traders who want to follow trends while avoiding false signals. The AMA is calculated by multiplying a smoothing constant with the difference between the current price and the previous AMA value, then adding the result to the previous AMA value.
T3
The T3 moving average is a type of technical indicator used in financial analysis to identify trends in price movements. It is similar to the Exponential Moving Average (EMA) and the Double Exponential Moving Average (DEMA), but uses a different smoothing algorithm.
The T3 moving average is calculated using a series of exponential moving averages that are designed to filter out noise and smooth the data. The resulting smoothed data is then weighted with a non-linear function to produce a final output that is more responsive to changes in trend direction.
The T3 moving average can be customized by adjusting the length of the moving average, as well as the weighting function used to smooth the data. It is commonly used in conjunction with other technical indicators as part of a larger trading strategy.
█ Giga Kaleidoscope Modularized Trading System
Core components of an NNFX algorithmic trading strategy
The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend
3. Confirmation 1 - a technical indicator used to identify trends
4. Confirmation 2 - a technical indicator used to identify trends
5. Continuation - a technical indicator used to identify trends
6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown
7. Exit - a technical indicator used to determine when a trend is exhausted
What is Volatility in the NNFX trading system?
In the NNFX (No Nonsense Forex) trading system, ATR (Average True Range) is typically used to measure the volatility of an asset. It is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. ATR is calculated by taking the average of the true range values over a specified period.
True range is calculated as the maximum of the following values:
-Current high minus the current low
-Absolute value of the current high minus the previous close
-Absolute value of the current low minus the previous close
ATR is a dynamic indicator that changes with changes in volatility. As volatility increases, the value of ATR increases, and as volatility decreases, the value of ATR decreases. By using ATR in NNFX system, traders can adjust their stop loss and take profit levels according to the volatility of the asset being traded. This helps to ensure that the trade is given enough room to move, while also minimizing potential losses.
Other types of volatility include True Range Double (TRD), Close-to-Close, and Garman-Klass
What is a Baseline indicator?
The baseline is essentially a moving average, and is used to determine the overall direction of the market.
The baseline in the NNFX system is used to filter out trades that are not in line with the long-term trend of the market. The baseline is plotted on the chart along with other indicators, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR).
Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards, only long trades are taken, and if the baseline is sloping downwards, only short trades are taken. This approach helps to ensure that trades are in line with the overall trend of the market, and reduces the risk of entering trades that are likely to fail.
By using a baseline in the NNFX system, traders can have a clear reference point for determining the overall trend of the market, and can make more informed trading decisions. The baseline helps to filter out noise and false signals, and ensures that trades are taken in the direction of the long-term trend.
What is a Confirmation indicator?
Confirmation indicators are technical indicators that are used to confirm the signals generated by primary indicators. Primary indicators are the core indicators used in the NNFX system, such as the Average True Range (ATR), the Moving Average (MA), and the Relative Strength Index (RSI).
The purpose of the confirmation indicators is to reduce false signals and improve the accuracy of the trading system. They are designed to confirm the signals generated by the primary indicators by providing additional information about the strength and direction of the trend.
Some examples of confirmation indicators that may be used in the NNFX system include the Bollinger Bands, the MACD (Moving Average Convergence Divergence), and the MACD Oscillator. These indicators can provide information about the volatility, momentum, and trend strength of the market, and can be used to confirm the signals generated by the primary indicators.
In the NNFX system, confirmation indicators are used in combination with primary indicators and other filters to create a trading system that is robust and reliable. By using multiple indicators to confirm trading signals, the system aims to reduce the risk of false signals and improve the overall profitability of the trades.
What is a Continuation indicator?
In the NNFX (No Nonsense Forex) trading system, a continuation indicator is a technical indicator that is used to confirm a current trend and predict that the trend is likely to continue in the same direction. A continuation indicator is typically used in conjunction with other indicators in the system, such as a baseline indicator, to provide a comprehensive trading strategy.
What is a Volatility/Volume indicator?
Volume indicators, such as the On Balance Volume (OBV), the Chaikin Money Flow (CMF), or the Volume Price Trend (VPT), are used to measure the amount of buying and selling activity in a market. They are based on the trading volume of the market, and can provide information about the strength of the trend. In the NNFX system, volume indicators are used to confirm trading signals generated by the Moving Average and the Relative Strength Index. Volatility indicators include Average Direction Index, Waddah Attar, and Volatility Ratio. In the NNFX trading system, volatility is a proxy for volume and vice versa.
By using volume indicators as confirmation tools, the NNFX trading system aims to reduce the risk of false signals and improve the overall profitability of trades. These indicators can provide additional information about the market that is not captured by the primary indicators, and can help traders to make more informed trading decisions. In addition, volume indicators can be used to identify potential changes in market trends and to confirm the strength of price movements.
What is an Exit indicator?
The exit indicator is used in conjunction with other indicators in the system, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR), to provide a comprehensive trading strategy.
The exit indicator in the NNFX system can be any technical indicator that is deemed effective at identifying optimal exit points. Examples of exit indicators that are commonly used include the Parabolic SAR, the Average Directional Index (ADX), and the Chandelier Exit.
The purpose of the exit indicator is to identify when a trend is likely to reverse or when the market conditions have changed, signaling the need to exit a trade. By using an exit indicator, traders can manage their risk and prevent significant losses.
In the NNFX system, the exit indicator is used in conjunction with a stop loss and a take profit order to maximize profits and minimize losses. The stop loss order is used to limit the amount of loss that can be incurred if the trade goes against the trader, while the take profit order is used to lock in profits when the trade is moving in the trader's favor.
Overall, the use of an exit indicator in the NNFX trading system is an important component of a comprehensive trading strategy. It allows traders to manage their risk effectively and improve the profitability of their trades by exiting at the right time.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v1.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data between modules. Data is passed between each module as described below:
GKD-B => GKD-V => GKD-C(1) => GKD-C(2) => GKD-C(Continuation) => GKD-E => GKD-BT
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Strategy with 1-3 take profits, trailing stop loss, multiple types of PnL volatility, and 2 backtesting styles
Baseline: Hull Moving Average
Volatility/Volume: Hurst Exponent
Confirmation 1: Polychromatic Momentum as shown on the chart above
Confirmation 2: Williams Percent Range
Continuation: Polychromatic Momentum
Exit: Rex Oscillator
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD protocol chain.
Giga Kaleidoscope Modularized Trading System Signals (based on the NNFX algorithm)
Standard Entry
1. GKD-C Confirmation 1 Signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
6. GKD-C Confirmation 1 signal was less than 7 candles prior
Volatility/Volume Entry
1. GKD-V Volatility/Volume signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-B Baseline agrees
6. GKD-C Confirmation 1 signal was less than 7 candles prior
Continuation Entry
1. Standard Entry, Baseline Entry, or Pullback; entry triggered previously
2. GKD-B Baseline hasn't crossed since entry signal trigger
3. GKD-C Confirmation Continuation Indicator signals
4. GKD-C Confirmation 1 agrees
5. GKD-B Baseline agrees
6. GKD-C Confirmation 2 agrees
1-Candle Rule Standard Entry
1. GKD-C Confirmation 1 signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
1-Candle Rule Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 1 signal was less than 7 candles prior
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume Agrees
1-Candle Rule Volatility/Volume Entry
1. GKD-V Volatility/Volume signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 1 signal was less than 7 candles prior
Next Candle:
1. Price retraced (Long: close < close or Short: close > close)
2. GKD-B Volatility/Volume agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-B Baseline agrees
PullBack Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is beyond 1.0x Volatility of Baseline
Next Candle:
1. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
2. GKD-C Confirmation 1 agrees
3. GKD-C Confirmation 2 agrees
4. GKD-V Volatility/Volume Agrees
]█ Setting up the GKD
The GKD system involves chaining indicators together. These are the steps to set this up.
Use a GKD-C indicator alone on a chart
1. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Simple"
Use a GKD-V indicator alone on a chart
**nothing, it's already useable on the chart without any settings changes
Use a GKD-B indicator alone on a chart
**nothing, it's already useable on the chart without any settings changes
Baseline (Baseline, Backtest)
1. Import the GKD-B Baseline into the GKD-BT Backtest: "Input into Volatility/Volume or Backtest (Baseline testing)"
2. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Baseline"
Volatility/Volume (Volatility/Volume, Backte st)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Solo"
2. Inside the GKD-V indicator, change the "Signal Type" setting to "Crossing" (neither traditional nor both can be backtested)
3. Import the GKD-V indicator into the GKD-BT Backtest: "Input into C1 or Backtest"
4. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Volatility/Volume"
5. Inside the GKD-BT Backtest, a) change the setting "Backtest Type" to "Trading" if using a directional GKD-V indicator; or, b) change the setting "Backtest Type" to "Full" if using a directional or non-directional GKD-V indicator (non-directional GKD-V can only test Longs and Shorts separately)
6. If "Backtest Type" is set to "Full": Inside the GKD-BT Backtest, change the setting "Backtest Side" to "Long" or "Short
7. If "Backtest Type" is set to "Full": To allow the system to open multiple orders at one time so you test all Longs or Shorts, open the GKD-BT Backtest, click the tab "Properties" and then insert a value of something like 10 orders into the "Pyramiding" settings. This will allow 10 orders to be opened at one time which should be enough to catch all possible Longs or Shorts.
Solo Confirmation Simple (Confirmation, Backtest)
1. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Simple"
1. Import the GKD-C indicator into the GKD-BT Backtest: "Input into Backtest"
2. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Solo Confirmation Simple"
Solo Confirmation Complex without Exits (Baseline, Volatility/Volume, Confirmation, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Complex"
4. Import the GKD-V indicator into the GKD-C indicator: "Input into C1 or Backtest"
5. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full wo/ Exits"
6. Import the GKD-C into the GKD-BT Backtest: "Input into Exit or Backtest"
Solo Confirmation Complex with Exits (Baseline, Volatility/Volume, Confirmation, Exit, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Complex"
4. Import the GKD-V indicator into the GKD-C indicator: "Input into C1 or Backtest"
5. Import the GKD-C indicator into the GKD-E indicator: "Input into Exit"
6. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full w/ Exits"
7. Import the GKD-E into the GKD-BT Backtest: "Input into Backtest"
Full GKD without Exits (Baseline, Volatility/Volume, Confirmation 1, Confirmation 2, Continuation, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C 1 indicator, change the "Confirmation Type" setting to "Confirmation 1"
4. Import the GKD-V indicator into the GKD-C 1 indicator: "Input into C1 or Backtest"
5. Inside the GKD-C 2 indicator, change the "Confirmation Type" setting to "Confirmation 2"
6. Import the GKD-C 1 indicator into the GKD-C 2 indicator: "Input into C2"
7. Inside the GKD-C Continuation indicator, change the "Confirmation Type" setting to "Continuation"
8. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full wo/ Exits"
9. Import the GKD-E into the GKD-BT Backtest: "Input into Exit or Backtest"
Full GKD with Exits (Baseline, Volatility/Volume, Confirmation 1, Confirmation 2, Continuation, Exit, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C 1 indicator, change the "Confirmation Type" setting to "Confirmation 1"
4. Import the GKD-V indicator into the GKD-C 1 indicator: "Input into C1 or Backtest"
5. Inside the GKD-C 2 indicator, change the "Confirmation Type" setting to "Confirmation 2"
6. Import the GKD-C 1 indicator into the GKD-C 2 indicator: "Input into C2"
7. Inside the GKD-C Continuation indicator, change the "Confirmation Type" setting to "Continuation"
8. Import the GKD-C Continuation indicator into the GKD-E indicator: "Input into Exit"
9. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full w/ Exits"
10. Import the GKD-E into the GKD-BT Backtest: "Input into Backtest"
Baseline + Volatility/Volume (Baseline, Volatility/Volume, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Baseline + Volatility/Volume"
2. Inside the GKD-V indicator, make sure the "Signal Type" setting is set to "Traditional"
3. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
4. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Baseline + Volatility/Volume"
5. Import the GKD-V into the GKD-BT Backtest: "Input into C1 or Backtest"
6. Inside the GKD-BT Backtest, change the setting "Backtest Type" to "Full". For this backtest, you must test Longs and Shorts separately
7. To allow the system to open multiple orders at one time so you can test all Longs or Shorts, open the GKD-BT Backtest, click the tab "Properties" and then insert a value of something like 10 orders into the "Pyramiding" settings. This will allow 10 orders to be opened at one time which should be enough to catch all possible Longs or Shorts.
Requirements
Inputs
Confirmation 1: GKD-V Volatility / Volume indicator
Confirmation 2: GKD-C Confirmation indicator
Continuation: GKD-C Confirmation indicator
Solo Confirmation Simple: GKD-B Baseline
Solo Confirmation Complex: GKD-V Volatility / Volume indicator
Solo Confirmation Super Complex: GKD-V Volatility / Volume indicator
Stacked 1: None
Stacked 2+: GKD-C, GKD-V, or GKD-B Stacked 1
Outputs
Confirmation 1: GKD-C Confirmation 2 indicator
Confirmation 2: GKD-C Continuation indicator
Continuation: GKD-E Exit indicator
Solo Confirmation Simple: GKD-BT Backtest
Solo Confirmation Complex: GKD-BT Backtest or GKD-E Exit indicator
Solo Confirmation Super Complex: GKD-C Continuation indicator
Stacked 1: GKD-C, GKD-V, or GKD-B Stacked 2+
Stacked 2+: GKD-C, GKD-V, or GKD-B Stacked 2+ or GKD-BT Backtest
Additional features will be added in future releases.
지수 이동 평균 (EMA)
GKD-C CCI Adaptive Smoother [Loxx]Giga Kaleidoscope GKD-C CCI Adaptive Smoother is a Confirmation module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
█ GKD-C CCI Adaptive Smoother
Commodity Channel Index: History, Calculation, and Advantages
The Commodity Channel Index (CCI) is a versatile technical analysis indicator widely used by traders and analysts to identify potential trends, reversals, and trading opportunities in various financial markets. Developed by Donald Lambert in 1980, the CCI was initially designed to analyze the cyclical behavior of commodities. However, its applications have expanded over time to include stocks, currencies, and other financial instruments. The following provides an overview of the CCI's history, explain its calculation, and discuss its advantages compared to other indicators.
History
Donald Lambert, a commodities trader and technical analyst, created the Commodity Channel Index in response to the unique challenges posed by the cyclical nature of the commodities markets. Lambert aimed to develop an indicator that could help traders identify potential turning points in the market, allowing them to capitalize on price trends and reversals. The CCI quickly gained popularity among traders and analysts due to its ability to adapt to various market conditions and provide valuable insights into price movements.
Calculation
The CCI is calculated through the following steps:
1. Determine the typical price for each period: The typical price is calculated as the average of the high, low, and closing prices for each period.
Typical Price = (High + Low + Close) / 3
2. Calculate the moving average of the typical price: The moving average is computed over a specified period, typically 14 or 20 days.
3. Calculate the mean deviation: For each period, subtract the moving average from the typical price, and take the absolute value of the result. Then, compute the average of these absolute values over the specified period.
4. Calculate the CCI: Divide the difference between the typical price and its moving average by the product of the mean deviation and a constant, typically 0.015.
CCI = (Typical Price - Moving Average) / (0.015 * Mean Deviation)
Why CCI is Used and Its Advantages over Other Indicators
The CCI offers several advantages over other technical indicators, making it a popular choice among traders and analysts:
1. Versatility: Although initially developed for commodities, the CCI has proven to be effective in analyzing a wide range of financial instruments, including stocks, currencies, and indices. Its adaptability to different markets and timeframes makes it a valuable tool for various trading strategies.
2. Identification of overbought and oversold conditions: The CCI measures the strength of the price movement relative to its historical average. When the CCI reaches extreme values, it can signal overbought or oversold conditions, indicating potential trend reversals or price corrections.
3. Confirmation of price trends: The CCI can help traders confirm the presence of a price trend by identifying periods of strong momentum. A rising CCI indicates increasing positive momentum, while a falling CCI suggests increasing negative momentum.
4. Divergence analysis: Traders can use the CCI to identify divergences between the indicator and price action. For example, if the price reaches a new high, but the CCI fails to reach a corresponding high, it can signal a weakening trend and potential reversal.
5. Independent of price scale: Unlike some other technical indicators, the CCI is not affected by the price scale of the asset being analyzed. This characteristic allows traders to apply the CCI consistently across various instruments and markets.
The Commodity Channel Index is a powerful and versatile technical analysis tool that has stood the test of time. Developed to address the unique challenges of the commodities markets, the CCI has evolved into an essential tool for traders and analysts in various financial markets. Its ability to identify trends, reversals, and trading opportunities, as well as its versatility and adaptability, sets it apart from other technical indicators. By incorporating the CCI into their analytical toolkit, traders can gain valuable insights into market conditions, enabling them to make more informed decisions and improve their overall trading performance.
As financial markets continue to evolve and grow more complex, the importance of reliable and versatile technical analysis tools like the CCI cannot be overstated. In an environment characterized by rapidly changing market conditions, the ability to quickly identify trends, reversals, and potential trading opportunities is crucial for success. The CCI's adaptability to different markets, timeframes, and instruments makes it an indispensable resource for traders seeking to navigate the increasingly dynamic financial landscape.
Additionally, the CCI can be effectively combined with other technical analysis tools, such as moving averages, trend lines, and candlestick patterns, to create a more comprehensive and robust trading strategy. By using the CCI in conjunction with these complementary techniques, traders can develop a more nuanced understanding of market behavior and enhance their ability to identify high-probability trading opportunities.
In conclusion, the Commodity Channel Index is a valuable and versatile tool in the world of technical analysis. Its ability to adapt to various market conditions and provide insights into price trends, reversals, and trading opportunities make it an essential resource for traders and analysts alike. As the financial markets continue to evolve, the CCI's proven track record and adaptability ensure that it will remain a cornerstone of technical analysis for years to come.
What is the Smoother Moving Average?
The smoother function is a custom algorithm designed to smooth the price data of a financial asset using a moving average technique. It takes the price (src) and the period of the rolling window sample (len) to reduce noise in the data and reveal underlying trends.
smoother(float src, int len)=>
wrk = src, wrk2 = src, wrk4 = src
wrk0 = 0., wrk1 = 0., wrk3 = 0.
alpha = 0.45 * (len - 1.0) / (0.45 * (len - 1.0) + 2.0)
wrk0 := src + alpha * (nz(wrk ) - src)
wrk1 := (src - wrk) * (1 - alpha) + alpha * nz(wrk1 )
wrk2 := wrk0 + wrk1
wrk3 := (wrk2 - nz(wrk4 )) * math.pow(1.0 - alpha, 2) + math.pow(alpha, 2) * nz(wrk3 )
wrk4 := wrk3 + nz(wrk4 )
wrk4
Here's a detailed breakdown of the code, explaining each step and its purpose:
1. wrk, wrk2, and wrk4: These variables are assigned the value of src, which represents the source price of the asset. This step initializes the variables with the current price data, serving as a starting point for the smoothing calculations.
wrk0, wrk1, and wrk3: These variables are initialized to 0. They will be used as temporary variables to hold intermediate results during the calculations.
Calculation of the alpha parameter:
2. The alpha parameter is calculated using the formula: 0.45 * (len - 1.0) / (0.45 * (len - 1.0) + 2.0). The purpose of this calculation is to determine the smoothing factor that will be used in the subsequent calculations. This factor will influence the balance between responsiveness to recent price changes and smoothness of the resulting moving average. A higher value of alpha will result in a more responsive moving average, while a lower value will produce a smoother curve.
Calculation of wrk0:
3. wrk0 is updated with the expression: src + alpha * (nz(wrk ) - src). This step calculates the first component of the moving average, which is based on the current price (src) and the previous value of wrk (if it exists, otherwise 0 is used). This calculation applies the alpha parameter to weight the contribution of the previous wrk value, effectively making the moving average more responsive to recent price changes.
Calculation of wrk1:
4. wrk1 is updated with the expression: (src - wrk) * (1 - alpha) + alpha * nz(wrk1 ). This step calculates the second component of the moving average, which is based on the difference between the current price (src) and the current value of wrk. The alpha parameter is used to weight the contribution of the previous wrk1 value, allowing the moving average to be even more responsive to recent price changes.
Calculation of wrk2:
5. wrk2 is updated with the expression: wrk0 + wrk1. This step combines the first and second components of the moving average (wrk0 and wrk1) to produce a preliminary smoothed value.
Calculation of wrk3:
6. wrk3 is updated with the expression: (wrk2 - nz(wrk4 )) * math.pow(1.0 - alpha, 2) + math.pow(alpha, 2) * nz(wrk3 ). This step refines the preliminary smoothed value (wrk2) by accounting for the differences between the current smoothed value and the previous smoothed values (wrk4 and wrk3 ). The alpha parameter is used to weight the contributions of the previous smoothed values, providing a balance between smoothness and responsiveness.
Calculation of wrk4:
7. Calculation of wrk4:
wrk4 is updated with the expression: wrk3 + nz(wrk4 ). This step combines the refined smoothed value (wrk3) with the previous smoothed value (wrk4 , or 0 if it doesn't exist) to produce the final smoothed value. The purpose of this step is to ensure that the resulting moving average incorporates information from past values, making it smoother and more representative of the underlying trend.
8. Return wrk4:
The function returns the final smoothed value wrk4. This value represents the Smoother Moving Average for the given data point in the price series.
In summary, the smoother function calculates a custom moving average by using a series of steps to weight and combine recent price data with past smoothed values. The resulting moving average is more responsive to recent price changes while still maintaining a smooth curve, which helps reveal underlying trends and reduce noise in the data. The alpha parameter plays a key role in balancing the responsiveness and smoothness of the moving average, allowing users to customize the behavior of the algorithm based on their specific needs and preferences.
What is the CCI Adaptive Smoother?
The Commodity Channel Index (CCI) Adaptive Smoother is an innovative technical analysis tool that combines the benefits of the CCI indicator with a Smoother Moving Average. By adapting the CCI calculation based on the current market volatility, this method offers a more responsive and flexible approach to identifying potential trends and trading signals in financial markets.
The CCI is a momentum-based oscillator designed to determine whether an asset is overbought or oversold. It measures the difference between the typical price of an asset and its moving average, divided by the mean absolute deviation of the typical price. The traditional CCI calculation relies on a fixed period, which may not be suitable for all market conditions, as volatility can change over time.
The introduction of the Smoother Moving Average to the CCI calculation addresses this limitation. The Smoother Moving Average is a custom smoothing algorithm that combines elements of exponential moving averages with additional calculations to fine-tune the smoothing effect based on a given parameter. This algorithm assigns more importance to recent data points, making it more sensitive to recent changes in the data.
The CCI Adaptive Smoother dynamically adjusts the period of the Smoother Moving Average based on the current market volatility. This is accomplished by calculating the standard deviation of the close prices over a specified period and then computing the simple moving average of the standard deviation. By comparing the average standard deviation with the current standard deviation, the adaptive period for the Smoother Moving Average can be determined.
This adaptive approach allows the CCI Adaptive Smoother to be more responsive to changing market conditions. In periods of high volatility, the adaptive period will be shorter, resulting in a more responsive moving average. Conversely, in periods of low volatility, the adaptive period will be longer, producing a smoother moving average. This flexibility enables the CCI Adaptive Smoother to better identify trends and potential trading signals in a variety of market environments.
Furthermore, the CCI Adaptive Smoother is a prime example of the evolution of technical analysis methodologies. As markets continue to become more complex and dynamic, it is crucial for analysts and traders to adapt and improve their techniques to stay competitive. The incorporation of adaptive algorithms, like the Smoother Moving Average, demonstrates the potential for blending traditional indicators with cutting-edge methods to create more powerful and versatile tools for market analysis.
The versatility of the CCI Adaptive Smoother makes it suitable for various trading strategies, including trend-following, mean-reversion, and breakout systems. By providing a more precise measurement of overbought and oversold conditions, the CCI Adaptive Smoother can help traders identify potential entry and exit points with greater accuracy. Additionally, its responsiveness to changing market conditions allows for more timely adjustments in trading positions, reducing the risk of holding onto losing trades.
While the CCI Adaptive Smoother is a valuable tool, it is essential to remember that no single indicator can provide a complete picture of the market. As seasoned analysts and traders, we must always consider a holistic approach, incorporating multiple indicators and techniques to confirm signals and validate our trading decisions. By combining the CCI Adaptive Smoother with other technical analysis tools, such as trend lines, support and resistance levels, and candlestick patterns, traders can develop a more comprehensive understanding of the market and make more informed decisions.
The development of the CCI Adaptive Smoother also highlights the increasing importance of computational power and advanced algorithms in the field of technical analysis. As financial markets become more interconnected and influenced by various factors, including macroeconomic events, geopolitical developments, and technological innovations, the need for sophisticated tools to analyze and interpret complex data sets becomes even more critical.
Machine learning and artificial intelligence (AI) are becoming increasingly relevant in the world of trading and investing. These technologies have the potential to revolutionize how technical analysis is performed, by automating the discovery of patterns, relationships, and trends in the data. By leveraging machine learning algorithms and AI-driven techniques, traders can uncover hidden insights, improve decision-making processes, and optimize trading strategies.
The CCI Adaptive Smoother is just one example of how advanced algorithms can enhance traditional technical indicators. As the adoption of machine learning and AI continues to grow in the financial sector, we can expect to see the emergence of even more sophisticated and powerful analysis tools. These innovations will undoubtedly lead to a new era of technical analysis, where the ability to quickly adapt to changing market conditions and extract meaningful insights from complex data becomes increasingly critical for success.
In conclusion, the CCI Adaptive Smoother is an essential step forward in the evolution of technical analysis. It demonstrates the potential for combining traditional indicators with advanced algorithms to create more responsive and versatile tools for market analysis. As technology continues to advance and reshape the financial landscape, it is crucial for traders and analysts to stay informed and embrace innovation. By integrating cutting-edge tools like the CCI Adaptive Smoother into their arsenal, traders can gain a competitive edge and enhance their ability to navigate the increasingly complex world of financial markets.
Additional Features
This indicator allows you to select from 33 source types. They are as follows:
Close
Open
High
Low
Median
Typical
Weighted
Average
Average Median Body
Trend Biased
Trend Biased (Extreme)
HA Close
HA Open
HA High
HA Low
HA Median
HA Typical
HA Weighted
HA Average
HA Average Median Body
HA Trend Biased
HA Trend Biased (Extreme)
HAB Close
HAB Open
HAB High
HAB Low
HAB Median
HAB Typical
HAB Weighted
HAB Average
HAB Average Median Body
HAB Trend Biased
HAB Trend Biased (Extreme)
What are Heiken Ashi "better" candles?
Heiken Ashi "better" candles are a modified version of the standard Heiken Ashi candles, which are a popular charting technique used in technical analysis. Heiken Ashi candles help traders identify trends and potential reversal points by smoothing out price data and reducing market noise. The "better formula" was proposed by Sebastian Schmidt in an article published by BNP Paribas in Warrants & Zertifikate, a German magazine, in August 2004. The aim of this formula is to further improve the smoothing of the Heiken Ashi chart and enhance its effectiveness in identifying trends and reversals.
Standard Heiken Ashi candles are calculated using the following formulas:
Heiken Ashi Close = (Open + High + Low + Close) / 4
Heiken Ashi Open = (Previous Heiken Ashi Open + Previous Heiken Ashi Close) / 2
Heiken Ashi High = Max (High, Heiken Ashi Open, Heiken Ashi Close)
Heiken Ashi Low = Min (Low, Heiken Ashi Open, Heiken Ashi Close)
The "better formula" modifies the standard Heiken Ashi calculation by incorporating additional smoothing, which can help reduce noise and make it easier to identify trends and reversals. The modified formulas for Heiken Ashi "better" candles are as follows:
Better Heiken Ashi Close = (Open + High + Low + Close) / 4
Better Heiken Ashi Open = (Previous Better Heiken Ashi Open + Previous Better Heiken Ashi Close) / 2
Better Heiken Ashi High = Max (High, Better Heiken Ashi Open, Better Heiken Ashi Close)
Better Heiken Ashi Low = Min (Low, Better Heiken Ashi Open, Better Heiken Ashi Close)
Smoothing Factor = 2 / (N + 1), where N is the chosen period for smoothing
Smoothed Better Heiken Ashi Open = (Better Heiken Ashi Open * Smoothing Factor) + (Previous Smoothed Better Heiken Ashi Open * (1 - Smoothing Factor))
Smoothed Better Heiken Ashi Close = (Better Heiken Ashi Close * Smoothing Factor) + (Previous Smoothed Better Heiken Ashi Close * (1 - Smoothing Factor))
The smoothed Better Heiken Ashi Open and Close values are then used to calculate the smoothed Better Heiken Ashi High and Low values, resulting in "better" candles that provide a clearer representation of the market trend and potential reversal points.
It's important to note that, like any other technical analysis tool, Heiken Ashi "better" candles are not foolproof and should be used in conjunction with other indicators and analysis techniques to make well-informed trading decisions.
Heiken Ashi "better" candles, as mentioned previously, provide a clearer representation of market trends and potential reversal points by reducing noise and smoothing out price data. When using these candles in conjunction with other technical analysis tools and indicators, traders can gain valuable insights into market behavior and make more informed decisions.
To effectively use Heiken Ashi "better" candles in your trading strategy, consider the following tips:
Trend Identification: Heiken Ashi "better" candles can help you identify the prevailing trend in the market. When the majority of the candles are green (or another color, depending on your chart settings) and there are no or few lower wicks, it may indicate a strong uptrend. Conversely, when the majority of the candles are red (or another color) and there are no or few upper wicks, it may signal a strong downtrend.
Trend Reversals: Look for potential trend reversals when a change in the color of the candles occurs, especially when accompanied by longer wicks. For example, if a green candle with a long lower wick is followed by a red candle, it could indicate a bearish reversal. Similarly, a red candle with a long upper wick followed by a green candle may suggest a bullish reversal.
Support and Resistance: You can use Heiken Ashi "better" candles to identify potential support and resistance levels. When the candles are consistently moving in one direction and then suddenly change color with longer wicks, it could indicate the presence of a support or resistance level.
Stop-Loss and Take-Profit: Using Heiken Ashi "better" candles can help you manage risk by determining optimal stop-loss and take-profit levels. For instance, you can place your stop-loss below the low of the most recent green candle in an uptrend or above the high of the most recent red candle in a downtrend.
Confirming Signals: Heiken Ashi "better" candles should be used in conjunction with other technical indicators, such as moving averages, oscillators, or chart patterns, to confirm signals and improve the accuracy of your analysis.
In this implementation, you have the choice of AMA, KAMA, or T3 smoothing. These are as follows:
Kaufman Adaptive Moving Average (KAMA)
The Kaufman Adaptive Moving Average (KAMA) is a type of adaptive moving average used in technical analysis to smooth out price fluctuations and identify trends. The KAMA adjusts its smoothing factor based on the market's volatility, making it more responsive in volatile markets and smoother in calm markets. The KAMA is calculated using three different efficiency ratios that determine the appropriate smoothing factor for the current market conditions. These ratios are based on the noise level of the market, the speed at which the market is moving, and the length of the moving average. The KAMA is a popular choice among traders who prefer to use adaptive indicators to identify trends and potential reversals.
Adaptive Moving Average
The Adaptive Moving Average (AMA) is a type of moving average that adjusts its sensitivity to price movements based on market conditions. It uses a ratio between the current price and the highest and lowest prices over a certain lookback period to determine its level of smoothing. The AMA can help reduce lag and increase responsiveness to changes in trend direction, making it useful for traders who want to follow trends while avoiding false signals. The AMA is calculated by multiplying a smoothing constant with the difference between the current price and the previous AMA value, then adding the result to the previous AMA value.
T3
The T3 moving average is a type of technical indicator used in financial analysis to identify trends in price movements. It is similar to the Exponential Moving Average (EMA) and the Double Exponential Moving Average (DEMA), but uses a different smoothing algorithm.
The T3 moving average is calculated using a series of exponential moving averages that are designed to filter out noise and smooth the data. The resulting smoothed data is then weighted with a non-linear function to produce a final output that is more responsive to changes in trend direction.
The T3 moving average can be customized by adjusting the length of the moving average, as well as the weighting function used to smooth the data. It is commonly used in conjunction with other technical indicators as part of a larger trading strategy.
█ Giga Kaleidoscope Modularized Trading System
Core components of an NNFX algorithmic trading strategy
The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend
3. Confirmation 1 - a technical indicator used to identify trends
4. Confirmation 2 - a technical indicator used to identify trends
5. Continuation - a technical indicator used to identify trends
6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown
7. Exit - a technical indicator used to determine when a trend is exhausted
What is Volatility in the NNFX trading system?
In the NNFX (No Nonsense Forex) trading system, ATR (Average True Range) is typically used to measure the volatility of an asset. It is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. ATR is calculated by taking the average of the true range values over a specified period.
True range is calculated as the maximum of the following values:
-Current high minus the current low
-Absolute value of the current high minus the previous close
-Absolute value of the current low minus the previous close
ATR is a dynamic indicator that changes with changes in volatility. As volatility increases, the value of ATR increases, and as volatility decreases, the value of ATR decreases. By using ATR in NNFX system, traders can adjust their stop loss and take profit levels according to the volatility of the asset being traded. This helps to ensure that the trade is given enough room to move, while also minimizing potential losses.
Other types of volatility include True Range Double (TRD), Close-to-Close, and Garman-Klass
What is a Baseline indicator?
The baseline is essentially a moving average, and is used to determine the overall direction of the market.
The baseline in the NNFX system is used to filter out trades that are not in line with the long-term trend of the market. The baseline is plotted on the chart along with other indicators, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR).
Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards, only long trades are taken, and if the baseline is sloping downwards, only short trades are taken. This approach helps to ensure that trades are in line with the overall trend of the market, and reduces the risk of entering trades that are likely to fail.
By using a baseline in the NNFX system, traders can have a clear reference point for determining the overall trend of the market, and can make more informed trading decisions. The baseline helps to filter out noise and false signals, and ensures that trades are taken in the direction of the long-term trend.
What is a Confirmation indicator?
Confirmation indicators are technical indicators that are used to confirm the signals generated by primary indicators. Primary indicators are the core indicators used in the NNFX system, such as the Average True Range (ATR), the Moving Average (MA), and the Relative Strength Index (RSI).
The purpose of the confirmation indicators is to reduce false signals and improve the accuracy of the trading system. They are designed to confirm the signals generated by the primary indicators by providing additional information about the strength and direction of the trend.
Some examples of confirmation indicators that may be used in the NNFX system include the Bollinger Bands, the MACD (Moving Average Convergence Divergence), and the MACD Oscillator. These indicators can provide information about the volatility, momentum, and trend strength of the market, and can be used to confirm the signals generated by the primary indicators.
In the NNFX system, confirmation indicators are used in combination with primary indicators and other filters to create a trading system that is robust and reliable. By using multiple indicators to confirm trading signals, the system aims to reduce the risk of false signals and improve the overall profitability of the trades.
What is a Continuation indicator?
In the NNFX (No Nonsense Forex) trading system, a continuation indicator is a technical indicator that is used to confirm a current trend and predict that the trend is likely to continue in the same direction. A continuation indicator is typically used in conjunction with other indicators in the system, such as a baseline indicator, to provide a comprehensive trading strategy.
What is a Volatility/Volume indicator?
Volume indicators, such as the On Balance Volume (OBV), the Chaikin Money Flow (CMF), or the Volume Price Trend (VPT), are used to measure the amount of buying and selling activity in a market. They are based on the trading volume of the market, and can provide information about the strength of the trend. In the NNFX system, volume indicators are used to confirm trading signals generated by the Moving Average and the Relative Strength Index. Volatility indicators include Average Direction Index, Waddah Attar, and Volatility Ratio. In the NNFX trading system, volatility is a proxy for volume and vice versa.
By using volume indicators as confirmation tools, the NNFX trading system aims to reduce the risk of false signals and improve the overall profitability of trades. These indicators can provide additional information about the market that is not captured by the primary indicators, and can help traders to make more informed trading decisions. In addition, volume indicators can be used to identify potential changes in market trends and to confirm the strength of price movements.
What is an Exit indicator?
The exit indicator is used in conjunction with other indicators in the system, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR), to provide a comprehensive trading strategy.
The exit indicator in the NNFX system can be any technical indicator that is deemed effective at identifying optimal exit points. Examples of exit indicators that are commonly used include the Parabolic SAR, the Average Directional Index (ADX), and the Chandelier Exit.
The purpose of the exit indicator is to identify when a trend is likely to reverse or when the market conditions have changed, signaling the need to exit a trade. By using an exit indicator, traders can manage their risk and prevent significant losses.
In the NNFX system, the exit indicator is used in conjunction with a stop loss and a take profit order to maximize profits and minimize losses. The stop loss order is used to limit the amount of loss that can be incurred if the trade goes against the trader, while the take profit order is used to lock in profits when the trade is moving in the trader's favor.
Overall, the use of an exit indicator in the NNFX trading system is an important component of a comprehensive trading strategy. It allows traders to manage their risk effectively and improve the profitability of their trades by exiting at the right time.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v1.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data between modules. Data is passed between each module as described below:
GKD-B => GKD-V => GKD-C(1) => GKD-C(2) => GKD-C(Continuation) => GKD-E => GKD-BT
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Strategy with 1-3 take profits, trailing stop loss, multiple types of PnL volatility, and 2 backtesting styles
Baseline: Hull Moving Average
Volatility/Volume: Hurst Exponent
Confirmation 1: CCI Adaptive Smoother as shown on the chart above
Confirmation 2: Williams Percent Range
Continuation: CCI Adaptive Smoother
Exit: Rex Oscillator
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD protocol chain.
Giga Kaleidoscope Modularized Trading System Signals (based on the NNFX algorithm)
Standard Entry
1. GKD-C Confirmation 1 Signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
6. GKD-C Confirmation 1 signal was less than 7 candles prior
Volatility/Volume Entry
1. GKD-V Volatility/Volume signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-B Baseline agrees
6. GKD-C Confirmation 1 signal was less than 7 candles prior
Continuation Entry
1. Standard Entry, Baseline Entry, or Pullback; entry triggered previously
2. GKD-B Baseline hasn't crossed since entry signal trigger
3. GKD-C Confirmation Continuation Indicator signals
4. GKD-C Confirmation 1 agrees
5. GKD-B Baseline agrees
6. GKD-C Confirmation 2 agrees
1-Candle Rule Standard Entry
1. GKD-C Confirmation 1 signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
1-Candle Rule Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 1 signal was less than 7 candles prior
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume Agrees
1-Candle Rule Volatility/Volume Entry
1. GKD-V Volatility/Volume signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 1 signal was less than 7 candles prior
Next Candle:
1. Price retraced (Long: close < close or Short: close > close)
2. GKD-B Volatility/Volume agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-B Baseline agrees
PullBack Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is beyond 1.0x Volatility of Baseline
Next Candle:
1. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
2. GKD-C Confirmation 1 agrees
3. GKD-C Confirmation 2 agrees
4. GKD-V Volatility/Volume Agrees
]█ Setting up the GKD
The GKD system involves chaining indicators together. These are the steps to set this up.
Use a GKD-C indicator alone on a chart
1. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Simple"
Use a GKD-V indicator alone on a chart
**nothing, it's already useable on the chart without any settings changes
Use a GKD-B indicator alone on a chart
**nothing, it's already useable on the chart without any settings changes
Baseline (Baseline, Backtest)
1. Import the GKD-B Baseline into the GKD-BT Backtest: "Input into Volatility/Volume or Backtest (Baseline testing)"
2. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Baseline"
Volatility/Volume (Volatility/Volume, Backte st)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Solo"
2. Inside the GKD-V indicator, change the "Signal Type" setting to "Crossing" (neither traditional nor both can be backtested)
3. Import the GKD-V indicator into the GKD-BT Backtest: "Input into C1 or Backtest"
4. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Volatility/Volume"
5. Inside the GKD-BT Backtest, a) change the setting "Backtest Type" to "Trading" if using a directional GKD-V indicator; or, b) change the setting "Backtest Type" to "Full" if using a directional or non-directional GKD-V indicator (non-directional GKD-V can only test Longs and Shorts separately)
6. If "Backtest Type" is set to "Full": Inside the GKD-BT Backtest, change the setting "Backtest Side" to "Long" or "Short
7. If "Backtest Type" is set to "Full": To allow the system to open multiple orders at one time so you test all Longs or Shorts, open the GKD-BT Backtest, click the tab "Properties" and then insert a value of something like 10 orders into the "Pyramiding" settings. This will allow 10 orders to be opened at one time which should be enough to catch all possible Longs or Shorts.
Solo Confirmation Simple (Confirmation, Backtest)
1. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Simple"
1. Import the GKD-C indicator into the GKD-BT Backtest: "Input into Backtest"
2. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Solo Confirmation Simple"
Solo Confirmation Complex without Exits (Baseline, Volatility/Volume, Confirmation, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Complex"
4. Import the GKD-V indicator into the GKD-C indicator: "Input into C1 or Backtest"
5. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full wo/ Exits"
6. Import the GKD-C into the GKD-BT Backtest: "Input into Exit or Backtest"
Solo Confirmation Complex with Exits (Baseline, Volatility/Volume, Confirmation, Exit, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Complex"
4. Import the GKD-V indicator into the GKD-C indicator: "Input into C1 or Backtest"
5. Import the GKD-C indicator into the GKD-E indicator: "Input into Exit"
6. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full w/ Exits"
7. Import the GKD-E into the GKD-BT Backtest: "Input into Backtest"
Full GKD without Exits (Baseline, Volatility/Volume, Confirmation 1, Confirmation 2, Continuation, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C 1 indicator, change the "Confirmation Type" setting to "Confirmation 1"
4. Import the GKD-V indicator into the GKD-C 1 indicator: "Input into C1 or Backtest"
5. Inside the GKD-C 2 indicator, change the "Confirmation Type" setting to "Confirmation 2"
6. Import the GKD-C 1 indicator into the GKD-C 2 indicator: "Input into C2"
7. Inside the GKD-C Continuation indicator, change the "Confirmation Type" setting to "Continuation"
8. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full wo/ Exits"
9. Import the GKD-E into the GKD-BT Backtest: "Input into Exit or Backtest"
Full GKD with Exits (Baseline, Volatility/Volume, Confirmation 1, Confirmation 2, Continuation, Exit, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C 1 indicator, change the "Confirmation Type" setting to "Confirmation 1"
4. Import the GKD-V indicator into the GKD-C 1 indicator: "Input into C1 or Backtest"
5. Inside the GKD-C 2 indicator, change the "Confirmation Type" setting to "Confirmation 2"
6. Import the GKD-C 1 indicator into the GKD-C 2 indicator: "Input into C2"
7. Inside the GKD-C Continuation indicator, change the "Confirmation Type" setting to "Continuation"
8. Import the GKD-C Continuation indicator into the GKD-E indicator: "Input into Exit"
9. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full w/ Exits"
10. Import the GKD-E into the GKD-BT Backtest: "Input into Backtest"
Baseline + Volatility/Volume (Baseline, Volatility/Volume, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Baseline + Volatility/Volume"
2. Inside the GKD-V indicator, make sure the "Signal Type" setting is set to "Traditional"
3. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
4. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Baseline + Volatility/Volume"
5. Import the GKD-V into the GKD-BT Backtest: "Input into C1 or Backtest"
6. Inside the GKD-BT Backtest, change the setting "Backtest Type" to "Full". For this backtest, you must test Longs and Shorts separately
7. To allow the system to open multiple orders at one time so you can test all Longs or Shorts, open the GKD-BT Backtest, click the tab "Properties" and then insert a value of something like 10 orders into the "Pyramiding" settings. This will allow 10 orders to be opened at one time which should be enough to catch all possible Longs or Shorts.
Requirements
Inputs
Confirmation 1: GKD-V Volatility / Volume indicator
Confirmation 2: GKD-C Confirmation indicator
Continuation: GKD-C Confirmation indicator
Solo Confirmation Simple: GKD-B Baseline
Solo Confirmation Complex: GKD-V Volatility / Volume indicator
Solo Confirmation Super Complex: GKD-V Volatility / Volume indicator
Stacked 1: None
Stacked 2+: GKD-C, GKD-V, or GKD-B Stacked 1
Outputs
Confirmation 1: GKD-C Confirmation 2 indicator
Confirmation 2: GKD-C Continuation indicator
Continuation: GKD-E Exit indicator
Solo Confirmation Simple: GKD-BT Backtest
Solo Confirmation Complex: GKD-BT Backtest or GKD-E Exit indicator
Solo Confirmation Super Complex: GKD-C Continuation indicator
Stacked 1: GKD-C, GKD-V, or GKD-B Stacked 2+
Stacked 2+: GKD-C, GKD-V, or GKD-B Stacked 2+ or GKD-BT Backtest
Additional features will be added in future releases.
Seer's HutThis is a strategy based on Exponential Moving Averages or Volume Weighted Moving Averages against Adaptive fib resistance / support level and profit percentage which can be definetly defined by user and targeting small profits(profits will be raised by leverages).
In this strategy, there are predefined values which are collected one by one with statistical background and backtests. This gives an advantage to see which ratios are working better for each symbol. Also this statistics are re-evaluated monthly and if there is a need they are going to be changed with the help of libraries. Also IT IS RECOMMENDED TO USE IN DAILY INTERVAL GRAPHICS!!!!
When we deep dive to strategy, it is based on profit percentages. it is similar to the MOST system. MOST only changes the way with default value of %2. But this hardcoded strategy is not working well with each Symbol.
So this is the point where DC and ADR Statistics are involved.
For Ex. while BTC is suits well with %2, it does not do wonders for RSR or RUNE which is 4-5% for each.
There is 3 options for setting the statistical usage of this indicator.
1. Auto calculated based on 1000 days of ADR and DC
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2. Using Library where statistical values are stored.
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3. User-defined values used. Yeah you read it right. Fully on-demand changes are supported. Which gives freedom to users for setup their own Adaptive FIB and Profit Percentages.
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Based on this 3 options, TP and SL points are calculated on bar closures. Strategy Orders are also shown / raised with the closures.
Ok, system calculates these values but how to read / use them. what is this strategy based on ?
This strategy is mostly looking for minimizing the LOSS in case of any stop. So because of this, in each TP, system gives order signal to close half of the remaining open position.
There are 7 type of orders
OL : Open Long (Close Short and Open Long if in position)
CL 50 : Close Long - %50 of Open Position
CL 100 : Close Long - Close all position
OS : Open Short (Close Long and Open Short if in position)
CL 50 : Close Short - %50 of Open Position
CL 100 : Close Short - Close all position
TP5 : Highest TP reached. Close all position.
Script checks cross of EMA / VWMA and adFib to decide open a position. In reversal / crosses, adFib line had been set to defined Fib. Percentage (FP) level.
For creating the TP points, Profit Percentage (PP) parameter had been used which I briefly introduce at the beginning with the options.
One important topic about this strategy, it is not stacking / pyramiding the positions. Which means, it always calculate one way position. For example we are in the long position after OL signal.
We reached TP values and take profits. Later on due to FP crossing EMA, OS order signal given. This means you have to close all long position and open short position.
But beware. These calculated points are based on given values or calculated regarding to average ADR / DC ratings. For supporting strategy, several methods also had been included in the options.
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These are:
1. MA plotting (Optional 4 EMA, 1WMA) - checking for Golden and Death Cross
2. Bollinger Bands (Length 25 and Multiplier 2.5 set as default. Used in correlation with TEMA)
3. Kama 2 / Kama 5 - Crossing speaks of Trend way
4. TEMA (TEMA 50, VWMA 25 calculations and plotting. Used for TEMA 50 / VWMA 25 / SMA 25 cross checks for weakening or strengthening trend analysis)
5. ATR plotting
6. Chandelier Exit plotting (Widely used for calculating Stop levels in market)
7. PSAR (Widely used for indicating trend reversal)
Also for the ease of use, if the users does not want to plot any values on the graph and just want to see the values there is couple of tables also included.
1. EMA info
2. KAMA info
3. Order info
4. TP/SL info
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Some important notes:
1. To minimize the stop just after the order opening candle in volatile grounds, system prevents to raise new order signals if there is a signal already raised in last 4 candle.
2. if system reach and give close order in one of the TP points (For Ex TP1.), then index goes down and goes up again same TP (above TP1 in scenario) after 4 candle, system gives a close order signal again in the same TP.
3. There is a Profit Factor value had been shown at Order Info table. This information shows how profitable is the setup regarding to given FP and PP values.
In general market conditions, A Profit Factor above 1.50 is considered good enough and above 2.0 it is considered ideal. A strategy with profit factor less than 1.20 suggests too bigger a risk taken for making money.
In some cases automatic ADR and DC calculations are not good enough. so if you want to find a good Profit Factor value, you can change the system automatic calculation to manual value entering and you can see the results directly with in this field.
GKD-C RSI-Adaptive, STD-Filtered EMA [Loxx]Giga Kaleidoscope GKD-C RSI-Adaptive, STD-Filtered EMA is a Confirmation module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
█ Giga Kaleidoscope Modularized Trading System
What is Loxx's "Giga Kaleidoscope Modularized Trading System"?
The Giga Kaleidoscope Modularized Trading System is a trading system built on the philosophy of the NNFX (No Nonsense Forex) algorithmic trading.
What is the NNFX algorithmic trading strategy?
The NNFX (No-Nonsense Forex) trading system is a comprehensive approach to Forex trading that is designed to simplify the process and remove the confusion and complexity that often surrounds trading. The system was developed by a Forex trader who goes by the pseudonym "VP" and has gained a significant following in the Forex community.
The NNFX trading system is based on a set of rules and guidelines that help traders make objective and informed decisions. These rules cover all aspects of trading, including market analysis, trade entry, stop loss placement, and trade management.
Here are the main components of the NNFX trading system:
1. Trading Philosophy: The NNFX trading system is based on the idea that successful trading requires a comprehensive understanding of the market, objective analysis, and strict risk management. The system aims to remove subjective elements from trading and focuses on objective rules and guidelines.
2. Technical Analysis: The NNFX trading system relies heavily on technical analysis and uses a range of indicators to identify high-probability trading opportunities. The system uses a combination of trend-following and mean-reverting strategies to identify trades.
3. Market Structure: The NNFX trading system emphasizes the importance of understanding the market structure, including price action, support and resistance levels, and market cycles. The system uses a range of tools to identify the market structure, including trend lines, channels, and moving averages.
4. Trade Entry: The NNFX trading system has strict rules for trade entry. The system uses a combination of technical indicators to identify high-probability trades, and traders must meet specific criteria to enter a trade.
5. Stop Loss Placement: The NNFX trading system places a significant emphasis on risk management and requires traders to place a stop loss order on every trade. The system uses a combination of technical analysis and market structure to determine the appropriate stop loss level.
6. Trade Management: The NNFX trading system has specific rules for managing open trades. The system aims to minimize risk and maximize profit by using a combination of trailing stops, take profit levels, and position sizing.
Overall, the NNFX trading system is designed to be a straightforward and easy-to-follow approach to Forex trading that can be applied by traders of all skill levels.
Core components of an NNFX algorithmic trading strategy
The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend
3. Confirmation 1 - a technical indicator used to identify trends
4. Confirmation 2 - a technical indicator used to identify trends
5. Continuation - a technical indicator used to identify trends
6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown
7. Exit - a technical indicator used to determine when a trend is exhausted
What is Volatility in the NNFX trading system?
In the NNFX (No Nonsense Forex) trading system, ATR (Average True Range) is typically used to measure the volatility of an asset. It is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. ATR is calculated by taking the average of the true range values over a specified period.
True range is calculated as the maximum of the following values:
-Current high minus the current low
-Absolute value of the current high minus the previous close
-Absolute value of the current low minus the previous close
ATR is a dynamic indicator that changes with changes in volatility. As volatility increases, the value of ATR increases, and as volatility decreases, the value of ATR decreases. By using ATR in NNFX system, traders can adjust their stop loss and take profit levels according to the volatility of the asset being traded. This helps to ensure that the trade is given enough room to move, while also minimizing potential losses.
Other types of volatility include True Range Double (TRD), Close-to-Close, and Garman-Klass
What is a Baseline indicator?
The baseline is essentially a moving average, and is used to determine the overall direction of the market.
The baseline in the NNFX system is used to filter out trades that are not in line with the long-term trend of the market. The baseline is plotted on the chart along with other indicators, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR).
Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards, only long trades are taken, and if the baseline is sloping downwards, only short trades are taken. This approach helps to ensure that trades are in line with the overall trend of the market, and reduces the risk of entering trades that are likely to fail.
By using a baseline in the NNFX system, traders can have a clear reference point for determining the overall trend of the market, and can make more informed trading decisions. The baseline helps to filter out noise and false signals, and ensures that trades are taken in the direction of the long-term trend.
What is a Confirmation indicator?
Confirmation indicators are technical indicators that are used to confirm the signals generated by primary indicators. Primary indicators are the core indicators used in the NNFX system, such as the Average True Range (ATR), the Moving Average (MA), and the Relative Strength Index (RSI).
The purpose of the confirmation indicators is to reduce false signals and improve the accuracy of the trading system. They are designed to confirm the signals generated by the primary indicators by providing additional information about the strength and direction of the trend.
Some examples of confirmation indicators that may be used in the NNFX system include the Bollinger Bands, the MACD (Moving Average Convergence Divergence), and the MACD Oscillator. These indicators can provide information about the volatility, momentum, and trend strength of the market, and can be used to confirm the signals generated by the primary indicators.
In the NNFX system, confirmation indicators are used in combination with primary indicators and other filters to create a trading system that is robust and reliable. By using multiple indicators to confirm trading signals, the system aims to reduce the risk of false signals and improve the overall profitability of the trades.
What is a Continuation indicator?
In the NNFX (No Nonsense Forex) trading system, a continuation indicator is a technical indicator that is used to confirm a current trend and predict that the trend is likely to continue in the same direction. A continuation indicator is typically used in conjunction with other indicators in the system, such as a baseline indicator, to provide a comprehensive trading strategy.
What is a Volatility/Volume indicator?
Volume indicators, such as the On Balance Volume (OBV), the Chaikin Money Flow (CMF), or the Volume Price Trend (VPT), are used to measure the amount of buying and selling activity in a market. They are based on the trading volume of the market, and can provide information about the strength of the trend. In the NNFX system, volume indicators are used to confirm trading signals generated by the Moving Average and the Relative Strength Index. Volatility indicators include Average Direction Index, Waddah Attar, and Volatility Ratio. In the NNFX trading system, volatility is a proxy for volume and vice versa.
By using volume indicators as confirmation tools, the NNFX trading system aims to reduce the risk of false signals and improve the overall profitability of trades. These indicators can provide additional information about the market that is not captured by the primary indicators, and can help traders to make more informed trading decisions. In addition, volume indicators can be used to identify potential changes in market trends and to confirm the strength of price movements.
What is an Exit indicator?
The exit indicator is used in conjunction with other indicators in the system, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR), to provide a comprehensive trading strategy.
The exit indicator in the NNFX system can be any technical indicator that is deemed effective at identifying optimal exit points. Examples of exit indicators that are commonly used include the Parabolic SAR, the Average Directional Index (ADX), and the Chandelier Exit.
The purpose of the exit indicator is to identify when a trend is likely to reverse or when the market conditions have changed, signaling the need to exit a trade. By using an exit indicator, traders can manage their risk and prevent significant losses.
In the NNFX system, the exit indicator is used in conjunction with a stop loss and a take profit order to maximize profits and minimize losses. The stop loss order is used to limit the amount of loss that can be incurred if the trade goes against the trader, while the take profit order is used to lock in profits when the trade is moving in the trader's favor.
Overall, the use of an exit indicator in the NNFX trading system is an important component of a comprehensive trading strategy. It allows traders to manage their risk effectively and improve the profitability of their trades by exiting at the right time.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v1.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data between modules. Data is passed between each module as described below:
GKD-B => GKD-V => GKD-C(1) => GKD-C(2) => GKD-C(Continuation) => GKD-E => GKD-BT
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Strategy with 1-3 take profits, trailing stop loss, multiple types of PnL volatility, and 2 backtesting styles
Baseline: Hull Moving Average
Volatility/Volume: Hurst Exponent
Confirmation 1: RSI-Adaptive, STD-Filtered EMA as shown on the chart above
Confirmation 2: Williams Percent Range
Continuation: Fisher Transform
Exit: Rex Oscillator
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD protocol chain.
Giga Kaleidoscope Modularized Trading System Signals (based on the NNFX algorithm)
Standard Entry
1. GKD-C Confirmation 1 Signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
6. GKD-C Confirmation 1 signal was less than 7 candles prior
Volatility/Volume Entry
1. GKD-V Volatility/Volume signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-B Baseline agrees
6. GKD-C Confirmation 1 signal was less than 7 candles prior
Continuation Entry
1. Standard Entry, Baseline Entry, or Pullback; entry triggered previously
2. GKD-B Baseline hasn't crossed since entry signal trigger
3. GKD-C Confirmation Continuation Indicator signals
4. GKD-C Confirmation 1 agrees
5. GKD-B Baseline agrees
6. GKD-C Confirmation 2 agrees
1-Candle Rule Standard Entry
1. GKD-C Confirmation 1 signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
1-Candle Rule Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 1 signal was less than 7 candles prior
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume Agrees
1-Candle Rule Volatility/Volume Entry
1. GKD-V Volatility/Volume signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 1 signal was less than 7 candles prior
Next Candle:
1. Price retraced (Long: close < close or Short: close > close)
2. GKD-B Volatility/Volume agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-B Baseline agrees
PullBack Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is beyond 1.0x Volatility of Baseline
Next Candle:
1. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
2. GKD-C Confirmation 1 agrees
3. GKD-C Confirmation 2 agrees
4. GKD-V Volatility/Volume Agrees
]█ Setting up the GKD
The GKD system involves chaining indicators together. These are the steps to set this up.
Use a GKD-C indicator alone on a chart
1. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Simple"
Use a GKD-V indicator alone on a chart
**nothing, it's already useable on the chart without any settings changes
Use a GKD-B indicator alone on a chart
**nothing, it's already useable on the chart without any settings changes
Baseline (Baseline, Backtest)
1. Import the GKD-B Baseline into the GKD-BT Backtest: "Input into Volatility/Volume or Backtest (Baseline testing)"
2. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Baseline"
Volatility/Volume (Volatility/Volume, Backte st)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Solo"
2. Inside the GKD-V indicator, change the "Signal Type" setting to "Crossing" (neither traditional nor both can be backtested)
3. Import the GKD-V indicator into the GKD-BT Backtest: "Input into C1 or Backtest"
4. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Volatility/Volume"
5. Inside the GKD-BT Backtest, a) change the setting "Backtest Type" to "Trading" if using a directional GKD-V indicator; or, b) change the setting "Backtest Type" to "Full" if using a directional or non-directional GKD-V indicator (non-directional GKD-V can only test Longs and Shorts separately)
6. If "Backtest Type" is set to "Full": Inside the GKD-BT Backtest, change the setting "Backtest Side" to "Long" or "Short
7. If "Backtest Type" is set to "Full": To allow the system to open multiple orders at one time so you test all Longs or Shorts, open the GKD-BT Backtest, click the tab "Properties" and then insert a value of something like 10 orders into the "Pyramiding" settings. This will allow 10 orders to be opened at one time which should be enough to catch all possible Longs or Shorts.
Solo Confirmation Simple (Confirmation, Backtest)
1. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Simple"
1. Import the GKD-C indicator into the GKD-BT Backtest: "Input into Backtest"
2. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Solo Confirmation Simple"
Solo Confirmation Complex without Exits (Baseline, Volatility/Volume, Confirmation, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Complex"
4. Import the GKD-V indicator into the GKD-C indicator: "Input into C1 or Backtest"
5. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full wo/ Exits"
6. Import the GKD-C into the GKD-BT Backtest: "Input into Exit or Backtest"
Solo Confirmation Complex with Exits (Baseline, Volatility/Volume, Confirmation, Exit, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Complex"
4. Import the GKD-V indicator into the GKD-C indicator: "Input into C1 or Backtest"
5. Import the GKD-C indicator into the GKD-E indicator: "Input into Exit"
6. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full w/ Exits"
7. Import the GKD-E into the GKD-BT Backtest: "Input into Backtest"
Full GKD without Exits (Baseline, Volatility/Volume, Confirmation 1, Confirmation 2, Continuation, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C 1 indicator, change the "Confirmation Type" setting to "Confirmation 1"
4. Import the GKD-V indicator into the GKD-C 1 indicator: "Input into C1 or Backtest"
5. Inside the GKD-C 2 indicator, change the "Confirmation Type" setting to "Confirmation 2"
6. Import the GKD-C 1 indicator into the GKD-C 2 indicator: "Input into C2"
7. Inside the GKD-C Continuation indicator, change the "Confirmation Type" setting to "Continuation"
8. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full wo/ Exits"
9. Import the GKD-E into the GKD-BT Backtest: "Input into Exit or Backtest"
Full GKD with Exits (Baseline, Volatility/Volume, Confirmation 1, Confirmation 2, Continuation, Exit, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C 1 indicator, change the "Confirmation Type" setting to "Confirmation 1"
4. Import the GKD-V indicator into the GKD-C 1 indicator: "Input into C1 or Backtest"
5. Inside the GKD-C 2 indicator, change the "Confirmation Type" setting to "Confirmation 2"
6. Import the GKD-C 1 indicator into the GKD-C 2 indicator: "Input into C2"
7. Inside the GKD-C Continuation indicator, change the "Confirmation Type" setting to "Continuation"
8. Import the GKD-C Continuation indicator into the GKD-E indicator: "Input into Exit"
9. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full w/ Exits"
10. Import the GKD-E into the GKD-BT Backtest: "Input into Backtest"
Baseline + Volatility/Volume (Baseline, Volatility/Volume, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Baseline + Volatility/Volume"
2. Inside the GKD-V indicator, make sure the "Signal Type" setting is set to "Traditional"
3. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
4. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Baseline + Volatility/Volume"
5. Import the GKD-V into the GKD-BT Backtest: "Input into C1 or Backtest"
6. Inside the GKD-BT Backtest, change the setting "Backtest Type" to "Full". For this backtest, you must test Longs and Shorts separately
7. To allow the system to open multiple orders at one time so you can test all Longs or Shorts, open the GKD-BT Backtest, click the tab "Properties" and then insert a value of something like 10 orders into the "Pyramiding" settings. This will allow 10 orders to be opened at one time which should be enough to catch all possible Longs or Shorts.
█ GKD-C RSI-Adaptive, STD-Filtered EMA
What is the RSI?
The Relative Strength Index (RSI) is a popular momentum oscillator used in technical analysis to evaluate the strength and speed of price movements for a financial instrument, such as stocks, commodities, or cryptocurrencies. It was developed by J. Welles Wilder Jr. in 1978 and is used to identify overbought or oversold conditions in a market, as well as to generate potential buy or sell signals.
The RSI is calculated using the following formula:
RSI = 100 - (100 / (1 + RS))
Where:
RS (Relative Strength) = Average gain of up periods during the specified time frame / Average loss of down periods during the specified time frame.
The RSI is typically calculated over a 14-day period, but traders can adjust this to suit their preferences. The resulting RSI value ranges from 0 to 100.
In general, RSI values above 70 are considered overbought, suggesting that the market may be overextended and a price reversal or correction could occur. Conversely, RSI values below 30 are considered oversold, indicating that the market could be undervalued and a price increase might be expected.
It's important to note that the RSI, like any other technical indicator, is not infallible and should be used in conjunction with other tools and analysis methods to make more informed trading decisions. Additionally, the RSI might produce false signals, so traders should exercise caution and use proper risk management techniques.
What is the EMA?
The EMA, or Exponential Moving Average, is a type of moving average used in technical analysis to track the price trend of a financial instrument, such as stocks, commodities, or cryptocurrencies. Unlike the Simple Moving Average (SMA), which assigns equal weight to all data points within a specified period, the EMA assigns more weight to recent price data, making it more responsive to recent price changes.
The EMA is calculated using the following formula:
EMA = (Close - Previous EMA) * (2 / (N + 1)) + Previous EMA
Where:
-Close: The closing price of the financial instrument for the current period.
-Previous EMA: The EMA calculated for the previous period.
-N: The number of periods chosen for the EMA calculation.
The EMA helps smooth out price data over time, emphasizing recent price movements to better identify trends and potential reversals. This can provide traders with valuable information on whether to enter or exit a position.
It is important to remember that the EMA, like any other technical indicator, should be used in conjunction with other tools and analysis methods to make more informed trading decisions.
What is the RSI-Adaptive, STD-Filtered EMA?
The RSI Adaptive EMA is a combination of two technical indicators – the Relative Strength Index (RSI) and the Exponential Moving Average (EMA) – to create a more responsive and adaptive indicator that can better track price trends and momentum in financial markets.
The idea behind the RSI Adaptive EMA is to use the RSI value to adjust the smoothing factor of the EMA, making the EMA more sensitive to price changes when the market is experiencing strong momentum and less sensitive when the market is in a consolidation or ranging phase. This adaptive quality helps to reduce lag and provide more timely signals compared to using the standard EMA.
Here's how the RSI Adaptive EMA is calculated:
1. Calculate the RSI for the desired period (typically 14 days).
2. Normalize the RSI value to a range between 0 and 1 by dividing it by 100.
3. Calculate the adaptive smoothing factor (α) using the normalized RSI value: α = 2 / (RSI + 1).
4. Compute the RSI Adaptive EMA using the adaptive smoothing factor: Adaptive EMA = (Close - Previous Adaptive EMA) * α + Previous Adaptive EMA
5. The final EMA value is then filtered using a Standard Deviation stepping algorithm.
By combining the RSI and EMA, the RSI Adaptive EMA aims to provide a more effective tool for identifying price trends and potential reversals. However, like any other technical indicator, it is not foolproof and should be used in conjunction with other tools and analysis methods to make informed trading decisions.
Requirements
Inputs
Confirmation 1: GKD-V Volatility / Volume indicator
Confirmation 2: GKD-C Confirmation indicator
Continuation: GKD-C Confirmation indicator
Solo Confirmation Simple: GKD-B Baseline
Solo Confirmation Complex: GKD-V Volatility / Volume indicator
Solo Confirmation Super Complex: GKD-V Volatility / Volume indicator
Stacked 1: None
Stacked 2+: GKD-C, GKD-V, or GKD-B Stacked 1
Outputs
Confirmation 1: GKD-C Confirmation 2 indicator
Confirmation 2: GKD-C Continuation indicator
Continuation: GKD-E Exit indicator
Solo Confirmation Simple: GKD-BT Backtest
Solo Confirmation Complex: GKD-BT Backtest or GKD-E Exit indicator
Solo Confirmation Super Complex: GKD-C Continuation indicator
Stacked 1: GKD-C, GKD-V, or GKD-B Stacked 2+
Stacked 2+: GKD-C, GKD-V, or GKD-B Stacked 2+ or GKD-BT Backtest
Additional features will be added in future releases.
NSDT EMA+ATRI had this idea to make a custom Moving Average that adapts to the market. I chose to use the Average True Range. As the market makes bigger/smaller moves, this custom Moving Average applies the ATR as the length of the EMA. This gives more distance to the Moving Average as the volatility picks up or reduces.
Just set the length you want the ATR to look back (default is 100) and the multiplier (default is 2) to work with the instrument being traded.
It's also setup for use on Multi Time Frames.
LowFinder_PyraMider_V2This strategy is a result of an exploration to experiment with other ways to detect lows / dips in the price movement, to try out alternative ways to exit and stop positions and a dive into risk management. It uses a combination of different indicators to detect and filter the potential lows and opens multiple positions to spread the risk and opportunities for unrealized losses or profits. This script combines code developed by fellow Tradingview community_members.
LowFinder
The lows in the price movement are detected by the Low finder script by RafaelZioni . It finds the potential lows based on the difference between RSI and EMA RSI. The MTF RSI formula is part of the MTFindicators library developed by Peter_O and is integrated in the Low finder code to give the option to use the RSI of higher timeframes. The sensitivity of the LowFinder is controlled by the MA length. When potential lows are detected, a Moving Average, a MTF Stochastic (based the the MTFindiicators by Peter_O) and the average price level filter out the weak lows. In the settings the minimal percentage needed for a low to be detected below the average price can be specified.
Order Sizing and Pyramiding
Pyramiding, or spreading multiple positions, is at the heart of this strategy and what makes it so powerful. The order size is calculated based on the max number of orders and portfolio percentage specified in the input settings. There are two order size modes. The ‘base’ mode uses the same base quantity for each order it opens, the ‘multiply’ mode multiplies the quantity with each order number. For example, when Long 3 is opened, the quantity is multiplied by 3. So, the more orders the bigger the consecutive order sizes. When using ‘multiply’ mode the sizes of the first orders are considerably lower to make up for the later bigger order sizes. There is an option to manually set a fixed order size but use this with caution as it bypasses all the risk calculations.
Stop Level, Take Profit, Trailing Stop
The one indicator that controls the exits is the Stop Level. When close crosses over the Stop Level, the complete position is closed and all orders are exited. The Stop Level is calculated based on the highest high given a specified candle lookback (settings). There is an option to deviate above this level with a specified percentage to tweak for better results. You can activate a Take Profit / Trailing Stop. When activated and close crosses the specified percentage, the Stop Level logic changes to a trailing stop to gain more profits. Another option is to use the percentage as a take profit, either when the stop level crosses over the take profit or close. With this option active, you can make this strategy more conservative. It is active by default.
And finally there is an option to Take Profit per open order. If hit, the separate orders close. In the current settings this option is not used as the percentage is 10%.
Stop Loss
I published an earlier version of this script a couple of weeks ago, but it got hidden by the moderators. Looking back, it makes sense because I didn’t pay any attention to risk management and save order sizing. This resulted in unrealistic results. So, in this script update I added a Stop Loss option. There are two modes. The ‘average price’ mode calculates the stop loss level based on a given percentage below the average price of the total position. The ‘equity’ mode calculates the stop loss level based on a given percentage of your equity you want to lose. By default, the ‘equity’ mode is active. By tweaking the percentage of the portfolio size and the stop loss equity mode, you can achieve a quite low risk strategy set up.
Variables in comments
To sent alerts to my exchange I use a webhook server. This works with a sending the information in the form of a comment. To be able to send messages with different quantities, a variable is added to the comment. This makes it possible to open different positions on the exchange with increasing quantities. To test this the quantities are printed in the comment and the quantities are switched off in the style settings.
This code is a result of a study and not intended for use as a worked out and full functioning strategy. Use it at your own risk. To make the code understandable for users that are not so much introduced into pine script (like me), every step in the code is commented to explain what it does. Hopefully it helps.
Enjoy!
VWAP+15EMA with RSIVWAP+EMA+RSI Strategy for the group MelléCasH
This strategy will enter a long position when the closing price is above both the VWAP and the 15 EMA, and the RSI is above the specified overbought level. It will exit the position when the price falls by the specified stop loss percentage, rises by the specified take profit percentage, or when the trailing stop loss (which trails the highest price achieved after the position was entered by the specified percentage) is hit. The VWAP, EMA, and RSI indicators are also plotted on the chart for reference.
Simple Chop ZoneThe original Chop Zone indicator by Trading View is good, but has a few limitations which I've addressed in this one
Too many colors which confuse and/or overwhelm users like me
Inability to change the EMA period
This one has just 3 customizable colors for
Uptrend - default = Turquoise
Downtrend - default = red
Everything else - default = lime
And you can set your own EMA length. The default is 34 as per the original Chop Zone indicator
PivotBoss Tool (PART 1)Hello Everyone,
This indicator is being published on TradingView to help traders solve their multiframe analysis issue and at the same time get additional information of different timeframe like - Strength, Momentum and Central Pivot Range relationships all under one single frame.
This indicator is based on the concepts of Secrets of Pivot Boss by Mr.Frank Ochoa and strives to provide more insightful information of pivot points and other general indicators being used by traders on day-to-day basis in the simplest format possible so that traders of all kinds can relate to the same.
Below is the brief information of the indicator table you see in the layout of the above chart -
-This is the most interesting part of the indicator where the user gets to the Pivot Trend, RSI strength and Central Pivot Range (CPR) relationship all under one table which comes to be very handy during Intraday trading and Swing/Positional Trading.
#Pivot Trend
This column gives the user the information regarding price movement near to pivot points across multiple timeframes in a single frame which gives the user the accessibility to track the trend in different time frames, to make the information readily available colour code are included in the table which is customisable in the hands of the user and below is the explanation for the same -
- GREEN (Above H3)
- GREY (Between H3-L3)
- RED (Below L3)
#RSI
This column gives the user the information regarding price movement near to RSI values across multiple timeframes in a single frame which gives the user the accessibility to track the momentum in different time frames, to make the information readily available colour code are included in the table which is customisable in the hands of the user and below is the explanation for the same -
- GREEN (Above 70)
- GREY (Between 30 to 70)
- RED (Below 30)
#Central Pivot Range (CPR) Relationship
This column gives an idea of the trend direction and intensity which is exactly formulated according the concepts of PivotBoss Book and it also states the relationship of CPR's with customisable colour codes in the indicator settings, to make the information readily available colour code are included in the table which is customisable in the hands of the user and below is the explanation for the same -
There are generally six possible relationships for CPR compared to previous CPR where the timeframe can be variable but the relationship identification stays constant which is depicted as below -
- GREEN
1) Dark Green denotes "Higher Value CPR Relationship"
2) Light Green denotes "Overlapping Higher Value CPR Relationship"
- RED
3) Dark Red denotes "Lower Value CPR Relationship"
4) Light Red denotes "Overlapping Lower Value CPR Relationship"
- GREY
5) Denotes "Outside Value CPR Relationship"
- YELLOW
6) Denotes "Inside Value CPR Relationship"
This is a very basic tool created to identify Strength, Momentum and Central Pivot Relationship (CPR) across different timeframes so that the user is able to identify the broader aspect of the stock in a single frame and thus can execute his trading skills with optimum efficiency.
This indicator will be updated with time and depending on community's feedback and requirements.
Credits -
- Mr. Frank Ochoa (Concepts and ideas from the book 'Secrets of PivotBoss' )
- TradingView (Providing a platform to traders to simply their trading through 'PineScript')
Regards,
Mukkull
Moving Average Scalper by nnamdertWhat does this Indicator Do?
By request and popular demand, I have created a quick and easy Moving Average Crossover Scalper Indicator. This indicator simply allows the trader to visualize scalping opportunities in an easy way using MA crossovers.
The Indicator also plots multiple higher moving averages via an "optional" table. The table gives a quick glance at the overall trend (based on moving Averages alone).
Users can adjust the initial Moving Average Length and the number of additional Moving Average Lengths to be plotted on the chart.
How do I use it?
As shown below, the cross overs are very easy to see. The Stoploss "should" be set at the most recent swing high or low prior to the MA Cross.
The dotted yellow line must cross above or below the thick mutli-colored line in order to be considered valid.
As seen in the screenshot below, an optional input setting turns ON / OFF additional Moving Average "Lines" and plots them on the chart. In addition, the indicator color fills between the moving averages based on Bullish or Bearish movement. If the lines are in continuity, then the color will be either RED or GREEN depending on the market sentiment (bull or bear).
The total number of Moving Averages listed in the table can be manually adjusted in the settings by the user. The table is small and see-through so it works on mobile devices as well and allows the user to still see the candles easily. Simply double clicking on the table will bring up the settings.
As shown below, the table can be relocated to a position acceptable to the user if it is in the way. This option is available under input settings.
I hope this indicator proves useful for you and your trading style. If you have any suggestions please let me know.
Ignition Cha Cha ChaIgnition Cha Cha Cha (ICCC) is a 3 color coded moving average indicator which numerically quantify the angle of their trends. I have labeled them as fast, medium and slow. The trend colors are Green for bullish, Red for bearish and Grey for sideways. The sideways movement can be user defined for all 3 in the settings under Threshold. If you regard for example anything under 10º as sideways then place 10 in the corresponding threshold and any angle under 10º will give a grey moving average and a grey labeled text. I use this chart in several ways. If you don't want moving averages all over your Chartistic Masterpiece you can turn off the plots and leave the numeric angles which will give you an overview of the trend. Conversely if you want to make the ultimate trend chart you can setup a 4 chart layout, Weekly, Daily, 12 hour and 4 hour and add the indicator with 200/50/25 moving averages and look for confluence. I find the best way for this is turn off the candles and use the moving averages with the numeric labels. You also have the ability to turn off and on different aspects of the indicator so that there is good control over its look. Also I have given the indicator lots of Alert presets for all 3 of the moving averages so you can avoid demented screen-stairing. Please forgive the name, my mother made me do Ballroom dancing lessons as a kid.
Rebalance by StrategyThaiStrategy Rebalance
Rebalancing trade in the context of cryptocurrency refers to adjusting the composition of a cryptocurrency portfolio to maintain a desired allocation of different digital assets. As the market value of various cryptocurrencies changes over time, the proportion of each asset in the portfolio may deviate from the original target allocation. Rebalancing aims to restore the portfolio to its desired balance, ensuring it remains aligned with the investor's risk tolerance and investment goals.
Here are some steps to rebalance a cryptocurrency portfolio:
Assess your portfolio: Review your current cryptocurrency holdings and their respective market values. Determine the current allocation of each asset as a percentage of your total portfolio value.
Set target allocations: Decide on the target allocation for each cryptocurrency in your portfolio based on your investment goals, risk tolerance, and market outlook. This might involve allocating a higher percentage to more established cryptocurrencies like Bitcoin and Ethereum and a smaller percentage to newer or more volatile digital assets.
Calculate rebalancing amounts: Compare your current allocations with your target allocations. Calculate the amount of each cryptocurrency you need to buy or sell to achieve your target allocations.
Execute trades: Buy or sell the necessary amounts of each cryptocurrency to reach your target allocations. Keep in mind that transaction fees and taxes may apply, depending on your jurisdiction and the trading platform you use.
Monitor and adjust: Regularly review your cryptocurrency portfolio and market conditions. Rebalance as needed to maintain your target allocations and adapt to changing market dynamics.
Rebalancing a cryptocurrency portfolio can help manage risk and potentially enhance returns by ensuring that the portfolio remains diversified and aligned with the investor's objectives. However, it is important to consider the costs and tax implications of frequent rebalancing before implementing this strategy.
##########################################################################
Setting input
Start : start date
End : end date
----
Rebalance Mode :
Normal = Rebalance Always adjust the balance according to the preset proportions. , e.g. 50% of equity.
Fixed Asset = Fixed Asset value. e.g. always Fixed Asset 50% of capital
----
Proportion : Proportion 0.05 = 5% of capital or equity
Min Size Trade value : The minimum that the exchange allows to trade in usdt,usd
Range Price : distance openclose last price (0.01 = 1%)
Use indicator :
Indicator Period : Length
TradeEasy - KintroThe TradingView script provided is a custom indicator named "TradeEasy - Kintro". It is created by the author Kintro and is designed to help traders identify potential buy and sell signals in the market. The indicator is based on the Exponential Moving Average (EMA) and uses two different EMAs, one with a period of 20 and the other with a period of 50.
The indicator is meant to be used on the 5-minute timeframe and it is recommended to use TradingView in Dark Mode for better appearance. The author also reminds users that no strategy works 100% accurately and backtesting should be done before trading with a real account. The author is not responsible for any losses incurred by traders.
The indicator uses a simple set of rules to generate trading signals. The thick line on the chart represents the 50 EMA while the thin line represents the 20 EMA. When the thin line crosses upwards over the thick line, it indicates a bullish signal. After the crossover, traders are advised to wait for the price to pullback between the two lines. A range should then be created while the price moves through the thin line.
On the break of the range, an entry signal is generated, and the stop loss should be set below the range. The author advises traders to exit their profits according to their own analysis or price action and not to re-enter on the next pullback of the same trend. The same rules apply when the thin line crosses downwards over the thick line.
The author emphasizes that range creation is mandatory on crossing and that traders should not try to go against the trend. If the price is above both lines, traders should only go for buy orders, and vice versa.
If there is no range created while crossing, traders are advised not to enter the market. Traders should wait for the opportunity and not force a trade.
The indicator also includes a plot of the 34 EMA, and a range is created above and below the price action using the "up" and "down" variables. The author uses the "fill" function to color the background of the chart to highlight the range. The "dummy" variable is used to plot circles above or below the price action, depending on the trend.
In summary, the "TradeEasy - Kintro" indicator is a custom indicator designed to help traders identify potential buy and sell signals based on the crossing of two EMAs. The author provides a set of rules to generate trading signals and advises traders to wait for the opportunity and not force a trade. The indicator also includes a visual representation of the range created on the chart. As always, traders are advised to conduct their own research and analysis before entering any trades.
Relative Strength Index w/ STARC Bands and PivotsThis is an old script that I use with some useful RSI strategies from "Technical Analysis for the Trading Professional" 2nd edition by Constance Brown.
The base RSI comes with the option for custom length, and has some pre-configured ranges for looking at exits and entrances. The idea is to be bullish when bounces happen in the red zone during an already bullish trend or when the indicator enters green without a rejection. Be bearish if the indicator falls through the red zone or fails to enter green during an already bearish trend.
I have added the formulas used for creating STARC bands (just think fancier volatility bands) with adjustable tolerances. The idea is to look out for when the RSI touches one of the bands and reverses. This is usually indicative of a strong reversal (though the timing will be up to the trader). Best use this on shorter time frames during a volatile time of a stock's price action.
Although a little messy, there is a small segment of the script which includes pivot points. I like to use these because they make indicating local highs/lows for finding divergences easier.
Finally, I have added a couple of customizable EMAS for the RSI itself. Useful when combined with the other features!
Bar Color Long / Short Indicator With Advised SLOverview
This script is a trading indicator named "Bar Color Long / Short Indicator With Advised SL" designed for the TradingView platform. The indicator's primary purpose is to provide entry signals for long and short positions, based on various technical analysis methods. Additionally, the indicator suggests stop-loss levels for both long and short positions.
User Inputs
The indicator has several user inputs, such as:
Length
Smoothing
Multiplier
Show bar colors (ON/OFF)
When the bar colors are turned off, the alert signals for long and short positions will be displayed instead.
Custom Risk Calculation
The script calculates a custom risk level based on a modified version of the RSI (Relative Strength Index) formula. The custom risk level is divided into three categories: low, medium, and high.
Sentiment Score Calculation
The indicator calculates a sentiment score based on a combination of methods resembling EMA (Exponential Moving Average), MACD (Moving Average Convergence Divergence), and ROC (Rate of Change). The sentiment score is used to determine if the sentiment is positive or negative.
Bollinger Bands Percent and Combined Signal
The Bollinger Bands Percent is calculated, and the custom risk, sentiment score, and Bollinger Bands Percent are combined to generate a new signal. This signal is used in conjunction with EMA10 to determine the bar colors and provide entry signals.
Bar Colors
Based on the combined signal and EMA10, the script determines the bar colors as follows:
Orange: Positive sentiment
Blue: Negative sentiment
Gray: Neutral
Entry Signals and Alerts
When the bar colors are turned off, the indicator displays large green arrow signals for long (buy) positions and red arrow signals for short (sell) positions based on the sentiment and EMA10 conditions. The script also includes alert conditions for long and short signals, which can be used to set up notifications when these signals are triggered in the TradingView platform.
Advised Stop-Loss Levels
The indicator plots stop-loss lines for both long and short positions at the last candle, accompanied by labels showing the advised stop-loss levels in numeric values.
GKD-C Momentum Ratio Oscillator [Loxx]Giga Kaleidoscope GKD-C Momentum Ratio Oscillator is a Confirmation module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
█ Giga Kaleidoscope Modularized Trading System
What is Loxx's "Giga Kaleidoscope Modularized Trading System"?
The Giga Kaleidoscope Modularized Trading System is a trading system built on the philosophy of the NNFX (No Nonsense Forex) algorithmic trading.
What is the NNFX algorithmic trading strategy?
The NNFX (No-Nonsense Forex) trading system is a comprehensive approach to Forex trading that is designed to simplify the process and remove the confusion and complexity that often surrounds trading. The system was developed by a Forex trader who goes by the pseudonym "VP" and has gained a significant following in the Forex community.
The NNFX trading system is based on a set of rules and guidelines that help traders make objective and informed decisions. These rules cover all aspects of trading, including market analysis, trade entry, stop loss placement, and trade management.
Here are the main components of the NNFX trading system:
1. Trading Philosophy: The NNFX trading system is based on the idea that successful trading requires a comprehensive understanding of the market, objective analysis, and strict risk management. The system aims to remove subjective elements from trading and focuses on objective rules and guidelines.
2. Technical Analysis: The NNFX trading system relies heavily on technical analysis and uses a range of indicators to identify high-probability trading opportunities. The system uses a combination of trend-following and mean-reverting strategies to identify trades.
3. Market Structure: The NNFX trading system emphasizes the importance of understanding the market structure, including price action, support and resistance levels, and market cycles. The system uses a range of tools to identify the market structure, including trend lines, channels, and moving averages.
4. Trade Entry: The NNFX trading system has strict rules for trade entry. The system uses a combination of technical indicators to identify high-probability trades, and traders must meet specific criteria to enter a trade.
5. Stop Loss Placement: The NNFX trading system places a significant emphasis on risk management and requires traders to place a stop loss order on every trade. The system uses a combination of technical analysis and market structure to determine the appropriate stop loss level.
6. Trade Management: The NNFX trading system has specific rules for managing open trades. The system aims to minimize risk and maximize profit by using a combination of trailing stops, take profit levels, and position sizing.
Overall, the NNFX trading system is designed to be a straightforward and easy-to-follow approach to Forex trading that can be applied by traders of all skill levels.
Core components of an NNFX algorithmic trading strategy
The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend
3. Confirmation 1 - a technical indicator used to identify trends
4. Confirmation 2 - a technical indicator used to identify trends
5. Continuation - a technical indicator used to identify trends
6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown
7. Exit - a technical indicator used to determine when a trend is exhausted
What is Volatility in the NNFX trading system?
In the NNFX (No Nonsense Forex) trading system, ATR (Average True Range) is typically used to measure the volatility of an asset. It is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. ATR is calculated by taking the average of the true range values over a specified period.
True range is calculated as the maximum of the following values:
-Current high minus the current low
-Absolute value of the current high minus the previous close
-Absolute value of the current low minus the previous close
ATR is a dynamic indicator that changes with changes in volatility. As volatility increases, the value of ATR increases, and as volatility decreases, the value of ATR decreases. By using ATR in NNFX system, traders can adjust their stop loss and take profit levels according to the volatility of the asset being traded. This helps to ensure that the trade is given enough room to move, while also minimizing potential losses.
Other types of volatility include True Range Double (TRD), Close-to-Close, and Garman-Klass
What is a Baseline indicator?
The baseline is essentially a moving average, and is used to determine the overall direction of the market.
The baseline in the NNFX system is used to filter out trades that are not in line with the long-term trend of the market. The baseline is plotted on the chart along with other indicators, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR).
Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards, only long trades are taken, and if the baseline is sloping downwards, only short trades are taken. This approach helps to ensure that trades are in line with the overall trend of the market, and reduces the risk of entering trades that are likely to fail.
By using a baseline in the NNFX system, traders can have a clear reference point for determining the overall trend of the market, and can make more informed trading decisions. The baseline helps to filter out noise and false signals, and ensures that trades are taken in the direction of the long-term trend.
What is a Confirmation indicator?
Confirmation indicators are technical indicators that are used to confirm the signals generated by primary indicators. Primary indicators are the core indicators used in the NNFX system, such as the Average True Range (ATR), the Moving Average (MA), and the Relative Strength Index (RSI).
The purpose of the confirmation indicators is to reduce false signals and improve the accuracy of the trading system. They are designed to confirm the signals generated by the primary indicators by providing additional information about the strength and direction of the trend.
Some examples of confirmation indicators that may be used in the NNFX system include the Bollinger Bands, the MACD (Moving Average Convergence Divergence), and the MACD Oscillator. These indicators can provide information about the volatility, momentum, and trend strength of the market, and can be used to confirm the signals generated by the primary indicators.
In the NNFX system, confirmation indicators are used in combination with primary indicators and other filters to create a trading system that is robust and reliable. By using multiple indicators to confirm trading signals, the system aims to reduce the risk of false signals and improve the overall profitability of the trades.
What is a Continuation indicator?
In the NNFX (No Nonsense Forex) trading system, a continuation indicator is a technical indicator that is used to confirm a current trend and predict that the trend is likely to continue in the same direction. A continuation indicator is typically used in conjunction with other indicators in the system, such as a baseline indicator, to provide a comprehensive trading strategy.
What is a Volatility/Volume indicator?
Volume indicators, such as the On Balance Volume (OBV), the Chaikin Money Flow (CMF), or the Volume Price Trend (VPT), are used to measure the amount of buying and selling activity in a market. They are based on the trading volume of the market, and can provide information about the strength of the trend. In the NNFX system, volume indicators are used to confirm trading signals generated by the Moving Average and the Relative Strength Index. Volatility indicators include Average Direction Index, Waddah Attar, and Volatility Ratio. In the NNFX trading system, volatility is a proxy for volume and vice versa.
By using volume indicators as confirmation tools, the NNFX trading system aims to reduce the risk of false signals and improve the overall profitability of trades. These indicators can provide additional information about the market that is not captured by the primary indicators, and can help traders to make more informed trading decisions. In addition, volume indicators can be used to identify potential changes in market trends and to confirm the strength of price movements.
What is an Exit indicator?
The exit indicator is used in conjunction with other indicators in the system, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR), to provide a comprehensive trading strategy.
The exit indicator in the NNFX system can be any technical indicator that is deemed effective at identifying optimal exit points. Examples of exit indicators that are commonly used include the Parabolic SAR, the Average Directional Index (ADX), and the Chandelier Exit.
The purpose of the exit indicator is to identify when a trend is likely to reverse or when the market conditions have changed, signaling the need to exit a trade. By using an exit indicator, traders can manage their risk and prevent significant losses.
In the NNFX system, the exit indicator is used in conjunction with a stop loss and a take profit order to maximize profits and minimize losses. The stop loss order is used to limit the amount of loss that can be incurred if the trade goes against the trader, while the take profit order is used to lock in profits when the trade is moving in the trader's favor.
Overall, the use of an exit indicator in the NNFX trading system is an important component of a comprehensive trading strategy. It allows traders to manage their risk effectively and improve the profitability of their trades by exiting at the right time.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v1.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data between modules. Data is passed between each module as described below:
GKD-B => GKD-V => GKD-C(1) => GKD-C(2) => GKD-C(Continuation) => GKD-E => GKD-BT
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Strategy with 1-3 take profits, trailing stop loss, multiple types of PnL volatility, and 2 backtesting styles
Baseline: Hull Moving Average
Volatility/Volume: Hurst Exponent
Confirmation 1: Momentum Ratio Oscillator as shown on the chart above
Confirmation 2: Williams Percent Range
Continuation: Fisher Transform
Exit: Rex Oscillator
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD protocol chain.
Giga Kaleidoscope Modularized Trading System Signals (based on the NNFX algorithm)
Standard Entry
1. GKD-C Confirmation 1 Signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
6. GKD-C Confirmation 1 signal was less than 7 candles prior
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
█ GKD-C Momentum Ratio Oscillator
What is an EMA?
EMA stands for Exponential Moving Average , which is a type of moving average that is commonly used in technical analysis to smooth out price data and identify trends.
In a simple moving average ( SMA ), each data point is given equal weight when calculating the average. For example, if you are calculating the 10-day SMA , you would add up the prices for the past 10 days and divide by 10 to get the average. In contrast, in an EMA , more weight is given to recent prices, while older prices are given less weight.
The formula for calculating an EMA involves using a smoothing factor that is multiplied by the difference between the current price and the previous EMA value, and then adding this to the previous EMA value. The smoothing factor is typically calculated based on the length of the EMA being used. For example, a 10-day EMA might use a smoothing factor of 2/(10+1) or 0.1818.
The result of using an EMA is that the line produced is more responsive to recent price changes than a simple moving average . This makes it useful for identifying short-term trends and potential trend reversals. However, it can also be more volatile and prone to whipsaws, so it is often used in combination with other indicators to confirm signals.
Overall, the EMA is a widely used and versatile tool in technical analysis , and its effectiveness depends on the specific context in which it is applied.
What is Momentum?
In technical analysis , momentum refers to the rate of change of an asset's price over a certain period of time. It is often used to identify trends and potential trend reversals in financial markets.
Momentum is calculated by subtracting the closing price of an asset X days ago from its current closing price, where X is the number of days being used for the calculation. The result is the momentum value for that particular day. A positive momentum value suggests that prices are increasing, while a negative value indicates that prices are decreasing.
Traders use momentum in a variety of ways. One common approach is to look for divergences between the momentum indicator and the price of the asset being traded. For example, if an asset's price is trending upwards but its momentum is trending downwards, this could be a sign of a potential trend reversal.
Another popular strategy is to use momentum to identify overbought and oversold conditions in the market. When an asset's price has been rising rapidly and its momentum is high, it may be considered overbought and due for a correction. Conversely, when an asset's price has been falling rapidly and its momentum is low, it may be considered oversold and due for a bounce back up.
Momentum is also often used in conjunction with other technical indicators, such as moving averages or Bollinger Bands , to confirm signals and improve the accuracy of trading decisions.
Overall, momentum is a useful tool for traders and investors to analyze price movements and identify potential trading opportunities. However, like all technical indicators, it should be used in conjunction with other forms of analysis and with consideration of the broader market context.
What is Momentum Ratio Oscillator?
The theory behind this indicator involves utilizing a sequence of exponential moving average ( EMA ) calculations to achieve a smoother value of momentum ratio, which compares the current value to the previous one. Although this results in an outcome similar to that of some pre-existing indicators (such as volume zone or price zone oscillators), the use of EMA for smoothing is what sets it apart. EMA produces a smooth step-like output when values undergo sudden changes, whereas the mathematics used for those other indicators are completely distinct. This is a concept by the beloved Mladen of FX forums.
To utilize this version of the indicator, you have the option of using either levels, middle, or signal crosses for signals. The indicator is range bound from 0 to 1.
Requirements
Inputs
Confirmation 1 and Solo Confirmation: GKD-V Volatility / Volume indicator
Confirmation 2: GKD-C Confirmation indicator
Outputs
Confirmation 2 and Solo Confirmation Complex: GKD-E Exit indicator
Confirmation 1: GKD-C Confirmation indicator
Continuation: GKD-E Exit indicator
Solo Confirmation Simple: GKD-BT Backtest strategy
Additional features will be added in future releases.
Momentum Ratio Oscillator [Loxx]What is Momentum Ratio Oscillator?
The theory behind this indicator involves utilizing a sequence of exponential moving average (EMA) calculations to achieve a smoother value of momentum ratio, which compares the current value to the previous one. Although this results in an outcome similar to that of some pre-existing indicators (such as volume zone or price zone oscillators), the use of EMA for smoothing is what sets it apart. EMA produces a smooth step-like output when values undergo sudden changes, whereas the mathematics used for those other indicators are completely distinct. This is a concept by the beloved Mladen of FX forums.
To utilize this version of the indicator, you have the option of using either levels, middle, or signal crosses for signals. The indicator is range bound from 0 to 1.
What is an EMA?
EMA stands for Exponential Moving Average, which is a type of moving average that is commonly used in technical analysis to smooth out price data and identify trends.
In a simple moving average (SMA), each data point is given equal weight when calculating the average. For example, if you are calculating the 10-day SMA, you would add up the prices for the past 10 days and divide by 10 to get the average. In contrast, in an EMA, more weight is given to recent prices, while older prices are given less weight.
The formula for calculating an EMA involves using a smoothing factor that is multiplied by the difference between the current price and the previous EMA value, and then adding this to the previous EMA value. The smoothing factor is typically calculated based on the length of the EMA being used. For example, a 10-day EMA might use a smoothing factor of 2/(10+1) or 0.1818.
The result of using an EMA is that the line produced is more responsive to recent price changes than a simple moving average. This makes it useful for identifying short-term trends and potential trend reversals. However, it can also be more volatile and prone to whipsaws, so it is often used in combination with other indicators to confirm signals.
Overall, the EMA is a widely used and versatile tool in technical analysis, and its effectiveness depends on the specific context in which it is applied.
What is Momentum?
In technical analysis, momentum refers to the rate of change of an asset's price over a certain period of time. It is often used to identify trends and potential trend reversals in financial markets.
Momentum is calculated by subtracting the closing price of an asset X days ago from its current closing price, where X is the number of days being used for the calculation. The result is the momentum value for that particular day. A positive momentum value suggests that prices are increasing, while a negative value indicates that prices are decreasing.
Traders use momentum in a variety of ways. One common approach is to look for divergences between the momentum indicator and the price of the asset being traded. For example, if an asset's price is trending upwards but its momentum is trending downwards, this could be a sign of a potential trend reversal.
Another popular strategy is to use momentum to identify overbought and oversold conditions in the market. When an asset's price has been rising rapidly and its momentum is high, it may be considered overbought and due for a correction. Conversely, when an asset's price has been falling rapidly and its momentum is low, it may be considered oversold and due for a bounce back up.
Momentum is also often used in conjunction with other technical indicators, such as moving averages or Bollinger Bands, to confirm signals and improve the accuracy of trading decisions.
Overall, momentum is a useful tool for traders and investors to analyze price movements and identify potential trading opportunities. However, like all technical indicators, it should be used in conjunction with other forms of analysis and with consideration of the broader market context.
Extras
Alerts
Signals
Loxx's Expanded Source Types, see here for details
CPR with inside candle, Pivot Points and 4EMA The CPR trading strategy is a technical analysis approach that combines multiple indicators to determine potential price levels and trading opportunities. The strategy uses three main components: Inside Candles, Pivot Points, and the 4EMA.
Inside Candles: The Inside Candle pattern is a candlestick pattern where the current candle has a lower high and a higher low than the previous candle. This pattern can indicate a period of consolidation or indecision in the market and can signal a potential reversal or continuation of the trend.
Pivot Points: Pivot Points are technical indicators that use the previous day's price data to calculate key levels of support and resistance for the current trading day. These levels can act as potential areas of buying or selling pressure and can help traders identify potential entry and exit points.
4EMA: The 4EMA is a short-term Exponential Moving Average that tracks the average price of an asset over the previous four periods. This indicator is used to help identify short-term trends in the market and can signal potential buying or selling opportunities.
To apply the CPR strategy, traders first look for Inside Candles on their chart, indicating a period of consolidation or indecision in the market. Next, they identify the Pivot Points for the current trading day, which can act as potential areas of support or resistance. Finally, traders use the 4EMA to confirm the direction of the trend and potential entry or exit points.
For example, if an Inside Candle forms at a Pivot Point level and the 4EMA is indicating an uptrend, this could be a potential buying opportunity. Conversely, if an Inside Candle forms at a Pivot Point level and the 4EMA is indicating a downtrend, this could be a potential selling opportunity.
CoffeeShopCrypto 3pl MAThe CoffeeShopCrypto 3pl MA indicator is a technical analysis tool that uses three different moving averages to identify trends in the price of an asset. The three moving averages have lengths of 12, 26, and 50. If these numbers sound familiar its because they are based off the standard of the MACD indicator, and can be either simple moving averages (SMA) or exponential moving averages (EMA), depending on user preference.
The following is plotted on the chart
The fast EMA/SMA (based on the 12-period length) in yellow.
The mid EMA/SMA (based on the 26-period length) in gray.
The slow EMA/SMA (based on the 50-period length) in either green or red, depending on whether the current close price is above or below the Overall Trend MA.
In addition to the moving averages, the indicator also calculates the MACD (Moving Average Convergence Divergence), and uses it to color the bars based on the momentum of the asset.
The MACD is calculated using two user-defined lengths (fast and slow), as well as a user-defined smoothing length for the signal line. The oscillator and signal line can be either SMA or EMA, and the colors of the MACD bars are based on whether the histogram is growing or falling, and whether it is above or below the zero line.
Overall, this indicator provides traders with a comprehensive tool for understanding the trend of an asset, as well as the momentum behind that trend. The moving averages provide a clear visual representation of the trend, while the MACD bars give insight into the strength of that trend and potential shifts in momentum.
---------------LONG ENTRY----------------
MA1 above MA2 and Overall trend = Green
IF RSI is above its midline you are confirmed for a long entry
-----------Short Entry--------------
MA1 below MA2 and Overall trend = Red
IF RSI is below its midline you are confirmed for a short entry
Know Sure Thing + RibbonFrom now on this will be the main indicator I will be using.
The mathematical foundation of KST is elegant and trustworthy. I took the time to share this beautiful (in my opinion) indicator, because you will probably be seeing it in my future ideas.
I am not a trader, this indicator was made to analyze mainly long-term charts, and trend-continuation/change analysis.
The purpose of this indicator is not to give entry/exit points. However, the 9-period EMA (tightest EMA) can serve as an alternative to the classic "9-period MA signal line".
Tread lightly, for this is hallowed ground.
-Father Grigori
ADD 2This is a modification to the original ADD script by Tom1trader
I added the option to choose the timeframe, moving average type and length.
Note from the original script:
"This is the NYSE Advancers - decliners which the SPX pretty much follows. You can chart it like any index (ADD -NYSE $ADV MINUS $DECL) but I find it more useful in a separate panel with colors for direction.
The level gives an idea of days move (example: plus or minus 500 is not much movement through the session) but I follow the direction as when more stocks advance (green) or decline (red) the index tends to track it pretty closely.
On SPX , SPY and correlates - very useful for intra-day trading (Scalping or 0DTE option trades) but not for higher time frames at all. If you chart the ADD in a chart and compare 5 minute to daily you will see what I mean."
MarketronShows you how the asset on the chart is trending versus the market. You can customise the market that it uses, and there are some common markets programmed in as options.
Displays moving averages and a simple red/green bias.
You could do this yourself by typing, e.g., ADAUSDT/TOTAL into the asset box in TradingView and adding some EMAs manually and then interpreting them by eye. There's no hidden technology in this indicator. It just makes it a lot easier.
You can choose various bias options.
I'm not sure if it will work at resolutions lower than one day, depending on the level of your TradingView plan.
These are all the user-configurable settings and what they do.
Market (Auto) – Choose from various preselected markets.
Market Ticker Manual Override – You can type in the ticker for your market if it's not in the list. If you do, it overrides the Auto list.
Show Classic EMAs – Show customisable Exponential Moving Averages.
Bias Mode – Derive the red/green bias from whether price is above/below the Classic EMAs, or from a custom EMA function, or both.
Show Bias Background – Colour the background, or not, with the directional bias.
EMA 1 Length (smallest) – The length for the smallest EMA.
EMA 2 Length – Length for the second EMA.
EMA 3 Length – Length for the third EMA.
Momentum PlayTraders always need a confirmation of momentum in price action to ride the swings.
Momentum Play Indicator consists of the below:
Bullish Conditions :
1)EMA 8 above EMA 34 and rising
2)Candle close above 5 candle high
3) RSI above 60
4) Volume above 5 candles avg. volume
5) ADX above 20
Bearish Conditions :
1)EMA 8 below EMA 34 and falling
2)Candle close below 5 candle low
3) RSI below 40
4) Volume above 5 candles avg. volume
5) ADX above 20
Traders can change the inputs as per their liking to adjust as per their comfortable timeframe.
Credits: Special Thanks to Mr. DTBHAT for sharing the above conditions.
Colorful Moving Averageswhat is Colorful Moving Averages?
This indicator allows you to use your favorite moving averages in their advanced form.
what it does?
It gives you easy access to the following information with a single indicator: the direction and momentum of the price,
rate of change of momentum (acceleration),
time-dependent change in momentum,
and all the other information a moving average provides.
it paints the selected moving average type according to the momentum it has, and also shows the momentum and acceleration values in a table. colors are interpreted as follows: the color of the moving average is red, the momentum is negative; A green color means the momentum is positive, and a yellow color means the momentum is 0. As the momentum changes, the moving average takes on different shades of these 3 colors. how it actually works can be easily understood at a glance.
"Δ" sign indicates momentum compressed between 100 and -100.
"Γ" sign indicates the momentum of the momentum, that is the acceleration. its values are compressed between 100 and -100.
how it does it?
it uses this formulas:
how to use it?
First, select the moving average type you want to use. then set the length and source. Now, with a single indicator, you can observe both the distance of the price from the mean, its instantaneous momentum relative to the last candle by looking at the symbol "Δ", the current change of momentum by looking at the symbol "Γ", and the time-dependent change in its momentum by looking at the colors. you can also see the maximum and minimum points where the momentum is equal to 0.
