MA Touch Alert SystemThis is a alert system This Pine Script creates an alert system in TradingView to notify you whenever the price touches a specified moving average. With adjustable settings, you can set your preferred moving average period, such as 50 or 200. The script calculates this moving average and triggers an alert if the price crosses it from above or below, enabling you to stay informed about important trend reversals. A visual on-chart label marks these points, and the alert condition ensures you receive notifications through TradingView. Perfect for traders looking to automate key level monitoring, this script supports trend-following and reversal strategies.
Double Exponential Moving Average (DEMA)
Dema Percentile Standard DeviationDema Percentile Standard Deviation
The Dema Percentile Standard Deviation indicator is a robust tool designed to identify and follow trends in financial markets.
How it works?
This code is straightforward and simple:
The price is smoothed using a DEMA (Double Exponential Moving Average).
Percentiles are then calculated on that DEMA.
When the closing price is below the lower percentile, it signals a potential short.
When the closing price is above the upper percentile and the Standard Deviation of the lower percentile, it signals a potential long.
Settings
Dema/Percentile/SD/EMA Length's: Defines the period over which calculations are made.
Dema Source: The source of the price data used in calculations.
Percentiles: Selects the type of percentile used in calculations (options include 60/40, 60/45, 55/40, 55/45). In these settings, 60 and 55 determine percentile for long signals, while 45 and 40 determine percentile for short signals.
Features
Fully Customizable
Fully Customizable: Customize colors to display for long/short signals.
Display Options: Choose to show long/short signals as a background color, as a line on price action, or as trend momentum in a separate window.
EMA for Confluence: An EMA can be used for early entries/exits for added signal confirmation, but it may introduce noise—use with caution!
Built-in Alerts.
Indicator on Diffrent Assets
INDEX:BTCUSD 1D Chart (6 high 56 27 60/45 14)
CRYPTO:SOLUSD 1D Chart (24 open 31 20 60/40 14)
CRYPTO:RUNEUSD 1D Chart (10 close 56 14 60/40 14)
Remember no indicator would on all assets with default setting so FAFO with setting to get your desired signal.
[Superior FSVZO] Advanced Stochastic RSI | viResearchAdvanced Stochastic RSI | viResearch
Conceptual Foundation and Innovation
The "Advanced Stochastic RSI" indicator from viResearch blends the principles of the Stochastic Oscillator and the Relative Strength Index (RSI), enhanced with smoothing via the Double Exponential Moving Average (DEMA). This combination offers traders a more refined and responsive tool for detecting potential trend reversals and assessing market momentum. The Stochastic Oscillator applied to the RSI allows for a detailed view of overbought and oversold conditions, while DEMA further smooths the data, reducing market noise. This integration results in a powerful tool for identifying key entry and exit points in the market based on momentum shifts.
By utilizing this advanced approach, the indicator gives traders more accurate signals for detecting price trends, particularly when traditional indicators may struggle with market noise and provide unreliable signals.
Technical Composition and Calculation
The "Advanced Stochastic RSI" indicator employs several key calculations to provide a comprehensive view of market momentum. The Double Exponential Moving Average (DEMA) is applied to the closing price to smooth fluctuations and provide a cleaner dataset. The RSI is then calculated on this smoothed price, which improves the accuracy of overbought and oversold signals. A for loop evaluates the RSI values between two user-defined thresholds to determine the overall market strength.
The Stochastic Oscillator is applied to this RSI-based system, calculating the %K line using a moving average, with the %D line as a further smoothing of the %K line. The crossing of these two lines serves as the primary signal for determining market entry and exit points. A positive crossing of %K above %D signals a potential upward trend, while a negative crossing of %K below %D suggests a possible downward trend.
Features and User Inputs
The "Advanced Stochastic RSI" script offers several customizable inputs, allowing traders to fine-tune the indicator’s sensitivity and behavior. The DEMA length defines the smoothing applied to the price data before calculating the RSI, which affects how responsive or smooth the indicator is. The RSI length determines the period over which the RSI is calculated, influencing the sensitivity of the momentum signals. The system’s for loop evaluates the RSI between two thresholds, providing a way to measure market strength over a defined range.
Additionally, the %K and %D smoothing controls the lengths of the Stochastic Oscillator’s %K and %D lines, adjusting the indicator’s responsiveness to changes in RSI. Traders can also adjust the bar color and set alert conditions for when the %K line crosses the %D line, allowing for real-time notifications of potential trading signals.
Practical Applications
The "Advanced Stochastic RSI" is designed for traders seeking a more nuanced approach to momentum analysis and trend detection. By combining the Stochastic Oscillator with the RSI, traders can more effectively identify overbought and oversold conditions, improving their timing for market entries and exits. This indicator is particularly useful for detecting reversals when the %K and %D lines cross, providing clear signals of potential trend reversals, especially when these crossovers occur in overbought or oversold zones.
The combination of DEMA and RSI confirms when the market is gaining or losing momentum, reducing the risk of false signals caused by short-term volatility. The ability to customize the indicator’s sensitivity through multiple inputs makes it adaptable for both short-term and long-term trading strategies, allowing traders to fine-tune the indicator to match their specific trading style.
Advantages and Strategic Value
The "Advanced Stochastic RSI" script offers significant value by combining three powerful elements—RSI, Stochastic Oscillator, and DEMA smoothing—into a single cohesive tool. This integration enhances the accuracy of trend detection by reducing noise while maintaining responsiveness to market movements. The ability to customize the inputs ensures that the indicator can be adjusted to suit different market environments, making it a versatile tool for traders at all levels.
By using the Stochastic RSI with an added smoothing layer, the indicator reduces the risk of whipsaw trades caused by market volatility, offering traders clearer signals for trend reversals and continuation patterns. This makes the "Advanced Stochastic RSI" a robust solution for identifying key momentum shifts.
Alerts and Visual Cues
The script includes alert conditions that notify traders of key trend shifts. A "Stochastic RSI Long" alert is triggered when the %K line crosses above the %D line, signaling a potential upward trend. A "Stochastic RSI Short" alert indicates a possible downward trend when the %K line crosses below the %D line. Additionally, the visual plot of the %K and %D lines, along with color-coded fill areas, provides clear cues for interpreting market conditions in real time.
Summary and Usage Tips
The "Advanced Stochastic RSI | viResearch" indicator provides traders with a powerful tool for analyzing market momentum and detecting potential reversals. By combining the strengths of the Stochastic Oscillator, RSI, and DEMA smoothing, this indicator improves the accuracy of trend detection and reduces the likelihood of false signals caused by market noise. Incorporating this script into your trading strategy can help enhance your timing of market entries and exits, offering a reliable and customizable solution for traders at all levels.
Note: Backtests are based on past results and are not indicative of future performance.
Dema EFI Volume | viResearchDema EFI Volume | viResearch
Conceptual Foundation and Innovation
The "Dema EFI Volume" indicator from viResearch integrates the Double Exponential Moving Average (DEMA) with the Elder Force Index (EFI), providing a dynamic approach to analyzing both price trends and volume strength. The DEMA is applied to smooth out price fluctuations while minimizing lag, which enhances the ability to detect trend direction. The EFI, developed by Dr. Alexander Elder, measures the power behind price movements by incorporating both price change and volume. This indicator, when combined with DEMA smoothing, gives traders a more accurate understanding of whether the current price movements are supported by significant volume, helping them make more informed trading decisions. The combination of DEMA and EFI allows traders to track trend strength while assessing the market’s volume dynamics, offering a more reliable method for identifying potential trend continuations or reversals.
Technical Composition and Calculation
The "Dema EFI Volume" script consists of two key components: the Double Exponential Moving Average (DEMA) and the Elder Force Index (EFI). The DEMA is applied to the selected source price over a user-defined length, providing a smoothed representation of price movements while reducing the noise that can occur with traditional moving averages. The EFI is calculated by multiplying the change in the DEMA by the volume over a user-defined period, which indicates whether the price movement is being driven by strong or weak volume. The script monitors the EFI values and volume data to generate trend signals. If the EFI is positive and volume increases, this indicates bullish pressure, while a negative EFI with decreasing volume suggests bearish conditions. The combination of these signals helps traders determine whether a price move is backed by sufficient volume, making it easier to identify trend continuations or potential reversals.
Features and User Inputs
The "Dema EFI Volume" script offers several customizable inputs, allowing traders to adapt the indicator to their specific strategies. The DEMA Length controls the smoothing applied to the price data, while the EFI Length defines the period over which the force index is calculated. Additionally, traders can set alert conditions for when a bullish or bearish EFI signal occurs, enabling them to react quickly to changing market conditions.
Practical Applications
The "Dema EFI Volume" indicator is designed for traders who want to combine price trend analysis with volume dynamics in a single tool. This makes it particularly effective for identifying trend continuations, as rising volume alongside a positive EFI suggests that the market move is supported by strong momentum. Conversely, decreasing volume and a negative EFI may indicate a weakening trend, giving traders early warning of potential reversals. The combination of DEMA and EFI also makes this indicator valuable for detecting trend strength by measuring whether price movements are backed by strong volume, confirming trend reversals by comparing price changes with volume activity, and improving trade entries and exits by analyzing both price and volume for more robust signals.
Advantages and Strategic Value
The "Dema EFI Volume" script offers significant advantages by combining the DEMA’s smoothing power with the EFI’s volume analysis. This integration allows traders to filter out noise in price data while ensuring that trend signals are backed by meaningful volume. The result is a more reliable tool for trend-following and reversal detection, making it easier for traders to stay aligned with strong market moves while avoiding false signals caused by low-volume fluctuations. The dual focus on price and volume makes the "Dema EFI Volume" an ideal tool for traders who value a comprehensive approach to market analysis.
Alerts and Visual Cues
The script includes alert conditions that notify traders when a significant EFI signal occurs. The "EFI Volume Long" alert is triggered when the EFI is positive and volume increases, indicating a potential upward trend. The "EFI Volume Short" alert signals a possible downward trend when the EFI turns negative and volume decreases. Visual cues, such as the color and direction of the plotted EFI line, help traders quickly identify trend shifts and make timely decisions.
Summary and Usage Tips
The "Dema EFI Volume | viResearch" indicator provides traders with a powerful tool for analyzing both price trends and volume strength. By incorporating this script into your trading strategy, you can improve your ability to detect trend continuations and reversals, making more informed decisions based on a combination of price movement and volume dynamics. Whether you are focused on identifying trend strength or looking for early reversal signals, the "Dema EFI Volume" offers a reliable and customizable solution for traders of all levels.
Note: Backtests are based on past results and are not indicative of future performance.
Dema DMI | viResearchDema DMI | viResearch
Conceptual Foundation and Innovation
The "Dema DMI" indicator integrates the Double Exponential Moving Average (DEMA) with the Directional Movement Index (DMI), creating a more responsive and precise trend-following system. The DEMA is used to smooth price data while minimizing lag, making it highly effective for trend detection. The DMI, on the other hand, measures the strength and direction of a trend by analyzing positive and negative directional movements. By combining these two elements, the "Dema DMI" offers traders a powerful tool for identifying trend changes and evaluating the strength of ongoing trends. This combination helps filter out noise in price data while maintaining sensitivity to market movements, providing better trend signals and decision-making opportunities.
Technical Composition and Calculation
The "Dema DMI" script uses two main components: the Double Exponential Moving Average (DEMA) and the Directional Movement Index (DMI). The DEMA is applied to both the high and low prices, creating smoothed versions of these prices based on a user-defined length. The DMI is then calculated by comparing changes in the smoothed high and low prices to measure directional movement. Positive directional movement (DM+) and negative directional movement (DM−) are calculated by evaluating whether the price is trending upward or downward, and the Average Directional Index (ADX) is computed to measure the strength of the trend. The ADX is smoothed to provide a more stable signal of trend strength.
Features and User Inputs
The "Dema DMI" script provides several customizable inputs, enabling traders to tailor the indicator to their strategies. The DEMA Length controls the period over which the DEMA is calculated for both high and low prices. The DMI Length sets the window for calculating directional movement, while the ADX Smoothing Length determines how smooth the ADX line appears, making it easier to assess whether a trend is strengthening or weakening. The script also includes customizable bar colors and alert conditions, providing traders with clear visual cues and notifications when a trend change occurs.
Practical Applications
The "Dema DMI" indicator is designed for traders looking to assess trend strength and direction more effectively. The DEMA smooths price movements, while the DMI highlights shifts in directional movement, providing early signals of potential trend reversals. The ADX helps gauge whether a trend is gaining momentum, allowing traders to improve the timing of trade entries and exits. Additionally, the customizable inputs make the indicator adaptable to different market conditions, ensuring its usefulness in both trending and ranging environments.
Advantages and Strategic Value
The "Dema DMI" script offers significant value by merging the smoothing effects of DEMA with the directional analysis of the DMI. This combination reduces the lag commonly associated with trend-following indicators, providing more timely and accurate trend signals. The ADX further enhances the indicator’s utility by measuring the strength of the trend, helping traders filter out weak signals and stay aligned with stronger trends. This makes the "Dema DMI" an ideal tool for traders seeking to improve their trend-following strategies and optimize their market positioning.
Alerts and Visual Cues
The script includes alert conditions that notify traders when a significant trend change occurs. The "Dema DMI Long" alert is triggered when the indicator detects an upward trend, while the "Dema DMI Short" alert signals a potential downward trend. Visual cues, such as changes in the bar color and the difference between positive and negative directional movement, help traders quickly identify trend shifts and act accordingly.
Summary and Usage Tips
The "Dema DMI | viResearch" indicator combines the smoothing benefits of the DEMA with the directional analysis of the DMI, providing traders with a reliable tool for detecting trend changes and confirming trend strength. By incorporating this script into your trading strategy, you can improve your ability to detect early trend reversals, confirm trend direction, and reduce noise in price data. The "Dema DMI" is a flexible and adaptable solution for traders looking to enhance their technical analysis in various market conditions.
Note: Backtests are based on past results and are not indicative of future performance.
Dema AFR | viResearchDema AFR | viResearch
Conceptual Foundation and Innovation
The "Dema AFR" indicator combines the Double Exponential Moving Average (DEMA) with an Average True Range (ATR)-based adaptive factor to create a responsive and adaptable trend-following system. The DEMA is known for its ability to smooth price data while reducing lag, making it highly effective for trend detection. By incorporating the ATR as a volatility factor, this indicator adapts dynamically to market conditions, allowing traders to capture trends while accounting for changes in volatility. The result is the Adaptive Factor Range (AFR), which provides clear signals for potential trend shifts and helps manage risk through its adaptive nature. This combination of DEMA smoothing and an ATR-based factor enables traders to follow trends more effectively while maintaining sensitivity to changing market conditions.
Technical Composition and Calculation
The "Dema AFR" script consists of two main components: the Double Exponential Moving Average (DEMA) and the Adaptive Factor Range (AFR). The DEMA is calculated over a user-defined length, smoothing out price fluctuations while reducing lag compared to traditional moving averages. The ATR is used to create a dynamic factor that adjusts the AFR based on market volatility. The factor is calculated by multiplying the ATR by a user-defined factor value, which scales the ATR to define upper and lower bounds for the AFR. The Adaptive Factor Range is derived from the DEMA, with upper and lower bounds set by adding or subtracting the ATR-based factor from the DEMA. When the price moves outside these bounds, the AFR is adjusted, and signals are generated. If the lower bound is exceeded, the AFR adjusts upward, while exceeding the upper bound causes the AFR to adjust downward. This dynamic adjustment helps the indicator stay responsive to market movements.
Features and User Inputs
The "Dema AFR" script provides several customizable inputs, allowing traders to tailor the indicator to their strategies. The DEMA Length controls the smoothing period for the DEMA, while the ATR Period defines the window for calculating the Average True Range. The ATR Factor determines the scale of the adaptive factor, controlling how much the AFR adjusts to volatility. Additionally, customizable bar colors and alert conditions allow traders to visualize the trend direction and receive notifications when key trend shifts occur.
Practical Applications
The "Dema AFR" indicator is designed for traders who want to capture trends while adapting to market volatility. The adaptive nature of the AFR makes it responsive to trend changes, providing early signals of potential trend reversals as the AFR adjusts to market movements. By incorporating ATR into the AFR calculation, the indicator adjusts to changing volatility, helping traders manage risk by staying aligned with market conditions. The AFR also helps confirm whether a price move is supported by momentum, improving the accuracy of trade entries and exits.
Advantages and Strategic Value
The "Dema AFR" script offers a significant advantage by combining the smoothness of the DEMA with the adaptability of the ATR-based factor. This dynamic combination allows the indicator to adjust to market conditions, providing more reliable trend signals in both trending and volatile markets. The adaptive nature of the AFR reduces the risk of false signals and helps traders stay on the right side of the trend while managing risk through volatility-adjusted ranges.
Alerts and Visual Cues
The script includes alert conditions that notify traders of key trend changes. The "Dema AFR Long" alert is triggered when the AFR indicates a potential upward trend, while the "Dema AFR Short" alert signals a potential downward trend. Visual cues such as color changes in the bar chart help traders quickly identify shifts in trend direction, allowing them to make informed decisions in real time.
Summary and Usage Tips
The "Dema AFR | viResearch" indicator provides traders with a powerful tool for trend analysis by combining DEMA smoothing with an ATR-based adaptive factor. This script helps traders stay aligned with trends while accounting for market volatility, improving their ability to detect trend reversals and manage risk. By incorporating this indicator into your trading strategy, you can make more informed decisions, whether in trending or volatile market environments. The "Dema AFR" offers a reliable and flexible solution for traders at all levels.
Note: Backtests are based on past results and are not indicative of future performance.
Dema Ema Crossover | viResearchDema Ema Crossover | viResearch
Conceptual Foundation and Innovation
The "Dema Ema Crossover" indicator combines the strengths of the Double Exponential Moving Average (DEMA) with an Exponential Moving Average (EMA) crossover strategy. The DEMA is well-known for its ability to reduce lag compared to standard moving averages, offering smoother trend-following signals. In this script, the DEMA is used as the foundation, with two EMAs applied on top of it to further refine the trend detection and crossover points. This combination provides traders with a robust tool for identifying trend shifts and potential entry or exit points.
By leveraging the faster responsiveness of the DEMA and using EMA crossovers, the "Dema Ema Crossover" indicator helps traders detect and act on trend reversals more efficiently, making it a powerful solution for capturing both short- and long-term market movements.
Technical Composition and Calculation
The "Dema Ema Crossover" script consists of three main components: the Double Exponential Moving Average (DEMA), the fast EMA, and the slow EMA. The DEMA is calculated based on the selected length and source price, providing a smooth representation of market trends. Two EMAs are then applied to the DEMA, with one being faster (shorter period) and the other slower (longer period). The crossover between these two EMAs generates the signals for trend changes.
For the DEMA, the calculation uses the ta.dema function, which reduces lag while maintaining smoothness in the moving average. The fast and slow EMAs are calculated using the ta.ema function, with the fast EMA responding more quickly to price changes, while the slow EMA captures broader trends. The crossover between these two EMAs is used to generate buy and sell signals based on the direction of the crossover.
Features and User Inputs
The "Dema Ema Crossover" script offers several customizable inputs that allow traders to tailor the indicator to their trading strategies. The DEMA Length controls how smooth the DEMA is, with a longer length creating a slower-moving average and a shorter length providing a more responsive one. The Fast EMA Length and Slow EMA Length are also customizable, allowing traders to adjust the sensitivity of the crossover signals based on their market outlook and preferred trading timeframe.
Practical Applications
The "Dema Ema Crossover" indicator is designed for traders looking for a reliable crossover strategy that combines the responsiveness of the DEMA with the precision of EMA crossovers. This tool is particularly effective for:
Identifying Trend Reversals: The crossover between the fast and slow EMAs applied to the DEMA provides early signals of potential trend reversals, allowing traders to position themselves in the market more effectively. Confirming Trend Direction: The combined effect of the DEMA and EMA crossovers helps confirm the strength of a trend, improving decision-making around trade entries and exits. Adapting to Different Market Conditions: The customizable parameters allow traders to adjust the sensitivity of the crossover signals, making the indicator suitable for both fast-moving markets and slower, trending environments.
Advantages and Strategic Value
The "Dema Ema Crossover" script offers a significant advantage by combining the smoothness of the DEMA with the accuracy of EMA crossovers. The DEMA’s ability to reduce lag while maintaining responsiveness makes it ideal for trend-following strategies, while the crossover between the fast and slow EMAs provides precise entry and exit points. This combination reduces false signals and helps traders adapt to changing market conditions, resulting in a more reliable and efficient trend-following system.
Alerts and Visual Cues
The script includes alert conditions to notify traders of key crossover events. The "Dema Ema Crossover Long" alert is triggered when the fast EMA crosses above the slow EMA, signaling a potential upward trend. Conversely, the "Dema Ema Crossover Short" alert signals a possible downward trend when the fast EMA crosses below the slow EMA. Visual cues such as colored fills between the two EMAs highlight these crossover points on the chart, helping traders quickly identify trend shifts.
Summary and Usage Tips
The "Dema Ema Crossover | viResearch" indicator provides traders with a powerful combination of the DEMA and EMA crossovers, offering a smooth yet responsive tool for detecting trend reversals and confirming trend direction. By incorporating this script into your trading strategy, you can improve your ability to capture trend changes with greater accuracy, reducing the impact of market noise. Whether you are focused on short-term market moves or long-term trends, the "Dema Ema Crossover" indicator offers a flexible and reliable solution for traders at all levels.
Note: Backtests are based on past results and are not indicative of future performance.
Dema Vstop | viResearchTitle: Dema Vstop | viResearch
Conceptual Foundation and Innovation
The "Dema Vstop" indicator combines the Double Exponential Moving Average (DEMA) with the Volatility Stop (Vstop) concept to improve trend-following and trend-reversal signals. This script provides a more responsive and dynamic approach to identifying trends and capturing market movements by integrating these two powerful tools. It is particularly effective for traders who seek a balance between smoothing out price action and quickly adapting to volatile changes in the market.
The DEMA smooths the price action more effectively than a traditional moving average, while the Vstop introduces a volatility-adjusted stop-loss mechanism, allowing traders to adapt to the market's changing conditions. The result is a robust system that captures both trend direction and potential reversal points with improved precision.
Technical Composition and Calculation
At the core of the "Dema Vstop" script are two primary components:
Double Exponential Moving Average (DEMA): This is used to smooth the source price over a user-defined period (dema_len), making it ideal for trend identification.
Volatility Stop (Vstop): The Vstop mechanism uses the Average True Range (ATR) to adjust stop-loss levels based on market volatility, allowing the indicator to account for changes in market conditions.
Key Calculations:
DEMA Calculation: Based on the selected length and source, the DEMA smooths the price data.
Vstop Calculation: The ATR (with customizable length) is used to adjust the stop distance, and the Vstop level is calculated based on whether the price is trending up or down.
Features and User Inputs
The "Dema Vstop" script offers a high degree of customization:
DEMA Length and Source: Control the smoothness of the DEMA and the price data being smoothed.
Vstop Length: Customize the length of the ATR calculation to control how reactive the Vstop is to price volatility.
Multiplier: Adjust the sensitivity of the Vstop to market volatility. A higher multiplier results in a wider stop, while a lower multiplier tightens the stop, making it more sensitive to price changes.
Practical Applications
The "Dema Vstop" is designed for traders looking for a hybrid trend-following system that is both smooth and responsive. It can be particularly useful for:
Identifying Trends: The combination of DEMA and Vstop makes trend-following easier, helping traders stay in profitable positions longer.
Volatility Protection: The Vstop dynamically adjusts based on market volatility, providing a built-in risk management tool that reduces exposure to volatile markets.
Reversals and Entries: The Vstop helps identify potential reversals by flipping its stop level when the trend direction changes, making it effective for signaling entries and exits with improved accuracy.
Advantages and Strategic Value
The key advantage of the "Dema Vstop" script lies in its ability to offer smoother trend detection through the DEMA while dynamically adapting to volatility using the Vstop. This combination reduces false signals, providing traders with a more stable and reliable tool for trend trading. Additionally, the customizable parameters allow traders to fine-tune the indicator to suit different trading styles and market conditions.
Alerts and Visual Cues
The script comes with built-in alert conditions that trigger when a trend shift is detected:
- Dema Vstop Long: Signals a potential upward trend.
- Dema Vstop Short: Signals a potential downward trend.
These alerts ensure that traders can stay informed about critical market changes without constantly monitoring the chart.
Summary and Usage Tips
The "Dema Vstop | viResearch" script is an innovative trend-following tool that combines the smoothness of DEMA with the adaptive qualities of Vstop. By offering a customizable and dynamic system, this indicator helps traders navigate the complexities of volatile markets while reducing noise and false signals. Incorporating this script into your trading strategy can improve trend analysis and increase the accuracy of entries and exits.
Note: Backtests are based on past results and are not indicative of future performance.
Dema Supertrend | viResearchDema Supertrend | viResearch
Conceptual Foundation and Innovation
The "Dema Supertrend" indicator by viResearch combines the benefits of the Double Exponential Moving Average (DEMA) with the popular Supertrend method to provide an advanced tool for trend detection and volatility management. By integrating DEMA into the Supertrend calculation, the indicator reduces lag while enhancing responsiveness to market changes. This results in more accurate trend identification and a refined method for capturing directional movements.
Technical Composition and Calculation
The "Dema Supertrend" builds on the core principles of the Supertrend indicator by incorporating DEMA for smoother and more responsive trend detection. The key innovation lies in replacing the raw price data with the DEMA-smoothed values, allowing traders to identify trends with reduced noise and enhanced precision.
DEMA and ATR-Based Supertrend Calculation:
DEMA Calculation (demalen): The Double Exponential Moving Average is applied to the price data (hlc3 by default) over a user-defined length, providing a smoothed representation of the market trend. DEMA minimizes lag compared to simple or exponential moving averages, allowing for more timely trend identification.
Supertrend Bands (u, l): The Supertrend upper and lower bands are calculated by adding or subtracting a multiple of the Average True Range (ATR) from the DEMA value. These bands dynamically adjust to market volatility, acting as support and resistance levels to guide trading decisions.
Trend Logic (L, S): The script determines whether the price is above or below the bands to signal an uptrend (L) or downtrend (S). Crosses above or below these bands trigger visual alerts and trend changes, with alerts built in for potential long or short positions.
Trend Continuation and Reversal:
The indicator ensures that once a trend is identified, it persists until clear reversal criteria are met. This is achieved through a comparison of the current and previous values of the Supertrend bands, reducing the occurrence of false signals in volatile markets.
Features and User Inputs
The "Dema Supertrend" script offers a range of customizable options, allowing traders to tailor the indicator to different market conditions and trading strategies:
Supertrend Length: The length of the Supertrend period can be adjusted, allowing traders to control the sensitivity of the trend detection.
Multiplier: The ATR multiplier adjusts the distance between the DEMA and the Supertrend bands. A higher multiplier reduces the frequency of trend changes, while a lower multiplier increases sensitivity to price movements.
DEMA Length: The length of the DEMA calculation can be customized to smooth price data over different timeframes, helping traders capture long-term trends or short-term movements more effectively.
Practical Applications
The "Dema Supertrend" is an ideal tool for traders who seek to follow trends while minimizing the impact of market noise. Its combination of DEMA and Supertrend provides a clear, dynamic view of the market's direction, making it especially effective in volatile environments.
Key Uses:
- Trend Following: The Dema Supertrend helps traders align their positions with the prevailing market trend by providing clear signals for uptrends and downtrends based on DEMA-smoothened price action.
- Volatility Management: The integration of ATR ensures that the Supertrend bands adapt to changes in market volatility, allowing traders to avoid entering trades during choppy, unpredictable price movements.
- Signal Confirmation: The script includes visual and alert-based signals for trend continuation and reversal, enabling traders to confirm entries and exits with greater accuracy.
Advantages and Strategic Value
The "Dema Supertrend" offers several strategic advantages:
- Reduced Lag: By integrating DEMA into the Supertrend calculation, the indicator responds more quickly to price changes, reducing the lag inherent in traditional moving averages.
- Noise Reduction: The use of DEMA filters out short-term fluctuations, providing a clearer signal for traders looking to capture significant market trends.
- Dynamic Adjustments: The combination of ATR and DEMA allows the indicator to adapt to both trending and ranging markets, making it suitable for a variety of trading strategies.
Summary and Usage Tips
The "Dema Supertrend" is a powerful tool for trend-following traders, offering a precise and adaptive method for identifying and confirming market direction. Traders can experiment with different settings for the Supertrend and DEMA lengths, as well as the ATR multiplier, to optimize the indicator for various trading environments. For best results, use the "Dema Supertrend" in conjunction with other technical analysis tools to confirm trends and manage risk. Whether you're seeking to capture long-term market moves or react to short-term volatility, the "Dema Supertrend" provides a reliable and flexible solution for your trading strategy.
Inverted SD Dema RSI | viResearchInverted SD Dema RSI | viResearch
The "Inverted SD Dema RSI" developed by viResearch introduces a new approach to trend analysis by combining the Double Exponential Moving Average (DEMA), Standard Deviation (SD), and Relative Strength Index (RSI). This unique indicator provides traders with a tool to capture market trends by integrating volatility-based thresholds. By using the smoothed DEMA along with standard deviation, the indicator offers improved responsiveness to price fluctuations, while RSI thresholds offer insight into overbought and oversold market conditions.
At the core of the "Inverted SD Dema RSI" is the combination of DEMA and standard deviation for a more nuanced view of market volatility. The use of RSI further aids in detecting price extremes and potential trend reversals.
DEMA Calculation (sublen): The Double Exponential Moving Average (DEMA) smoothes out price data over a user-defined period, reducing lag compared to traditional moving averages. This provides a clearer representation of the market's overall direction.
Standard Deviation Calculation (sublen_2): The standard deviation of the DEMA is used to define the upper (u) and lower (d) bands, highlighting areas where price volatility may signal a change in trend. These dynamic bands help traders gauge price volatility and potential breakouts or breakdowns.
RSI Calculation (len): The script applies the Relative Strength Index (RSI) to the smoothed DEMA values, allowing traders to detect momentum shifts based on a modified data set. This provides a more accurate reflection of market strength when combined with the DEMA.
Thresholds: The RSI is compared to user-defined thresholds (70 for overbought and 55 for oversold conditions). These thresholds help in identifying potential market reversals, especially when the price breaks outside of the calculated standard deviation bands.
Uptrend (L): An uptrend signal is generated when the RSI exceeds the upper threshold (70) and the price is not above the upper standard deviation band, indicating that there may be room for further price appreciation.
Downtrend (S): A downtrend signal occurs when the RSI falls below the lower threshold (55), indicating that the price may continue to decline.
The "Inverted SD Dema RSI" offers a wide range of customizable settings, allowing traders to adjust the indicator based on their trading style or market conditions.
DEMA Length (sublen): Controls the period used to smooth the price data, impacting the sensitivity of the DEMA to recent price movements.
Standard Deviation Length (sublen_2): Defines the length over which the standard deviation is calculated, helping traders control the width of the upper and lower bands.
RSI Length (len): Adjusts the period used for the RSI calculation, providing flexibility in determining overbought and oversold conditions.
RSI Thresholds: Traders can define their own levels for detecting trend reversals, with default values of 70 for an uptrend and 55 for a downtrend.
The "Inverted SD Dema RSI" is particularly well-suited for traders looking to capture trends while accounting for volatility and momentum. By using a smoothed DEMA as the foundation, it effectively filters out noise, making it ideal for detecting reliable trends in volatile markets.
Key Uses:
Trend Following: The indicator’s combination of DEMA, standard deviation, and RSI helps traders follow trends more effectively by reducing noise and identifying key momentum shifts.
Volatility Filtering: The use of standard deviation bands provides a dynamic measure of volatility, ensuring that traders are aware of potential breakouts or breakdowns in the market.
Momentum Detection: The inclusion of RSI ensures that the indicator is not only focused on trend direction but also on the strength of the underlying momentum, helping traders avoid entering trades during weak trends.
The "Inverted SD Dema RSI" provides several key advantages over traditional trend-following indicators:
Reduced Lag: The use of DEMA ensures faster trend detection, reducing the lag associated with simple moving averages.
Noise Reduction: The integration of standard deviation helps filter out irrelevant price movements, making it easier to identify significant trends.
Momentum Awareness: The addition of RSI provides valuable insight into the strength of trends, helping traders avoid false signals during periods of weak momentum.
The "Inverted SD Dema RSI" offers a powerful blend of trend-following and momentum detection, making it a versatile tool for modern traders. By integrating DEMA, standard deviation, and RSI, the indicator provides a comprehensive view of market trends and volatility. Traders are encouraged to experiment with different settings for the DEMA length, standard deviation, and RSI thresholds to fine-tune the indicator for their specific trading strategies. Whether used for trend confirmation, volatility assessment, or momentum analysis, the "Inverted SD Dema RSI" offers a valuable tool for traders seeking a comprehensive approach to market analysis.
Median Standard Deviation | viResearchMedian Standard Deviation | viResearch
The "Median Standard Deviation" indicator, developed by viResearch, introduces a unique combination of median smoothing and standard deviation to detect trends and volatility in market data. This tool provides traders with a stable and accurate measure of price trends by integrating median smoothing with a customized calculation of the standard deviation. This innovative approach allows for enhanced sensitivity to market fluctuations while filtering out short-term price noise.
Technical Composition and Calculation:
The "Median Standard Deviation" indicator incorporates median smoothing and dynamic standard deviation calculations to build upon traditional volatility measures.
Median Smoothing:
DEMA Calculation (len_dema): The script applies a Double Exponential Moving Average (DEMA) to smooth the price data over a user-defined period, reducing noise and helping traders focus on broader market trends.
Median Calculation (median_len): The smoothed DEMA data is further refined by calculating the 50th percentile (median) over a specified length, ensuring that the central tendency of price data is captured more accurately than with a simple moving average.
Volatility Measurement:
ATR Calculation (atr_len, atr_mul): The script incorporates the Average True Range (ATR) to measure market volatility. The user-defined ATR multiplier is applied to this value to calculate upper and lower trend bands around the median, providing a dynamic measure of potential price movement based on recent volatility.
Standard Deviation Analysis:
Standard Deviation Calculation (len_sd): The script calculates the standard deviation of the median over a user-defined length, providing another layer of volatility measurement. The upper and lower standard deviation bands (sdd, sdl) act as additional indicators of price extremes.
Trend Detection:
Trend Logic: The indicator uses the calculated bands to identify whether the price is moving within or outside the standard deviation and ATR bands. Crosses above or below these bands are used to signal potential uptrends or downtrends, offering traders a clear view of market direction.
Features and User Inputs:
The "Median Standard Deviation" script offers a variety of user inputs to customize the indicator to suit traders' styles and market conditions:
DEMA Length: Allows traders to adjust the sensitivity of the DEMA smoothing to control the amount of noise filtered from the price data.
Median Length: Users can define the length over which the median price is calculated, providing flexibility in capturing short-term or long-term trends.
ATR Length and Multiplier: These inputs let traders fine-tune the ATR calculation, affecting the size of the dynamic upper and lower bands.
Standard Deviation Length: Controls how the standard deviation is calculated, allowing for further customization in detecting price volatility.
Practical Applications:
The "Median Standard Deviation" indicator is particularly effective in volatile markets where price swings can lead to false signals using traditional methods. By combining median smoothing and standard deviation, this tool provides a more robust analysis of trends and price movements.
Key Uses:
Trend Following: The upper and lower bands provide clear signals for entering and exiting trades based on whether the price is moving outside the calculated ranges.
Volatility Detection: The integration of ATR and standard deviation bands allows traders to assess market volatility in real time, enabling more informed trading decisions.
Noise Reduction: The use of median smoothing ensures that short-term price fluctuations do not interfere with broader trend analysis, making this indicator ideal for traders looking to avoid whipsaws in volatile markets.
Advantages and Strategic Value:
The "Median Standard Deviation" indicator offers several key advantages:
Precision in Trend Detection: The combination of median smoothing and standard deviation allows traders to detect trends with greater accuracy, reducing the risk of false signals.
Customization: With several adjustable parameters, traders can fine-tune the indicator to suit different timeframes and trading strategies.
Volatility Sensitivity: By incorporating ATR and standard deviation, this indicator provides an adaptive measure of market volatility, ensuring that traders are always aware of potential price swings.
Summary and Usage Tips:
The "Median Standard Deviation" indicator is a powerful tool for traders looking to refine their analysis of market trends and volatility. Its combination of median smoothing and standard deviation provides a nuanced view of market movements, helping traders make better-informed decisions. It's recommended to experiment with the various input parameters to optimize the indicator for specific needs, whether used for trend detection, volatility analysis, or noise reduction. The "Median Standard Deviation" offers a reliable and adaptable solution for modern trading strategies.
Please keep in mind the following text: Backtests are based on past results and are not indicative of future performance.
No-Lag MA Crossover ScalperThe No Lag Crossover Scalper aims to capitalize on short-term trends using a combination of Hull Moving Average (HMA) for trend detection and multiple indicators for generating buy and sell signals. Here’s an overview of its components and approach:
1. Trend Detection with Hull Moving Averages (HMA) :
- Dual Hull MA Setup : Uses two Hull Moving Averages (HMA) to detect crossovers and crossunders, which are signals of short-term trend changes.
- No Lag Nature : HMAs are chosen for their ability to reduce lag compared to traditional moving averages, providing quicker responses to price movements.
2. Indicators for Signal Generation :
- Relative Strength Index (RSI) : Detects overbought and oversold conditions, generating signals when price movements diverge from RSI readings.
- Moving Average Convergence Divergence (MACD) : Provides signals based on the convergence and divergence of two moving averages, indicating potential trend reversals.
- Stochastic Oscillator (Stoch) : Identifies momentum shifts by comparing the current closing price to its range over a specific period.
- On-Balance Volume (OBV) : Measures buying and selling pressure based on volume flow, signaling potential changes in price direction.
- RSI Divergence : Looks for discrepancies between price action and RSI values, suggesting weakening trends and possible reversals.
3. Signal Generation Logic :
- Buy Signals : Generated when both HMAs cross over, supported by bullish indications from RSI, MACD, Stoch, OBV, or RSI divergence. At least 2 indicators must be true to generate a signal.
- Sell Signals : Triggered when HMAs cross under, complemented by bearish signals from the mentioned indicators.
4. Implementation and Optimization :
- Parameter Optimization : Fine-tuning of indicator periods and sensitivity settings to balance signal accuracy and responsiveness.
- Confirmation Mechanisms : Use of multiple indicators to confirm signals, reducing false positives and enhancing reliability.
Overall, the No Lag Crossover Scalper combines the speed of Hull Moving Averages with the reliability of multiple indicators to identify short-term trends effectively. By focusing on no lag indicators and confirming signals with diverse technical tools, it aims to capitalize on rapid market movements while managing risk through disciplined execution.
Credits: used TradingView ta library for a lot of the built-in indicators.
Disclaimer: This is still experimental beta version so use at your own risk.
Simplified MA Crossover indicatorThis is my first script, it is really simple logic and you probably saw something similar before. Is a crossover indicator between 2 Moving Average, one fast MA and the second slow MA.
Inputs you can adjust:
- 8 different source of MA's
- lenght of the MA's
- 7 different types of MA's ("EMA", "SMA", "RMA", "WMA", "DEMA", "TEMA", "HMA")
- 3 smoothing level of the fast MA
- plotting fast MA into the chart
- plotting crossover triangle shapes
I really enjoed the creation of this simple concept indicator, maybe not the fastest because of his nature but I liked work on it. I am sure is a good base to improve, study and try new idea.
Volatility Adjusted Weighted DEMA [BackQuant]Volatility Adjusted Weighted DEMA
The Volatility Adjusted Weighted Double Exponential Moving Average (VAWDEMA) by BackQuant is a sophisticated technical analysis tool designed for traders seeking to integrate volatility into their moving average calculations. This innovative indicator adjusts the weighting of the Double Exponential Moving Average (DEMA) according to recent volatility levels, offering a more dynamic and responsive measure of market trends.
Primarily, the single Moving average is very noisy, but can be used in the context of strategy development, where as the crossover, is best used in the context of defining a trading zone/ macro uptrend on higher timeframes.
Why Volatility Adjustment is Beneficial
Volatility is a fundamental aspect of financial markets, reflecting the intensity of price changes. A volatility adjustment in moving averages is beneficial because it allows the indicator to adapt more quickly during periods of high volatility, providing signals that are more aligned with the current market conditions. This makes the VAWDEMA a versatile tool for identifying trend strength and potential reversal points in more volatile markets.
Understanding DEMA and Its Advantages
DEMA is an indicator that aims to reduce the lag associated with traditional moving averages by applying a double smoothing process. The primary benefit of DEMA is its sensitivity and quicker response to price changes, making it an excellent tool for trend following and momentum trading. Incorporating DEMA into your analysis can help capture trends earlier than with simple moving averages.
The Power of Combining Volatility Adjustment with DEMA
By adjusting the weight of the DEMA based on volatility, the VAWDEMA becomes a powerful hybrid indicator. This combination leverages the quick responsiveness of DEMA while dynamically adjusting its sensitivity based on current market volatility. This results in a moving average that is both swift and adaptive, capable of providing more relevant signals for entering and exiting trades.
Core Logic Behind VAWDEMA
The core logic of the VAWDEMA involves calculating the DEMA for a specified period and then adjusting its weighting based on a volatility measure, such as the average true range (ATR) or standard deviation of price changes. This results in a weighted DEMA that reflects both the direction and the volatility of the market, offering insights into potential trend continuations or reversals.
Utilizing the Crossover in a Trading System
The VAWDEMA crossover occurs when two VAWDEMAs of different lengths cross, signaling potential bullish or bearish market conditions. In a trading system, a crossover can be used as a trigger for entry or exit points:
Bullish Signal: When a shorter-period VAWDEMA crosses above a longer-period VAWDEMA, it may indicate an uptrend, suggesting a potential entry point for a long position.
Bearish Signal: Conversely, when a shorter-period VAWDEMA crosses below a longer-period VAWDEMA, it might signal a downtrend, indicating a possible exit point or a short entry.
Incorporating VAWDEMA crossovers into a trading strategy can enhance decision-making by providing timely and adaptive signals that account for both trend direction and market volatility. Traders should combine these signals with other forms of analysis and risk management techniques to develop a well-rounded trading strategy.
Alert Conditions For Trading
alertcondition(vwdema>vwdema , title="VWDEMA Long", message="VWDEMA Long - {{ticker}} - {{interval}}")
alertcondition(vwdema<vwdema , title="VWDEMA Short", message="VWDEMA Short - {{ticker}} - {{interval}}")
alertcondition(ta.crossover(crossover, 0), title="VWDEMA Crossover Long", message="VWDEMA Crossover Long - {{ticker}} - {{interval}}")
alertcondition(ta.crossunder(crossover, 0), title="VWDEMA Crossover Short", message="VWDEMA Crossover Short - {{ticker}} - {{interval}}")
Thus following all of the key points here are some sample backtests on the 1D Chart
Disclaimer: Backtests are based off past results, and are not indicative of the future.
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
DEMA RSI Overlay [BackQuant]DEMA RSI Overlay
PLEASE Read the following, knowing what an indicator does at its core before adding it into a system is pivotal. The core concepts can allow you to include it in a logical and sound manner.
Anyways,
BackQuant's new trading indicator that blends the Double Exponential Moving Average (DEMA) with the Relative Strength Index (RSI) to create a unique overlay on the trading chart. This combination is not arbitrary; both the DEMA and RSI are revered for their distinct advantages in trading strategy development. Let's delve into the core components of this script, the rationale behind choosing DEMA and RSI, the logic of long and short signals, and its practical trading applications.
Understanding DEMA
DEMA is an enhanced version of the conventional exponential moving average that aims to reduce the lag inherent in traditional averages. It does this by applying more weight to recent prices. The reduction in lag makes DEMA an excellent tool for tracking price trends more closely. In the context of this script, DEMA serves as the foundation for the RSI calculation, offering a smoother and more responsive signal line that can provide clearer trend indications.
Why DEMA?
DEMA is chosen for its responsiveness to price changes. This characteristic is particularly beneficial in fast-moving markets where entering and exiting positions quickly is crucial. By using DEMA as the price source, the script ensures that the signals generated are timely and reflective of the current market conditions, reducing the risk of entering or exiting a trade based on outdated information.
Integrating RSI
The RSI, a momentum oscillator, measures the speed and change of price movements. It oscillates between zero and 100 and is typically used to identify overbought or oversold conditions. In this script, the RSI is calculated based on DEMA, which means it inherits the responsiveness of DEMA, allowing traders to spot potential reversals or continuation signals sooner.
Why RSI?
Incorporating RSI offers a measure of price momentum and market conditions relative to past performance. By setting thresholds for long (buy) and short (sell) signals, the script uses RSI to identify potential turning points in the market, providing traders with strategic entry and exit points.
Calculating Long and Short Signals
Long Signals : These are generated when the RSI of the DEMA crosses above the longThreshold (set at 70 by default) and the closing price is not above the upper volatility band. This suggests that the asset is gaining upward momentum while not being excessively overbought, presenting a potentially favorable buying opportunity.
Short Signals : Generated when the RSI of the DEMA falls below the shortThreshold (set at 55 by default). This indicates that the asset may be losing momentum or entering a downtrend, signaling a possible selling or shorting opportunity.
Logical Soundness
The logic of combining DEMA with RSI for generating trade signals is sound for several reasons:
Timeliness : The use of DEMA ensures that the price source for RSI calculation is up-to-date, making the momentum signals more relevant.
Balance : By setting distinct thresholds for long and short signals, the script balances sensitivity and specificity, aiming to minimize false signals while capturing genuine market movements.
Adaptability : The inclusion of user inputs for periods and thresholds allows traders to customize the indicator to fit various trading styles and timeframes.
Trading Use-Cases
This DEMA RSI Overlay indicator is versatile and can be applied across different markets and timeframes. Its primary use-cases include:
Trend Following: Traders can use it to identify the start of a new trend or the continuation of an existing trend.
Swing Trading: The indicator's sensitivity to price changes makes it ideal for swing traders looking to capitalize on short to medium-term price movements.
Risk Management: By providing clear long and short signals, it helps traders manage their positions more effectively, potentially reducing the risk of significant losses.
Final Note
We have also decided to add in the option of standard deviation bands, calculated on the DEMA, this can be used as a point of confluence rendering trading ranges. Expanding when volatility is high and compressing when it is low.
For example:
This provides the user with a 1, 2, 3 standard deviation band of the DEMA.
Thus following all of the key points here are some sample backtests on the 1D Chart
Disclaimer: Backtests are based off past results, and are not indicative of the future.
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
DEMA Adjusted Average True Range [BackQuant]The use of the Double Exponential Moving Average (DEMA) within your Adjusted Average True Range (ATR) calculation serves as a cornerstone for enhancing the indicator's responsiveness to market changes. To delve deeper into why DEMA is employed specifically in the context of your ATR calculation, let's explore the inherent qualities of DEMA and its impact on the ATR's performance.
DEMA and Its Advantages
As previously mentioned, DEMA was designed to offer a more responsive alternative to the traditional Exponential Moving Average (EMA). By giving more weight to recent price data, DEMA reduces the lag typically associated with moving averages. This reduction in lag is especially beneficial for short-term traders looking to capitalize on trend reversals and other market movements as swiftly as possible.
The calculation of DEMA involves the following steps:
Calculate EMA1: This is the Exponential Moving Average of the price.
Calculate EMA2: This is the Exponential Moving Average of EMA1, thus it is a smoothing of a smoothing, leading to a greater lag.
Formulate DEMA: The formula
EMA1 = EMA of price
EMA2 = EMA of EMA1
DEMA = (2 x EMA1) - EMA2
effectively doubles the weighting of the most recent data points by subtracting the lagged, double-smoothed EMA2 from twice the single-smoothed EMA1.
This process enhances the moving average's sensitivity to recent price movements, allowing the DEMA to adhere more closely to the price bars than either EMA1 or EMA2 alone.
Integration with ATR
In the context of your ATR calculation, the integration of DEMA plays a crucial role in defining the indicator's core functionality. Here's a detailed explanation of how DEMA affects the ATR calculation:
Initial Determination of DEMA : By applying the DEMA formula to the chosen source data (which can be adjusted to use Heikin Ashi candle close prices for an even smoother analysis), you set a foundation for a more reactive trend-following mechanism within the ATR framework.
Application to ATR Bands : The calculated DEMA serves as the central line from which the ATR bands are derived. The ATR value, multiplied by a user-defined factor, is added to and subtracted from the DEMA to form the upper and lower bands, respectively. This dynamic adjustment not only reflects the volatility based on the ATR but does so in a way that is closely aligned with the most recent price action, thanks to the utilization of DEMA.
Enhanced Signal Quality : The responsiveness of DEMA ensures that the ATR bands adjust more promptly to changes in market conditions. This quality is vital for traders who rely on the ATR bands to identify potential entry and exit points, trend reversals, or to assess market volatility.
By employing DEMA as the core component in calculating the Adjusted Average True Range, your indicator leverages DEMA's reduced lag and increased weight on recent data to provide a more timely and accurate measure of market volatility. This innovative approach enhances the utility of the ATR by making it not only a tool for assessing volatility but also a more reactive indicator for trend analysis and trading signal generation.
The main concept of combining these is to reduce lag, get a more robust signal and still capture clear trends over medium time horizons.
For me, this is best used in confluence with other indicators, it can be made faster in order to get fasters response time, or slower. This is all depending on the needs of you as a trader.
User Inputs:
The script offers several user-configurable inputs, such as the period lengths for DEMA and ATR calculations, the multiplication factor for the ATR, and options to use Heikin Ashi candles or standard price data. Additionally, it allows for the toggling of visual features, like the plotting of the DEMA ATR and its moving average, and the application of color-coded trends on price bars.
Additional Features:
Moving Average Confluence: Traders can opt to display a moving average of the DEMA ATR, choosing from various types (e.g., SMA, EMA, HMA). This feature provides a layer of confluence, aiding in the identification of trend direction and strength.
Trend Identification :
The script employs logical conditions to ascertain the trend direction based on the movement of the DEMA ATR. It assigns colors to represent bullish or bearish trends, which are reflected in the plotted lines and the coloring of price bars.
Alerts :
Customizable alert conditions for trend reversals enhance the utility of the indicator for active trading, notifying users of significant changes in trend direction.
1D Backtests
We include these backtests as a general proxy for how they work.
Please do your own calibrating to suit it to your own needs and backtest.
Past results don't = future results but they can help you understand how it functions.
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
REMA CROSSOVER BY JUGNUThis indicator triggers alerts for long and short positions on DAILY TIME FRAME for SWING trades based on the conditions which described below. This script will generate alerts when the following conditions are met:
LONG POSITION:
RSI(14) above 50.
EMA(5) crosses above EMA(10).
Indicator Triangle Green below price bars
SHORT POSITION:
RSI(14) below 50.
EMA(5) crosses down EMA(10).
Indicator Triangle RED above price bars
This script plots green and red triangles below and above the price bars to indicate long and short alert conditions, respectively. It also triggers alerts when these conditions are met.
13E2113E21 is a strategy based on the concept of "Buy-on-Dip" and "Sell-on-Rise". The strategy is built around the concept that as the market starts trending in a particular direction it will give a retrace to it's 13 exponential moving average price and then continue in it's trend thus forming higher lows (or lower highs) in the process.
The indicator 13E21 helps determine the 2 EMAs (13 and 21) and also highlights the candle that touches either EMAs and closes accordingly.
The edge in the code is that it makes use of the difference between the two EMAs as a signal of the market trending. It will trigger an entry only when the difference between the two EMAs is greater than 0.02% thus implying that the market is actually trending and not consolidating.
The indicator will give bullish triggers only when the price touches 13EMA or 21EMA, the closing price is greater than 13EMA and the difference between 13EMA and 21EMA is greater than 0.02% or 10 points.
Similarly, the indicator will give bearish triggers only when the price touches 13EMA or 21EMA, the closing price is less than 13EMA and the difference between 13EMA and 21EMA is greater than 0.02% or 10 points.
Dee EMA 5.0
1. Indicator Features:
- The indicator can plot four different sets of EMA on a chart.
- The EMA values can be displayed on the chart with their respective names (e.g., ema9, ema20, etc.).
- The indicator allows customization of the EMA values.
2. Purpose of Dee_EMA 5.0:
- Dee_EMA 5.0 is a unique EMA indicator specially designed for traders to provide better insights and aid in trading decisions.
- The primary reason for building this indicator is to address the challenge of managing multiple time frames while using normal EMA tables.
- Traditional EMA tables might not show all EMA values across different time frames simultaneously, leading to time-consuming processes like shifting time frames and refreshing charts.
- Dee_EMA 5.0 solves this issue by displaying EMA values for different time frames in one table, allowing traders to make quick judgments without repeatedly changing time frames and refreshing charts.
3. Importance of Different Time Frame EMA Values:
- Different time frames EMA values are crucial in trading because they provide valuable insights into the market dynamics at various levels.
- When using shorter time frames (e.g., 1-minute), EMA values can help identify short-term trends, support, and resistance levels.
- On the other hand, using larger time frames (e.g., 5-minute or 15-minute) provides more data and increases the accuracy of EMA-based analysis, enabling traders to identify longer-term trends and potential price movements.
4. EMA Crossover Table:
- Traders often prefer a clutter-free chart without too many lines, but they still need access to EMA values for analysis.
- The EMA table and EMA crossover table serve this purpose by providing EMA values and EMA crossover information in a structured table format.
- With the EMA crossover table, traders can quickly check EMA values and crossovers across different time frames without having to switch time frames repeatedly, saving time and facilitating faster decision-making during trading.
In summary, Dee_EMA 5.0 is an EMA indicator designed to help traders efficiently analyze EMA values across different time frames, allowing for faster and more informed trading decisions. The EMA crossover table provides additional convenience by presenting EMA crossovers without cluttering the chart.
QuantBot 3:Ultimate MA CrossoverTHIS IS A SAMPLE CODE TO AUTOMATE WITH QUANTBOT
The moving average strategy is a popular and widely used technique in financial analysis and trading. It involves the calculation and analysis of moving averages, which are mathematical indicators that smooth out price data over a specified period. This strategy is primarily applied in the context of stock trading, but it can be used for other financial instruments as well.
The concept behind the moving average strategy is to identify trends and potential entry or exit points in the market. By calculating and analyzing moving averages of different timeframes, traders aim to capture the overall direction of the price movement and filter out short-term fluctuations or noise.
To implement the moving average strategy, a trader typically selects two or more moving averages with different periods. The most common combinations include the 50-day and 200-day moving averages. The shorter-term moving average is considered more reactive to price changes, while the longer-term moving average provides a smoother trend line. When the shorter-term moving average crosses above the longer-term moving average, it generates a buy signal, indicating a potential upward trend. Conversely, when the shorter-term moving average crosses below the longer-term moving average, it generates a sell signal, indicating a potential downward trend.
Traders can use various variations of the moving average strategy based on their trading objectives and risk tolerance. For instance, some traders may prefer to use exponential moving averages (EMAs) instead of simple moving averages (SMAs) to give more weight to recent price data. Others may incorporate additional indicators or filters to confirm signals or avoid false signals.
One of the strengths of the moving average strategy is its simplicity and ease of interpretation. It provides a clear visual representation of the trend direction and potential entry or exit points. However, it's important to note that the moving average strategy is a lagging indicator, meaning that it relies on past price data. Therefore, it may not always accurately predict future market movements or capture sudden reversals.
Like any trading strategy, the moving average strategy is not foolproof and carries risks. It is crucial for traders to conduct thorough analysis, consider other relevant factors, and manage their risk through proper position sizing and risk management techniques. Additionally, it's important to adapt the strategy to specific market conditions and combine it with other complementary strategies or indicators for improved decision-making.
Overall, the moving average strategy serves as a valuable tool for traders to identify and follow trends in financial markets, aiding in the analysis of price movements and potential trading opportunities.
PA Double Diamond [NawidD.]This indicator will use ALMA cross as strategy to display Buy and Sell signals. You can filter the signals with several options, like a Moving Average (MA), True Strength Index (TSI), Range Filter, and/or filter by session. You can set alerts with pre-defined Take Profit (TP) and Stoploss (SL). Please read below for more detailed information.
Plots on the chart
- ALMA Fast and ALMA Slow.
- ALMA Cross Dots on top.
- Buy/Sell signals. Show as a Diamond or as regular.
- Moving Average (MA). Available options: SMA/EMA/ZLEMA/DEMA/TEMA.
- Sessions Filter (London/New York/Tokyo/Sydney)
- Take Profit and Stoploss.
- Show Stoploss hit.
ALMA
Default is ALMA Fast set to 13 and ALMA Slow set to 50. These can be changed by input.
ALMA Cross Dots on top
This will display dots on top of the chart. It shows ALMA Fast and ALMA Slow crosses only, without MA, TSI, Range Filter, and Session filter.
- Blue dot: ALMA crossover, up direction.
- Orange dot: ALMA crossunder, down direction.
Moving Average (MA) for overall trend direction
It is possible to enable the overal trend direction using the MA.
When enabled, Buy signals will be shown when signal is above the MA, and Sell signals will be shown when signal is below the MA. The following options are available:
- SMA = Simple Moving Average
- EMA = Exponential Moving Average
- ZLEMA = Zero Lag Exponential Moving Average
- DEMA = Double Exponential Moving Average
- TEMA = Triangular Moving Average
True Strength Index (TSI)
The signals can be filtered using the True Strength Index (TSI). Please note, this indicator will use the TSI, but won't display it for visualization. Default options: Long Length 25, Short Long 13, Signal Length 13. This can be changed by input.
Range Filter
The signals can be filtered using the Range Filter. Change the input in the settings. You can also display the Range Filter from the Styles tab.
Sessions Filter
Filter signals by session. You can also select the UTC timezone, and use daylight savings time (this will add 1 hour for daylight savings time). Available options to use as session filter: London/New York/Tokyo/Sydney. You can also display the sessions without using them as filter.
Take Profit (TP) and Stoploss (SL)
The TP and SL can be set. Use the value in ticks. So 30 pips equals 300 ticks. You can enable/disable the TP and SL from settings.
Alert Option
Alerts can be set to message you with the pre-defined TP and SL when a Buy Signal or Sell Signal occurs. I recommend to use alerts with trigger "Once per bar close". When linked to your broker/metatrader it is possible to set the indicator as autotrading since it will message you:
- Entry price
- TP price
- SL price
GKD-C QQE of Variety RSI [Loxx]Giga Kaleidoscope GKD-C QQE of Variety RSI is a Confirmation module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
█ GKD-C QQE of Variety RSI
QQE: A Comprehensive Alternative to the Relative Strength Index
The Relative Strength Index (RSI) is a popular technical indicator that measures the speed and change of price movements to help traders identify potential trend reversals, overbought, and oversold conditions. Although the RSI is widely used, it has its limitations, and traders often seek alternative or complementary indicators to improve their market analysis. One such alternative is the Qualitative Quantitative Estimation (QQE) indicator, a comprehensive oscillator that combines the features of the RSI with additional smoothing and volatility adjustments. In the following, we will explore the QQE indicator, its calculation, and its potential benefits compared to using any type of RSI alone.
QQE Indicator
The QQE indicator was developed by an unknown author and is based on the RSI with additional modifications to enhance its performance. The QQE calculation involves three main steps:
1. The first step is to compute the RSI value for a specified period using the traditional RSI formula.
2. The second step is to apply a smoothing technique, such as the Wilder's smoothing or an exponential moving average (EMA), to the RSI value, resulting in the smoothed RSI.
3. The third step is to calculate the volatility-adjusted upper and lower bands (referred to as the QQE lines) around the smoothed RSI using an ATR-based (Average True Range) multiplier.
The QQE indicator is typically displayed as an oscillator with the smoothed RSI line in the middle and the upper and lower QQE lines acting as dynamic boundaries.
Comparison with the RSI
To better understand the potential benefits of the QQE indicator compared to using any type of RSI alone, let's examine its key features and how they may contribute to improved market analysis.
Advantages
1. The QQE indicator provides a more comprehensive view of the market by combining the strengths of the RSI with additional smoothing and volatility adjustments. This may result in a more reliable and accurate reflection of market conditions and price trends.
2. The smoothed RSI line in the QQE oscillator can help filter out noise and reduce the number of false signals often experienced when using the traditional RSI alone, making it easier for traders to identify genuine trend reversals and trading opportunities.
3. The dynamic QQE lines offer an additional layer of information by accounting for market volatility. This can help traders to better gauge the strength of price movements and identify potential support and resistance levels.
4. The QQE indicator can be used as a standalone tool or in combination with other technical indicators, providing traders with greater flexibility in their market analysis.
Disadvantages
1. The QQE indicator may be more complex to understand and implement than the traditional RSI due to the additional smoothing and volatility adjustments involved in its calculation.
2. As the QQE indicator is less widely known and used than the RSI, traders may find it more challenging to find resources and support for incorporating this indicator into their trading strategies.
Conclusion:
The QQE indicator is a versatile and comprehensive alternative to the traditional RSI, offering potential benefits in terms of noise reduction, volatility adjustment, and improved market analysis. However, it is important to recognize its limitations, such as increased complexity and limited resources compared to the RSI. Traders should carefully consider the potential advantages and drawbacks of using the QQE indicator before integrating it into their trading strategies. Ultimately, the choice between the QQE and any type of RSI will depend on individual traders' preferences and the specific market conditions they are analyzing.
This indicator includes 3 types of signals
1. Middle cross
2. Levels cross
3. Slow Trend cross
This indicator includes 9 types of RSI
1. Regular RSI
2. Slow RSI
3. Ehlers Smoothed RSI
4. Cutler's RSI or Rapid RSI
5. RSI T3
6. RSI DEMA
7. Harris' RSI
8. RSI TEMA
9. Jurik RSX
Regular RSI
The Relative Strength Index (RSI) is a widely used technical indicator in the field of financial market analysis. Developed by J. Welles Wilder Jr. in 1978, the RSI is a momentum oscillator that measures the speed and change of price movements. It helps traders identify potential trend reversals, overbought, and oversold conditions in a market.
The RSI is calculated based on the average gains and losses of an asset over a specified period, typically 14 days. The formula for calculating the RSI is as follows:
RSI = 100 - (100 / (1 + RS))
Where:
RS (Relative Strength) = Average gain over the specified period / Average loss over the specified period
The RSI ranges from 0 to 100, with values above 70 generally considered overbought (potentially indicating that the asset is overvalued and may experience a price decline) and values below 30 considered oversold (potentially indicating that the asset is undervalued and may experience a price increase).
Slow RSI
The Slow RSI is a variation of the standard RSI, which introduces a smoothing technique to the RSI calculation itself. The primary difference between the Slow RSI and the standard RSI lies in the calculation of the RSI value. In the Slow RSI, the current RSI value is calculated as a moving average of the previous RSI value and the standard RSI value for the current period.
The primary advantage of the Slow RSI is that it offers enhanced signal stability, reducing noise and potentially providing more reliable trading signals for traders.
Comparison with the original RSI
To better understand the potential advantages and disadvantages of the Slow RSI, it is essential to compare its performance against the original RSI.
Advantages
1. The Slow RSI provides enhanced signal stability by smoothing the RSI calculation, which can help traders better assess market conditions and identify potential overbought or oversold situations.
2. By offering more stable and reliable signals, the Slow RSI may improve the performance of trading strategies based on the RSI, especially in noisy or choppy market conditions.
Disadvantages
1. The smoothing technique employed by the Slow RSI may result in a slower response to changes in price momentum compared to the original RSI. This could lead to delayed signals for entering or exiting trades, which may not be ideal for short-term traders or fast-moving markets.
2. As the Slow RSI is less known and less widely used than the standard RSI, traders may find it more challenging to find resources and support for implementing this variation of the indicator.
The Slow RSI is an interesting modification of the standard RSI, offering potential benefits in terms of signal stability and reliability. However, it is crucial to recognize its limitations, such as a potentially slower response to changes in price momentum. Traders should carefully consider the potential advantages and drawbacks of using the Slow RSI compared to the original RSI before incorporating it into their trading strategies. Ultimately, the choice between the original RSI and the Slow RSI will depend on individual traders' preferences and the specific market conditions they are analyzing.
Ehlers Smoothed RSI
Ehlers Smoothed RSI is a variation of the standard RSI developed by John F. Ehlers, which introduces a smoothing technique to the price input data. The smoothing process involves averaging the current price with the previous two price values, which helps reduce noise and provide a more accurate representation of price momentum. The calculation of up and down price movements remains similar to the original RSI, but the smoothing technique alters the input data.
The primary advantage of Ehlers Smoothed RSI is that it reduces noise and offers a more accurate representation of price momentum, potentially providing more reliable signals for traders.
Comparison with the original RSI
To better understand the potential advantages and disadvantages of Ehlers Smoothed RSI, it is essential to compare its performance against the original RSI.
Advantages
1. Ehlers Smoothed RSI reduces noise by smoothing the price input data, which can help traders better assess market conditions and identify potential overbought or oversold situations.
2. By providing a more accurate representation of price momentum, Ehlers Smoothed RSI may offer more reliable signals for entering or exiting trades, potentially improving the performance of trading strategies based on the RSI.
Disadvantages
1. The smoothing technique employed by Ehlers Smoothed RSI may result in a slower response to changes in price momentum compared to the original RSI. This could lead to delayed signals for entering or exiting trades, which may not be ideal for short-term traders or fast-moving markets.
2. As Ehlers Smoothed RSI is less known and less widely used than the standard RSI, traders may find it more challenging to find resources and support for implementing this variation of the indicator.
Ehlers Smoothed RSI is an intriguing modification of the standard RSI, offering potential benefits in terms of noise reduction and accuracy. However, it is crucial to recognize its limitations, such as a potentially slower response to changes in price momentum. Traders should carefully consider the potential advantages and drawbacks of using Ehlers Smoothed RSI compared to the original RSI before incorporating it into their trading strategies. Ultimately, the choice between the original RSI and Ehlers Smoothed RSI will depend on individual traders' preferences and the specific market conditions they are analyzing.
Cutler's RSI or Rapid RSI
Cutler's RSI is a variation of the standard RSI, which modifies the calculation of average gains and losses. While the original RSI employs exponential moving averages (EMAs) for average gains and losses, Cutler's RSI utilizes simple moving averages (SMAs) instead. This change results in a slightly different behavior of the oscillator compared to the original RSI.
The primary advantage of Cutler's RSI is that it offers a simpler calculation method, which can potentially make it easier to understand and implement for traders. Additionally, by using SMAs, Cutler's RSI may provide a more consistent and stable representation of price momentum.
Comparison with the original RSI
It is essential to recognize the limitations and performance of Cutler's RSI compared to the original RSI to understand its potential advantages and disadvantages better.
Advantages
1. Cutler's RSI has a simpler calculation method, using SMAs instead of EMAs. This makes it easier to understand and implement for traders who prefer a more straightforward approach to technical analysis.
2. By using SMAs, Cutler's RSI may provide a more stable and consistent representation of price momentum, which can help traders better assess market conditions and identify potential overbought or oversold situations.
Disadvantages
1. The use of SMAs in Cutler's RSI may result in a slower response to changes in price momentum compared to the original RSI. This could lead to delayed signals for entering or exiting trades, which may not be ideal for short-term traders or fast-moving markets.
2. As Cutler's RSI is less known and less widely used than the standard RSI, it may be more challenging to find resources and support for implementing this variation of the indicator.
Cutler's RSI is an interesting modification of the standard RSI, offering potential benefits in terms of simplicity and stability. However, it is crucial to recognize its limitations, such as a potentially slower response to changes in price momentum. Traders should carefully consider the potential advantages and drawbacks of using Cutler's RSI compared to the original RSI before incorporating it into their trading strategies. Ultimately, the choice between the original RSI and Cutler's RSI will depend on individual traders' preferences and the specific market conditions they are analyzing.
RSI T3
The T3 RSI is a variation of the standard RSI that introduces the Triple Smoothed Exponential Moving Average (T3) into the calculation process. The primary difference between the T3 RSI and the standard RSI lies in the calculation of the average gains and losses. Instead of using simple moving averages or exponential moving averages, the T3 RSI utilizes T3 to calculate the average gains and losses for up and down price movements.
The primary advantage of the T3 RSI is that it offers enhanced responsiveness and accuracy compared to the original RSI, potentially providing more reliable trading signals for traders.
Comparison with the original RSI
To better understand the potential advantages and disadvantages of the T3 RSI, it is essential to compare its performance against the original RSI.
Advantages
1. The T3 RSI provides enhanced responsiveness and accuracy by incorporating the Triple Smoothed Exponential Moving Average into the calculation of average gains and losses. This can help traders better assess market conditions and identify potential overbought or oversold situations.
2. By offering more responsive and accurate signals, the T3 RSI may improve the performance of trading strategies based on the RSI, especially in fast-moving markets or during periods of high price volatility.
Disadvantages
1. The T3 RSI's increased responsiveness may result in more frequent trading signals, which could lead to higher trading costs or a higher likelihood of false signals.
2. As the T3 RSI is less known and less widely used than the standard RSI, traders may find it more challenging to find resources and support for implementing this variation of the indicator.
The T3 RSI is an innovative modification of the standard RSI, offering potential benefits in terms of responsiveness and accuracy. However, it is crucial to recognize its limitations, such as a potentially higher likelihood of false signals due to increased responsiveness. Traders should carefully consider the potential advantages and drawbacks of using the T3 RSI compared to the original RSI before incorporating it into their trading strategies. Ultimately, the choice between the original RSI and the T3 RSI will depend on individual traders' preferences and the specific market conditions they are analyzing.
RSI DEMA
The DEMA RSI is a variation of the standard RSI that introduces the Double Exponential Moving Average (DEMA) into the calculation process. The primary difference between the DEMA RSI and the standard RSI lies in the calculation of the average gains and losses. Instead of using simple moving averages or exponential moving averages, the DEMA RSI utilizes DEMA to calculate the average gains and losses for up and down price movements.
The primary advantage of the DEMA RSI is that it offers enhanced responsiveness and accuracy compared to the original RSI, potentially providing more reliable trading signals for traders.
Comparison with the original RSI
To better understand the potential advantages and disadvantages of the DEMA RSI, it is essential to compare its performance against the original RSI.
Advantages
1. The DEMA RSI provides enhanced responsiveness and accuracy by incorporating the Double Exponential Moving Average into the calculation of average gains and losses. This can help traders better assess market conditions and identify potential overbought or oversold situations.
2. By offering more responsive and accurate signals, the DEMA RSI may improve the performance of trading strategies based on the RSI, especially in fast-moving markets or during periods of high price volatility.
Disadvantages
1. The DEMA RSI's increased responsiveness may result in more frequent trading signals, which could lead to higher trading costs or a higher likelihood of false signals.
2. As the DEMA RSI is less known and less widely used than the standard RSI, traders may find it more challenging to find resources and support for implementing this variation of the indicator.
The DEMA RSI is an innovative modification of the standard RSI, offering potential benefits in terms of responsiveness and accuracy. However, it is crucial to recognize its limitations, such as a potentially higher likelihood of false signals due to increased responsiveness. Traders should carefully consider the potential advantages and drawbacks of using the DEMA RSI compared to the original RSI before incorporating it into their trading strategies. Ultimately, the choice between the original RSI and the DEMA RSI will depend on individual traders' preferences and the specific market conditions they are analyzing.
Harris' RSI
Harris' RSI is a variation of the standard RSI, designed to address some of its limitations and improve its performance in detecting potential trend reversals and filtering out noise. The key difference between the Harris' RSI and the standard RSI lies in the calculation of average gains and losses. While the standard RSI calculation uses exponential moving averages (EMAs) of gains and losses, Harris' RSI uses a different approach to compute the average gains and losses based on the number of up and down price movements.
The primary advantage of Harris' RSI is that it aims to provide a more adaptive and responsive indicator, making it better suited for detecting potential trend reversals and filtering out noise in the market. By taking into account the number of up and down price movements, Harris' RSI can be more sensitive to changes in the trend, potentially providing earlier signals for entering or exiting trades.
Comparison with the original RSI
While Harris' RSI offers potential improvements over the standard RSI, it is essential to recognize its limitations and compare its performance against the original RSI.
Advantages
1. Harris' RSI can potentially provide earlier signals for trend reversals due to its sensitivity to the number of up and down price movements. This can help traders to identify better entry and exit points in the market.
2. By focusing on the number of up and down price movements, Harris' RSI can filter out noise in the market, reducing the likelihood of false signals that may lead to losing trades.
Disadvantages
1. The increased sensitivity of Harris' RSI to price movements can lead to more frequent signals, which may result in overtrading and increased trading costs.
2. Harris' RSI is less known and less widely used than the standard RSI, which may make it more challenging to find resources and support for implementing this variation of the indicator.
Harris' RSI is an interesting variation of the standard RSI, offering potential advantages in detecting trend reversals and filtering out noise. However, like any technical indicator, it has its limitations and may not be suitable for all trading styles or market conditions. Traders should carefully consider the potential benefits and drawbacks of using Harris' RSI compared to the original RSI before incorporating it into their trading strategies. Ultimately, the choice between the original RSI and Harris' RSI will depend on individual traders' preferences and the specific market conditions they are analyzing.
RSI TEMA
The TEMA RSI is a variation of the standard RSI that introduces the Triple Exponential Moving Average (TEMA) into the calculation process. The primary difference between the TEMA RSI and the standard RSI lies in the calculation of the average gains and losses. Instead of using simple moving averages or exponential moving averages, the TEMA RSI utilizes TEMA to calculate the average gains and losses for up and down price movements.
The primary advantage of the TEMA RSI is that it offers enhanced responsiveness and accuracy compared to the original RSI, potentially providing more reliable trading signals for traders.
Comparison with the original RSI
To better understand the potential advantages and disadvantages of the TEMA RSI, it is essential to compare its performance against the original RSI.
Advantages
1. The TEMA RSI provides enhanced responsiveness and accuracy by incorporating the Triple Exponential Moving Average into the calculation of average gains and losses. This can help traders better assess market conditions and identify potential overbought or oversold situations.
2. By offering more responsive and accurate signals, the TEMA RSI may improve the performance of trading strategies based on the RSI, especially in fast-moving markets or during periods of high price volatility.
Disadvantages
1. The TEMA RSI's increased responsiveness may result in more frequent trading signals, which could lead to higher trading costs or a higher likelihood of false signals.
2. As the TEMA RSI is less known and less widely used than the standard RSI, traders may find it more challenging to find resources and support for implementing this variation of the indicator.
The TEMA RSI is an innovative modification of the standard RSI, offering potential benefits in terms of responsiveness and accuracy. However, it is crucial to recognize its limitations, such as a potentially higher likelihood of false signals due to increased responsiveness. Traders should carefully consider the potential advantages and drawbacks of using the TEMA RSI compared to the original RSI before incorporating it into their trading strategies. Ultimately, the choice between the original RSI and the TEMA RSI will depend on individual traders' preferences and the specific market conditions they are analyzing.
Jurik RSX
The Jurik RSX, developed by Mark Jurik, is a variation of the standard RSI that aims to provide a smoother and more responsive indicator by applying a unique smoothing algorithm based on a series of recursive calculations. The Jurik RSX calculates the price momentum (mom) and the absolute price momentum (moa) using a three-stage filtering process, which ultimately results in a smoother and more responsive output compared to the original RSI.
Comparison with the original RSI
To better understand the potential benefits and drawbacks of the Jurik RSX, it is essential to compare its performance against the original RSI.
Advantages
1. The Jurik RSX offers enhanced responsiveness and smoothness due to its unique recursive filtering process, allowing traders to better identify potential trend reversals, overbought, and oversold conditions.
2. The improved responsiveness of the Jurik RSX may result in more timely trading signals, helping traders to capitalize on opportunities more effectively, especially in fast-moving markets or during periods of high price volatility.
Disadvantages
1. The increased complexity of the Jurik RSX calculation may make it more challenging for traders to understand and implement compared to the original RSI.
2. As the Jurik RSX is less known and less widely used than the standard RSI, traders may find it more difficult to find resources and support for implementing this variation of the indicator.
The Jurik RSX is an innovative modification of the standard RSI, offering potential benefits in terms of responsiveness and smoothness. However, it is crucial to recognize its limitations, such as increased complexity and limited resources compared to the original RSI. Traders should carefully consider the potential advantages and drawbacks of using the Jurik RSX before incorporating it into their trading strategies. Ultimately, the choice between the original RSI and the Jurik RSX will depend on individual traders' preferences and the specific market conditions they are analyzing.
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: QQE of Variety RSI as shown on the chart above
Confirmation 2: Williams Percent Range
Continuation: QQE of Variety RSI
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.
GKD-C RSI DEMA [Loxx]Giga Kaleidoscope GKD-C RSI DEMA is a Confirmation module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
█ GKD-C RSI DEMA
Exploring RSI-DEMA: A Novel Indicator for Technical Analysis in Trading
The world of trading has evolved considerably with the advent of technology and the development of various technical analysis tools. These tools assist traders in making informed decisions based on the historical price movements of financial instruments. One such tool is the Relative Strength Index (RSI), which has been widely used to gauge the momentum of price movements. However, the following explores a new variation of RSI, calculated using the Double Exponential Moving Average (DEMA), which we will refer to as RSI-DEMA.
Background on RSI
The Relative Strength Index (RSI) is a momentum oscillator developed by J. Welles Wilder in 1978. It measures the speed and change of price movements, oscillating between 0 and 100. The RSI is typically used to identify overbought or oversold conditions in a market. An RSI value above 70 suggests an overbought condition, whereas a value below 30 indicates an oversold condition. This information can be valuable for traders in determining potential entry and exit points.
Introducing RSI-DEMA
The RSI-DEMA is a modified version of the traditional RSI that incorporates the Double Exponential Moving Average (DEMA) in its calculation. DEMA, developed by Patrick Mulloy, is a type of moving average that reacts more quickly to recent price changes compared to other moving averages like Simple Moving Average (SMA) and Exponential Moving Average (EMA). By combining RSI with DEMA, the RSI-DEMA aims to provide a more sensitive and responsive momentum oscillator for traders to analyze market conditions.
RSI-DEMA Calculation
The RSI-DEMA formula calculates the RSI-DEMA value for a given input price (src) and period (per). The first step is to compute the alpha value, which is inversely proportional to the square root of the period. Next, the price change is calculated and separated into positive and negative changes. These changes are then smoothed using the DEMA method, which involves two stages of exponential smoothing.
Finally, the smoothed positive and negative changes are divided, and the result is scaled by 50 to obtain the RSI-DEMA value, which oscillates between 0 and 100. This value provides insight into the strength of the price momentum and can be used similarly to the traditional RSI to identify overbought and oversold conditions in the market.
Advantages of RSI-DEMA
The primary advantage of RSI-DEMA over the traditional RSI is its increased sensitivity to recent price changes. By incorporating the DEMA in its calculation, RSI-DEMA reacts more quickly to sudden price movements, potentially providing traders with more timely signals for entry or exit points. This may prove beneficial, especially in fast-paced or volatile market conditions.
In summary, RSI-DEMA is a novel technical indicator that combines the strengths of both RSI and DEMA to provide a more sensitive and responsive momentum oscillator. While the traditional RSI remains a popular and widely-used tool in technical analysis, the RSI-DEMA offers an interesting alternative for traders who seek a more responsive indicator to capture market opportunities in fast-paced and dynamic environments. As with any trading tool, the RSI-DEMA should be used in conjunction with other technical analysis methods and risk management strategies to achieve optimal trading outcomes.
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: RSI DEMA 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.
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.
