Volume Adaptive Chikou Scalping Study
IDEA PLACEMENT
This indicator uses “Chikou” cross concept of Ichimoku cloud indicator and enhances usage of High/Low data with Volume Breakout and Volatility based dynamic adaption.
I’ve been working on making Moving Averages more adaptive based on Volume Breakout and Volatility but as we know Mas work better on close values. I wanted to create a study that may have maximum data available and that’s how I came up with the concept of making adaptive Ichimoku Cloud. Except, I used different concept than Ichimoku. As we know that Tenkan-sen and Kijun-sen from Ichimoku Cloud average out highest and lowest values within 26 and 9 period respectively but I tried making it Volume Breakout and Volatility based Adaptive but couldn’t get better results.
Along the way I came up with an idea of instead of averaging out just keeping the High/Low values data separate and intact and to do so I took Linear regression of High values of Volume Breakout and Volatility based Adaptive dynamic period and similarly with Low values.
Then the strategy was to use Chikou for crossover and crossunder indication and for this purpose I used Chikou with same dynamic length as used before in High/Low linear regression.
The idea becomes simple as when Adaptive Dynamic Chikou crosses Adaptive Dynamic Linear Regression of High/Low values then Lowest / Highest value within current Adaptive Dynamic Length becomes the next Support / Resistance.
SIGNALS
Not every Chikou cross would give signal instead signal should be supported by either Volume Breakout or Volatility whatever you have selected from.
FIBONACCI EVELOPE BANDS
I’ve included ATR based Fibonacci multiple bands which would act as good support/resistance zones.
DEFAULT SETTINGS
FURTHER ENHANCEMENTS
I’ve used Linear Regression of High/Low values because I found better results with it but SMA and HMA can also be used. I’m planning to perpetually use this study for Dynamically length adaption and trades confirmations in other strategies.
This indicator uses “Chikou” cross concept of Ichimoku cloud indicator and enhances usage of High/Low data with Volume Breakout and Volatility based dynamic adaption.
I’ve been working on making Moving Averages more adaptive based on Volume Breakout and Volatility but as we know Mas work better on close values. I wanted to create a study that may have maximum data available and that’s how I came up with the concept of making adaptive Ichimoku Cloud. Except, I used different concept than Ichimoku. As we know that Tenkan-sen and Kijun-sen from Ichimoku Cloud average out highest and lowest values within 26 and 9 period respectively but I tried making it Volume Breakout and Volatility based Adaptive but couldn’t get better results.
Along the way I came up with an idea of instead of averaging out just keeping the High/Low values data separate and intact and to do so I took Linear regression of High values of Volume Breakout and Volatility based Adaptive dynamic period and similarly with Low values.
Then the strategy was to use Chikou for crossover and crossunder indication and for this purpose I used Chikou with same dynamic length as used before in High/Low linear regression.
The idea becomes simple as when Adaptive Dynamic Chikou crosses Adaptive Dynamic Linear Regression of High/Low values then Lowest / Highest value within current Adaptive Dynamic Length becomes the next Support / Resistance.
SIGNALS
Not every Chikou cross would give signal instead signal should be supported by either Volume Breakout or Volatility whatever you have selected from.
FIBONACCI EVELOPE BANDS
I’ve included ATR based Fibonacci multiple bands which would act as good support/resistance zones.
DEFAULT SETTINGS
- I’ve set default Minimum length to 20 and Maximum length to 50 which I’ve found works best for almost all timeframes but you can change this delta to adpat your timeframe accordingly with more precision.
- Dynamic length adoption is enabled based on both Volume and Volatility but only one or none of them can also be selected.
- Trend signals verification is enabled based on Volume but Volatility can also be enabled for more precise confirmations.
- In “RVSI” settings TFS Volume Oscillator is set to default but others work good too especially Volume Zone Oscillator. For more details about Volume Breakout you can check “MZ RVSI Indicator”
- ATR breakout is set to be true if period 14 exceeds period 46 but can be changed if more adaption with volatility is required.
FURTHER ENHANCEMENTS
I’ve used Linear Regression of High/Low values because I found better results with it but SMA and HMA can also be used. I’m planning to perpetually use this study for Dynamically length adaption and trades confirmations in other strategies.
版本注释:
Added Strategy Entries inside the script. So, to use this study as a strategy, just Uncomment the last lines and replace "study" with "strategy"
版本注释:
Fixed the buggy condition that made ATR bands to go below zero on some coins
版本注释:
Fixed Bands colors to color.new and removed unnecessary code from high/low calculations