GKYZ-Filtered, Non-Linear Regression MA is a Non-Linear Regression of price moving average. Use this as you would any other moving average. This also includes a Garman-Klass-Yang-Zhang Historical Volatility Filter to reduce noise.
What is Non-Linear Regression?
In statistics, nonlinear regression is a form of regression analysis in which observational data...
JFD-Adaptive, GKYZ-Filtered KAMA is a Kaufman Adaptive Moving Average with the option to make it Jurik Fractal Dimension Adaptive. This also includes a Garman-Klass-Yang-Zhang Historical Volatility Filter to reduce noise.
What is KAMA?
Developed by Perry Kaufman, Kaufman's Adaptive Moving Average ( KAMA ) is a moving average designed to account for market...
RSI-Adaptive, GKYZ-Filtered DEMA is a Garman-Klass-Yang-Zhang Historical Volatility Filtered, RSI-Adaptive Double Exponential Moving Average. This is an experimental indicator. The way this is calculated is by turning RSI into an alpha value that is then injected into a DEMA function to output price. Price is then filtered using GKYZ Historical volatility. This...
Garman-Klass-Yang-Zhang Historical Volatility Bands are constructed using:
Average as the middle line.
Upper and lower bands using the Garman-Klass-Yang-Zhang Historical Volatility Bands for bands calculation.
What is Garman-Klass-Yang-Zhang Historical Volatility?
Yang and Zhang derived an extension to the Garman Klass historical volatility estimator...
Garman & Klass Estimator Historical Volatility Bands are constructed using:
Average as the middle line.
Upper and lower bands using the Garman & Klass Estimator Historical Volatility (instead of "regular" Historical Volatility ) for bands calculation.
What is Garman & Klaus Historical Volatility?
Garman Klass is a volatility estimator that incorporates...
First off, a huge thank you to the following people:
theheirophant: www.tradingview.com
alexgrover: www.tradingview.com
NGBaltic: www.tradingview.com
This is the Yang & Zhang extension of Garman & Klass. The equation was modified to include the logarithm of the open price divided by the preceding close price. As a result, this function uses the open, high,...
The Garman and Klass estimator for estimating historical volatility assumes Brownian motion with zero drift and no opening jumps (i.e. the opening = close of the previous period). This estimator is 7.4 times more efficient than the close-to-close estimator.
DISCLAIMER:
The Following indicator/code IS NOT intended to be a formal investment advice or recommendation by the author, nor should be construed as such. Users will be fully responsible by their use regarding their own trading vehicles/assets.
The embedded code and ideas within this work are FREELY AND PUBLICLY available on the Web for NON LUCRATIVE...
![USDCHF: GKYZ-Filtered, Non-Linear Regression MA [Loxx]](https://s3.tradingview.com/o/OLXmph7m_mid.png "GKYZ-Filtered, Non-Linear Regression MA [Loxx]")
![USDCHF: JFD-Adaptive, GKYZ-Filtered KAMA [Loxx]](https://s3.tradingview.com/k/KJQp4GrB_mid.png "JFD-Adaptive, GKYZ-Filtered KAMA [Loxx]")
![USDCHF: RSI-Adaptive, GKYZ-Filtered DEMA [Loxx]](https://s3.tradingview.com/o/oIP0U33J_mid.png "RSI-Adaptive, GKYZ-Filtered DEMA [Loxx]")
![USDCHF: Garman-Klass-Yang-Zhang Historical Volatility Bands [Loxx]](https://s3.tradingview.com/7/769aHr2F_mid.png "Garman-Klass-Yang-Zhang Historical Volatility Bands [Loxx]")
![USDCHF: Garman & Klass Estimator Historical Volatility Bands [Loxx]](https://s3.tradingview.com/6/6vG4XTPr_mid.png "Garman & Klass Estimator Historical Volatility Bands [Loxx]")
