OPEN-SOURCE SCRIPT

Volume, Momentum and Volatility weighted moving average

已更新

Moving averages are filters on price data. This moving average creates a filter which factors in:
- the price RSI or it's Momentum
- the volume RSI
- the RVI or Volatility

Each factor is put through a least squares filter to smooth them first.

Then the factors are used to build a coefficient for an exponentially weighted average.

The chart above shows a comparison of standard average types with this script.

This is useful if you are looking for a moving average based trigger and do not wish to react to candle noise price action.

版本注释

Minor updates
- reverted to traditional RVI calculation
- pulled apart the momentum for high and low separately

版本注释

- Some important revisions - feel free to alter the source

- Addressed some initialization conditions
- Added another filter using normalized ratios for relative value filter
- Changed RSI to CMO, CMO is more responsive than RSI and reduces lag
- Added one of my favorite moving average, the Vidya MA

I think it's important to use this moving average with another average or even a supertrend, where the input to the trend is the VMV average. Perhaps a later modification.

I hope you enjoy how these two MA's work together.

版本注释

Quick fix of scaling issue, CMO ranges -100 to 100, RVI ranges 0 to 100 . All factors now produce a range of 0 to 100.

版本注释

_ Allow the script to run in a time frame different from the chart
_ Produce a dynamic length based on stochastic oscillator
_ Vidya_ma now runs on dynamic length
_ two more of my favorite ma's are included - parameter-less price and vwap

版本注释

Removed dynamic length selections
Addressed more initialization problems, if you use a recursive formula it's important the first 100 bars in a data set are not NA and are reasonable values, so need to fix some borrowed pine
Switched from using stochastic to pick up on trend to using two different inputs, tema and parameterless ma - averaging their best fit length
Dynamic length applied to the Vidya ma only

版本注释

added gap fill if used in a higher time frame than the chart
removed the least squares method and replaced with simple ema for speed of execution, the outcomes are close enough so it doesn't warrant the tax on execution speed
smoothed over a fixed length and not variable

版本注释

Updated to V5 Pine
- streamlined and simplified a few averages to speed up processing speed
- dynamic length calculations are done now in one loop vs 2
- removed normalization for Vidya and VMV

The script still generates warnings on compilation, but there is no easy way around them.