OPEN-SOURCE SCRIPT

Scalper's Volatility Filter [QuantraSystems]

Updated
Scalpers Volatility Filter

Introduction
The ๐’ฎ๐’ธ๐’ถ๐“๐“…๐‘’๐“‡'๐“ˆ ๐’ฑ๐‘œ๐“๐’ถ๐“‰๐’พ๐“๐’พ๐“‰๐“Ž ๐น๐’พ๐“๐“‰๐‘’๐“‡ (๐’ฎ๐’ฑ๐น) is a sophisticated technical indicator, designed to increase the profitability of lower timeframe trading.
Due to the inherent decrease in the signal-to-noise ratio when trading on lower timeframes, it is critical to develop analysis methods to inform traders of the optimal market periods to trade - and more importantly, when you shouldnโ€™t trade.
The ๐’ฎ๐’ฑ๐น uses a blend of volatility and momentum measurements, to signal the dominant market condition - trending or ranging.

snapshot
Legend
The ๐’ฎ๐’ฑ๐น consists of a signal line that moves above and below a central zero line, serving as the indication of market regime.
  • When the signal line is positioned above zero, it indicates a period of elevated volatility. These periods are more profitable for trading, as an asset will experience larger price swings, and by design, trend-following indicators will give less false signals.
  • Conversely, when the signal line moves below zero, a low volatility or mean-reverting market regime dominates.


This distinction is critical for traders in order to align strategies with the prevailing market behaviors - leveraging trends in volatile markets and exercising caution or implementing mean-reversion systems in periods of lower volatility.

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Case Study
Here we can see the indicator's unique edge in action.
  • Out of the four potential long entries seen on the chart - displayed via bar coloring, two would result in losses.
  • However, with the power of the ๐’ฎ๐’ฑ๐น a trader can effectively filter false signals by only entering momentum-trades when the signal line is above zero.
  • In this small sample of four trades, the ๐’ฎ๐’ฑ๐น increased the win rate from 50% to 100%



Methodology
The methodology behind the ๐’ฎ๐’ฑ๐น is based upon three components:
  1. By calculating and contrasting two ATRโ€™s, the immediate market momentum relative to the broader, established trend is calculated. The original method for this can be credited to the user xinolia
  2. A modified and smoothed ADX indicator is calculated to further assess the strength and sustainability of trends.
  3. The โ€˜Linear Regression Dispersionโ€™ measures price deviations from a fitted regression line, adding further confluence to the signals representation of market conditions.


Together, these components synthesize a robust, balanced view of market conditions, enabling traders to help align strategies with the prevailing market environment, in order to potentially increase expected value and win rates.
Release Notes
Modified normalization logic.
Added 'Dynamic' capabilities.
Added 'Compressed Signal Mode'.
Release Notes
Updated Dynamic Function Library.
Update header name tag.
Release Notes
Added a Heikin Ashi volatility visualization - for faster measurements.
Added 'HA-Width' another experimental measure of volatility.

snapshot
ADXAverage Directional Index (ADX)Average True Range (ATR)cryptodamianivolatmeterHistorical Volatilitylinear-regressionmeanreversionmulti-timeframerobusttradingvolatilty

Open-source script

In true TradingView spirit, the author of this script has published it open-source, so traders can understand and verify it. Cheers to the author! You may use it for free, but reuse of this code in publication is governed by House rules. You can favorite it to use it on a chart.

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No statements or claims aim to be financial advice,
neither are any signals from us or our indicators.


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