2015issue C1134-37
Construct a percentage true range for cross-market volatility
An absolute true-range average cannot be compared across securities because it is built from raw price changes rather than a normalized scale. Dividing true range by the midpoint of that range produces a percentage true-range that can be compared with the same construction on other markets.
- An absolute true-range average cannot be compared across securities because it is built from raw price changes rather than a normalized scale.
- Percentage true range is the largest of three midpoint-normalized candidates: current high minus low, current high versus prior close, and current low versus prior close.
- After a 14-bar seed average, the percentage series updates as a recursive average and is scaled by 100 so volatility can be compared across securities.
- Seed start date, the first 14-bar simple average, the recursive update that begins on bar 15, and decimal rounding can change displayed values, so a spreadsheet sample need not match a chart reading exactly.
Start from the scale problem
An absolute true-range average cannot be compared across securities because it is built from raw price changes rather than a normalized scale.
Dividing true range by the midpoint of that range produces a percentage true-range that can be compared with the same construction on other markets.
Build the percentage true range
Percentage true range is the largest of three candidates: current high minus low, current high versus prior close, and current low versus prior close, each divided by the midpoint of the corresponding span, with the gap-to-prior-close spans taken as absolute values.
Midpoint-normalization divides a range span by the value that sits in the middle of that span so the result does not depend on the raw price level.
Smooth the percentage series
After a 14-bar seed average, the percentage series updates as a recursive average of the prior value times 13 plus the latest percentage true range, then divided by 14 and scaled by 100.
The average percentage true range is that recursively smoothed percentage of true range, typically seeded over 14 bars and scaled by 100, so volatility can be compared across securities.
The percentage construction can be computed on intraday, daily, weekly, or monthly bars, and the 14-bar default lookback can be changed.
Why two readings of the same series can disagree
Seed start date, the first 14-bar simple average, the recursive update that begins on bar 15, and decimal rounding can change displayed percentage values, so a short spreadsheet sample need not match a chart reading exactly.
On the same series, the percentage construction and the absolute-range construction can share a similar path shape while producing different numeric values.
What the historical charts showed
On a 2003 to 2007 weekly small-cap index chart that also plotted a 40-period exponential moving average, the percentage measure stayed relatively flat before a November 2007 breakout, while the absolute-range measure had been rising since May 2003.
In a July to October 2011 comparison, the percentage reading on a large-cap index was lower than the reading on a small-cap index, so the small-cap series was treated as the more volatile of the two.
All readings on this track · 36 readings
- 1988Constructing unsigned true range for directional models
- 1989Evaluate an always-in ATR breakout as one procedure
- 1992Variable lookback and average true range as a trend-filter construction
- 1993A random-walk index that uses true range as its scale
- 1993A shared harness for trend-filter construction
- 1998Finish a trend with a volatility trail, wave permission, and a slower-frame veto
- 1999A trend filter that switches tactics and scales ATR targets
- 2001Filter higher lows with linear regression, then judge the exit
- 2003A Mechanical trading system is a maintained procedure, not only an entry trigger
- 2005Construction of a volatility-bounded long entry
- 2005Six-zone encoding of open, high, low, and close
- 2006Normalized average true range as a pre-entry volatility bound
- 2006Chandelier exits, ATR position sizing, and trailing stops
- 2007Constructing a rule-based entry with Relative Strength Index and ATR position sizing
- 2008Constructing a zero-lag TMA and heikin-ashi crossover as a complete rule set
- 2010Use the session-range percent stop as a pre-trade filter
- 2011OCA exit groups, trailing limits, and ATR stops
- 2011ATR bands around support and resistance for stops and targets
- 2013Algorithmic head-and-shoulders construction with bounded exits
- 2013Constructing ATR-scaled swing pivots and linear-regression divergence
- 2013Constructing volatility bands from typical price
- 2014Constructing true-range contraction filters before expansion
- 2015Constructing touch plans from modified true range
- 2015One checklist for breakout entry and ATR risk
- 2015Percentage true-range construction for cross-market volatility filters
- 2015Construct a percentage true range for cross-market volatility
- 2015Percentage true range as a pre-entry exposure filter
- 2016Constructing ATR-filtered breakout entries
- 2017A dividend date as a pairs-trading classroom
- 2018Range-based volatility as a true-range construction
- 2018Moving average support and volatility-band construction
- 2018Construct a lifecycle breakout from compression
- 2018Pair the book first and let volatility or range set the size
- 2019Trend systems need a no-trade rule
- 2020Average true range as a shared unit for size, pairs, and stops
- 2020Volatility sizing and target-risk leverage as a pre-trade gate