investment viewpoints

A primer on range-based volatility estimators

A primer on range-based volatility estimators
François Chareyron - Portfolio Manager

François Chareyron

Portfolio Manager
Julien Royer, PhD - Quantitative Analyst, Multi Asset

Julien Royer, PhD

Quantitative Analyst, Multi Asset

Welcome to the first edition of MARS, our Multi-Asset Research Series that brings quantitative investment research back to Earth. The series focuses on complex research topics in the realm of multi asset and begins by exploring volatility measures that use high-frequency data. 


Key areas covered include:

  • Volatility research has recently expanded amid the greater availability of intraday price data for financial assets. How could range-based volatility estimators help proxy intraday-based realised volatilities?
  • Outlining the realised volatility framework, we explore its advantages and disadvantages as they relate to measurement errors, empirical properties, the impact of noise and implementation costs
  • Popular, range-based estimators are discussed, including their benefits in overcoming the shortcomings of high-frequency data-based measures
  • We consider the positive statistical properties of the proposed range-based estimators, such as reduced implementation costs and the ability to incorporate intraday patterns efficiently
  • Finding that the use of range-based estimators can help obtain well-behaved volatility measures, we look to two areas of future research about volatility


For more, please read the first edition of MARS using the download button

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