✦ LIBER ✦

The bias in time series volatility forecasts

✍ Scribed by Louis H. Ederington; Wei Guan

Publisher: John Wiley and Sons
Year: 2009
Tongue: English
Weight: 137 KB
Volume: 30
Category: Article
ISSN: 0270-7314
DOI: 10.1002/fut.20417

No coin nor oath required. For personal study only.

✦ Synopsis

Abstract

By Jensen's inequality, a model's forecasts of the variance and standard deviation of returns cannot both be unbiased. This study explores the bias in GARCH type model forecasts of the standard deviation of returns, which we argue is the more appropriate volatility measure for most financial applications. For a wide variety of markets, the GARCH, EGARCH, and GJR (or TGARCH) models tend to persistently over‐estimate the standard deviation of returns, whereas the ARLS model of L. Ederington and W. Guan (2005a) does not. Furthermore, the GARCH and GJR forecasts are especially biased following high volatility days, which cause a large jump in forecast volatility, which is rarely fully realized. © 2009 Wiley Periodicals, Inc. Jrl Fut Mark 30:305–323, 2010

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