The Bias in Time-Series Volatility Forecasts
Louis H. Ederington
University of Oklahoma - Division of Finance
University of South Florida St. Petersburg
May 17, 2009
Journal of Futures Markets, 2009
By Jensen’s inequality, a model’s forecasts of the variance and standard deviation of returns cannot both be unbiased. This paper 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 while the ARLS model of Ederington and Guan (2005, JFM) 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.
Number of Pages in PDF File: 28
Keywords: GARCH, EGARCH, volatility, value-at-risk
JEL Classification: G123, C22, C53
Date posted: May 17, 2009
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