USF St. Petersburg campus Faculty Publications
The bias in time series volatility forecasts.
Document Type
Article
Publication Date
2010
ISSN
0270-7314
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.
Language
en_US
Publisher
John Wiley & Sons
Recommended Citation
Ederington, L.H. & Guan, W. (2010). The bias in time series volatility forecasts. Journal of Futures Markets, 30(4), 305-323.
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Comments
Abstract only. Full-text article is available through licensed access provided by the publisher. Published in Journal of Futures Markets, 30(4), 305-323. DOI: 10.1002/fut.20417. Members of the USF System may access the full-text of the article through the authenticated link provided.