Article

Forecasting Stock Return Volatility: A Comparison of GARCH, Implied Volatility, and Realized Volatility Models

Details

Citation

Kambouroudis DS, McMillan D & Tsakou K (2016) Forecasting Stock Return Volatility: A Comparison of GARCH, Implied Volatility, and Realized Volatility Models. Journal of Futures Markets, 36 (12), pp. 1127-1163. https://doi.org/10.1002/fut.21783

Abstract
We investigate the information content of implied volatility forecasts for stock index return volatility. Using different autoregressive models, we examine whether implied volatility forecasts contain information for future volatility beyond that in GARCH and realized volatility models. Results show implied volatility follows a predictable pattern and confirm the existence of a contemporaneous relationship between implied volatility and index returns. Individually, implied volatility performs worse than alternate forecasts, however, a model that combines an asymmetric GARCH model with implied and realized volatility through (asymmetric) ARMA models is preferred model for forecasting volatility. This evidence is further supported by consideration of value-at-risk.

Journal
Journal of Futures Markets: Volume 36, Issue 12

StatusPublished
Publication date31/12/2016
Publication date online29/04/2016
Date accepted by journal23/01/2016
URLhttp://hdl.handle.net/1893/23189
PublisherWiley-Blackwell
ISSN0270-7314
eISSN1096-9934

People (2)

Dr Dimos S Kambouroudis

Dr Dimos S Kambouroudis

Senior Lecturer, Accounting & Finance

Professor David McMillan

Professor David McMillan

Professor in Finance, Accounting & Finance

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