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    Rights statement: This is the peer reviewed version of the following article: Yao X, Izzeldin M. Forecasting using alternative measures of model-free option-implied volatility. J Futures Markets. 2018;38:199–218. https://doi.org/10.1002/fut.21881 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1002/fut.21881/abstract This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.

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Forecasting Using Alternative Measures of Model-Free Option-Implied Volatility

Research output: Contribution to journalJournal article

Published
<mark>Journal publication date</mark>02/2018
<mark>Journal</mark>Journal of Futures Markets
Issue number2
Volume38
Number of pages20
Pages (from-to)199-218
Publication statusPublished
Early online date2/10/17
Original languageEnglish

Abstract

This paper evaluates the performance of various measures of model-free implied volatility in predicting returns and realized volatility. The critical role of the out-of-the money call options is highlighted through an investigation of the relevance of different components of the model-free implied volatility. The Monte Carlo simulations show that: first, volatility forecasting performance of various measures can be enhanced by employing an interpolation-extrapolation technique; second, for most measures considered, gains in their predictive power for future returns can be obtained by implementing an interpolation procedure. An empirical application using SPX options recorded from 2003 to 2013 further illustrates these claims.

Bibliographic note

This is the peer reviewed version of the following article: Yao X, Izzeldin M. Forecasting using alternative measures of model-free option-implied volatility. J Futures Markets. 2018;38:199–218. https://doi.org/10.1002/fut.21881 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1002/fut.21881/abstract This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.