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Does the option market produce superior forecasts of noise-corrected volatility measures?

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Author Info
Gael M. Martin (Department of Econometrics and Business Statistics, Monash University, Melbourne, Victoria, Australia)
Andrew Reidy (Department of Econometrics and Business Statistics, Monash University, Melbourne, Victoria, Australia)
Jill Wright (Department of Econometrics and Business Statistics, Monash University, Melbourne, Victoria, Australia)

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Abstract

This paper assesses the robustness of the relative performance of spot- and options-based volatility forecasts to the treatment of microstructure noise. Robustness of the results to the method of constructing option-implied forecasts is also investigated. Using a test for superior predictive ability, model-free implied volatility, which exploits information in the volatility 'smile', and at-the-money implied volatility, which does not, are both tested as benchmark forecasts of a range of alternative volatility proxies. The results provide compelling evidence against the model-free forecast for three Dow Jones Industrial Average stocks, over a 2001-2006 evaluation period. In contrast, the at-the-money implied volatility forecast is given strong support for the three equities over this period. Neither benchmark is supported for the S&P500 index. Importantly, the main qualitative results are invariant to the method of noise correction used in measuring future volatility. Copyright © 2008 John Wiley & Sons, Ltd.

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File URL: http://hdl.handle.net/10.1002/jae.1033
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File URL: http://qed.econ.queensu.ca:80/jae/2009-v24.1/
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Article provided by John Wiley & Sons, Ltd. in its journal Journal of Applied Econometrics.

Volume (Year): 24 (2009)
Issue (Month): 1 ()
Pages: 77-104
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Handle: RePEc:jae:japmet:v:24:y:2009:i:1:p:77-104

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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  3. Catherine S. Forbes & Gael M. Martin & Jill Wright, 2007. "Inference for a Class of Stochastic Volatility Models Using Option and Spot Prices: Application of a Bivariate Kalman Filter," Econometric Reviews, Taylor and Francis Journals, vol. 26(2-4), pages 387-418. [Downloadable!] (restricted)
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Le-Yu Chen & Jerzy Szroeter, 2009. "Hypothesis testing of multiple inequalities: the method of constraint chaining," CeMMAP working papers CWP13/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies. [Downloadable!]
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