Does the Option Market Produce Superior Forecasts of Noise-Corrected Volatility Measures?

Gael Martin, Andrew Reidy and Jill Wright ()

No 5/07, Monash Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics

Abstract: This paper presents a comprehensive empirical evaluation of option-implied and returns-based forecasts of volatility, in which recent developments related to the impact on measured volatility of market microstructure noise are taken into account. The paper also assesses the robustness of the performance of the option-implied forecasts to the way in which those forecasts are extracted from the option market. Using a test for superior predictive ability, model-free implied volatility, which aggregates information across the volatility 'smile', and at-the-money implied volatility, which ignores such information, are both tested as benchmark forecasts. The forecasting assessment is conducted using intraday data for three Dow Jones Industrial Average (DJIA) stocks and the S&P500 index over the 1996-2006 period, with future volatility proxied by a range of alternative noise-corrected realized measures. The results provide compelling evidence against the model-free forecast, with its poor performance linked to both the bias and excess variability that it exhibits as a forecast of actual volatility. The positive bias, in particular, is consistent with the option market factoring in a substantial premium for volatility risk. In contrast, implied volatility constructed from liquid at-the-money options is given strong support as a forecast of volatility, at least for the DJIA stocks. Neither benchmark is supported for the S&P500 index. Importantly, the qualitative results are robust to the measure used to proxy future volatility, although there is some evidence to suggest that any option-implied forecast may perform less well in forecasting the measure that excludes jump information, namely bi-power variation.

Keywords: Volatility Forecasts; Quadratic Variation; Intraday Volatility Measures (search for similar items in EconPapers)
JEL-codes: C10 C53 G12 (search for similar items in EconPapers)
Pages: 41 pages
Date: 2007-06
New Economics Papers: this item is included in nep-ets, nep-for, nep-mst and nep-rmg
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Citations: View citations in EconPapers (2)

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Related works:
Journal Article: Does the option market produce superior forecasts of noise-corrected volatility measures? (2009)
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