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Does VIX or volume improve GARCH volatility forecasts?

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  • Dimos S. Kambouroudis
  • David G. McMillan

Abstract

This article considers whether the inclusion of two additional variables can improve volatility forecasts over a standard GARCH-based model. We consider three alternative ways of incorporating the volatility index (VIX) and trading volume as exogenous variables within a selection of GARCH models. We are particularly interested in whether these variables have additional incremental forecast power over and above the baseline GARCH specification. Our results suggest that both the VIX and volume do provide some additional forecast power, and this is generally improved when considering both of these series jointly in the model. However, while the results may be statistically significant the gain is marginal and the coefficient values small. Moreover, in a horse race exercise VIX does not outperform the GARCH approach. In answering the question of whether VIX produces better forecasts than the GARCH model, then the answer is no, but the informational content of VIX cannot be ignored and should be incorporated into forecast regressions.

Suggested Citation

  • Dimos S. Kambouroudis & David G. McMillan, 2016. "Does VIX or volume improve GARCH volatility forecasts?," Applied Economics, Taylor & Francis Journals, vol. 48(13), pages 1210-1228, March.
  • Handle: RePEc:taf:applec:v:48:y:2016:i:13:p:1210-1228
    DOI: 10.1080/00036846.2015.1096004
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    References listed on IDEAS

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    1. Engle, Robert F. & White (the late), Halbert (ed.), 1999. "Cointegration, Causality, and Forecasting: Festschrift in Honour of Clive W. J. Granger," OUP Catalogue, Oxford University Press, number 9780198296836.
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