The Information Content of Implied Volatility Indexes for Forecasting Volatility and Market Risk

54 Pages Posted: 15 Jan 2003

See all articles by Pierre Giot

Pierre Giot

Facultés Universitaires Notre-Dame de la Paix (FUNDP)

Date Written: December 13, 2002

Abstract

In this paper, we assess the efficiency, information content and unbiasedness of volatility forecasts based on the VIX/VXN implied volatility indexes, RiskMetrics and GARCH-type models at the 5-, 10- and 22-day time horizon. Our empirical application focuses on the S&P100 and NASDAQ100 indexes. We also deal with the information content of the competing volatility forecasts in a market risk (VaR type) evaluation framework. The performance of the models is evaluated using LR, independence, conditional coverage and density forecast tests. Our results show that volatility forecasts based on the VIX/VXN indexes have the highest information content, both in the volatility forecasting and market risk assessment frameworks. Because they are easy-to-use and compare very favorably with much more complex econometric models that use historical returns, we argue that options and futures exchanges should compute implied volatility indexes and make these available to investors.

Keywords: VIX, Implied volatility, Volatility forecast, VaR, Density forecasts

Suggested Citation

Giot, Pierre, The Information Content of Implied Volatility Indexes for Forecasting Volatility and Market Risk (December 13, 2002). Available at SSRN: https://ssrn.com/abstract=362440 or http://dx.doi.org/10.2139/ssrn.362440

Pierre Giot (Contact Author)

Facultés Universitaires Notre-Dame de la Paix (FUNDP) ( email )

Rempart de la Vierge 8
B-5000 Namur
Belgium

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