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Primary Article

Implied Volatility Indexes and Daily Value at Risk Models

Pierre Giot
The Journal of Derivatives Summer 2005, 12 (4) 54-64; DOI: https://doi.org/10.3905/jod.2005.517186
Pierre Giot
A professor of finance at CEREFIM of the University of Namur in Namur, Belgium, and a research fellow at the Center for Operations Research and Econometrics (CORE) at the Université Catholique de Louvain, in Louvain,Belgium.
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Abstract

Value at risk, though flawed as a concept, has become one of the most common ways to summarize risk exposure for an investment position. Computing VaR requires the volatility of the underlying asset as an input. The two general approaches are to use historical volatility or some other estimator based on past returns, such as GARCH; or, alternatively, to compute implied volatility from observed market option prices. The Chicago Board Options Exchange computes and publishes indexes of implied volatilities from options on the stocks in the S&P 500 (VIX) and the Nasdaq index (VXN), respectively. In this article, Giot compares the performance of volatility forecasts drawn from historical returns and from option implied volatilities, using metrics that are appropriate for VaR estimates, such as the empirical failure rate relative to the target VaR percentage, independence, and conditional coverage. Implied volatility is found to perform relatively well, but combining GARCH and implied volatility often improves on the results from either one alone.

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The Journal of Derivatives
Vol. 12, Issue 4
Summer 2005
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Implied Volatility Indexes and Daily Value at Risk Models
Pierre Giot
The Journal of Derivatives May 2005, 12 (4) 54-64; DOI: 10.3905/jod.2005.517186

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Implied Volatility Indexes and Daily Value at Risk Models
Pierre Giot
The Journal of Derivatives May 2005, 12 (4) 54-64; DOI: 10.3905/jod.2005.517186
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