Model Averaging and Value-at-Risk Based Evaluation of Large Multi-Asset Volatility Models for Risk Management

Mohammad Pesaran and Paolo Zaffaroni

No 5279, CEPR Discussion Papers from C.E.P.R. Discussion Papers

Abstract: This paper considers the problem of model uncertainty in the case of multi-asset volatility models and discusses the use of model averaging techniques as a way of dealing with the risk of inadvertently using false models in portfolio management. Evaluation of volatility models is then considered and a simple Value-at-Risk (VaR) diagnostic test is proposed for individual as well as ?average? models. The asymptotic as well as the exact finite-sample distribution of the test statistic, dealing with the possibility of parameter uncertainty, are established. The model averaging idea and the VaR diagnostic tests are illustrated by an application to portfolios of daily returns based on 22 of Standard & Poor?s 500 industry group indices over the period 1995-2003. We find strong evidence in support of ?thick? modelling proposed in the forecasting literature by Granger and Jeon (2004).

Keywords: Model averaging; Value-at-risk; Decision-based evaluations (search for similar items in EconPapers)
JEL-codes: C32 C52 C53 G11 (search for similar items in EconPapers)
Date: 2005-10
New Economics Papers: this item is included in nep-bec, nep-ecm, nep-fin, nep-fmk and nep-rmg
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Citations: View citations in EconPapers (5)

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Related works:
Working Paper: Model Averaging and Value-at-Risk Based Evaluation of Large Multi Asset Volatility Models for Risk Management (2004)
Working Paper: Model Averaging and Value-at-Risk based Evaluation of Large Multi Asset Volatility Models for Risk Management (2004)
Working Paper: Model Averaging and Value-at-Risk based Evaluation of Large Multi Asset Volatility Models for Risk Management (2004)
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