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

M Pesaran () and Paolo Zaffaroni

No 04.3, IEPR Working Papers from Institute of Economic Policy Research (IEPR)

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. In particular, it is shown that under certain conditions portfolio returns based on an average model will be more fat-tailed than if based on an individual underlying model with the same average volatility. Evaluation of volatility models is also considered and a simple Value-at-Risk (VaR) diagnostic test is proposed for individual as well as 'average' models and its exact and asymptotic properties are established. The model averaging idea and the VaR diagnostic tests are illustrated by an application to portfolios of daily returns based on twenty two of Standard & Poor's 500 industry group indices over the period January 2, 1995 to October 13, 2003, inclusive.

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)
Pages: 47 pages
Date: 2004-10
New Economics Papers: this item is included in nep-bec, nep-fin, nep-fmk and nep-rmg
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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 (2005) Downloads
Working Paper: Model Averaging and Value-at-Risk Based Evaluation of Large Multi Asset Volatility Models for Risk Management (2004) Downloads
Working Paper: Model Averaging and Value-at-Risk based Evaluation of Large Multi Asset Volatility Models for Risk Management (2004) Downloads
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