Model Averaging in Risk Management with an Application to Futures Markets

Mohammad Pesaran, Christoph Schleicher and Paolo Zaffaroni

Cambridge Working Papers in Economics from Faculty of Economics, University of Cambridge

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 ¯nite-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 on six currencies, four equity indices, four ten year government bonds and four commodities over the period 1991-2007. The empirical evidence supports the use of `thick' model averaging strategies over single models or Bayesian type model averaging procedures.

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: 24
Date: 2008-01
New Economics Papers: this item is included in nep-ecm, nep-fmk and nep-rmg
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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Related works:
Journal Article: Model averaging in risk management with an application to futures markets (2009)
Working Paper: Model Averaging in Risk Management with an Application to Futures Markets (2008)
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Persistent link: https://EconPapers.repec.org/RePEc:cam:camdae:0808

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