Author's Personal Copy Model Averaging in Risk Management with an Application to Futures Markets ☆

Article history: Received 11 January 2006 Received in revised form 31 July 2008 Accepted 1 August 2008 Available online 6 August 2008 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 away 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 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. © 2008 Elsevier B.V. All rights reserved. JEL classification: C32 C52 C53 G11