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Model Averaging in Risk Management with an Application to Futures Markets

  • Pesaran, M.H.
  • Schleicher, C.
  • Zaffaroni, P.

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.

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File URL: http://www.econ.cam.ac.uk/research/repec/cam/pdf/cwpe0808.pdf
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Paper provided by Faculty of Economics, University of Cambridge in its series Cambridge Working Papers in Economics with number 0808.

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Length: 24
Date of creation: Jan 2008
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Handle: RePEc:cam:camdae:0808
Contact details of provider: Web page: http://www.econ.cam.ac.uk/index.htm

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