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

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Author Info
M. Hashem Pesaran
Paolo Zaffaroni

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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.

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File URL: http://www.usc.edu/dept/LAS/economics/IEPR/Working%20Papers/IEPR_04.3_%5BPesaran,Zaffroni%5D.pdf
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Publisher Info
Paper provided by Institute of Economic Policy Research (IEPR) in its series IEPR Working Papers with number 04.3.

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Length: 47 pages
Date of creation: Oct 2004
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Handle: RePEc:scp:wpaper:04-3

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Related research
Keywords: Model Averaging Value-at-Risk Decision Based Evaluations

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Find related papers by JEL classification:
C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models
C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation and Testing
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications
G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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References listed on IDEAS
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Chun Liu & John M Maheu, 2008. "Forecasting Realized Volatility: A Bayesian Model Averaging Approach," Working Papers tecipa-313, University of Toronto, Department of Economics. [Downloadable!]
  2. Anthony Garratt & Kevin Lee & Emi Mise & Kalvinder Shields, 2006. "Real Time Representation of the UK Output Gap in the Presence of Trend Uncertainty," Birkbeck Working Papers in Economics and Finance 0618, Birkbeck, School of Economics, Mathematics & Statistics. [Downloadable!]
  3. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005. "Practical Volatility and Correlation Modeling for Financial Market Risk Management," NBER Working Papers 11069, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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