Resource title

Model averaging and value-at-risk based evaluation of large multi asset volatility models for risk management

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Resource description

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.

Resource author

Mohammad Hashem Pesaran, Paolo Zaffaroni

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Resource publish date

Resource language

eng

Resource content type

text/html

Resource resource URL

http://hdl.handle.net/10419/18721

Resource license

Adapt according to the presented license agreement and reference the original author.