Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/38988
Authors: 
Pesaran, Bahram
Pesaran, Mohammad Hashem
Year of Publication: 
2010
Series/Report no.: 
CESifo working paper Empirical and Theoretical Methods 3023
Abstract: 
Modelling of conditional volatilities and correlations across asset returns is an integral part of portfolio decision making and risk management. Over the past three decades there has been a trend towards increased asset return correlations across markets, a trend which has been accentuated during the recent financial crisis. We shall examine the nature of asset return correlations using weekly returns on futures markets and investigate the extent to which multivariate volatility models proposed in the literature can be used to formally characterize and quantify market risk. In particular, we ask how adequate these models are for modelling market risk at times of financial crisis. In doing so we consider a multivariate t version of the Gaussian dynamic conditional correlation (DCC) model proposed by Engle (2002), and show that the t-DCC model passes the usual diagnostic tests based on probability integral transforms, but fails the value at risk (VaR) based diagnostics when applied to the post 2007 period that includes the recent financial crisis.
Subjects: 
volatilities and correlations
weekly returns
multivariate t
financial interdependence
VaR diagnostics
2008 stock market crash
JEL: 
C51
C52
G11
Document Type: 
Working Paper

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