Modelling Volatilities and Conditional Correlations in Futures Markets with a Multivariate t Distribution
Bahram Pesaran () and
M. Hashem Pesaran ()
Additional contact information
Bahram Pesaran: affiliation not available
M. Hashem Pesaran: University of Cambridge
Authors registered in the RePEc Author Service: Mohammad Hashem Pesaran
No 2906, IZA Discussion Papers from Institute of Labor Economics (IZA)
Abstract:
This paper considers a multivariate t version of the Gaussian dynamic conditional correlation (DCC) model proposed by Engle (2002), and suggests the use of devolatized returns computed as returns standardized by realized volatilities rather than by GARCH type volatility estimates. The t-DCC estimation procedure is applied to a portfolio of daily returns on currency futures, government bonds and equity index futures. The results strongly reject the normal-DCC model in favour of a t-DCC specification. The t-DCC model also passes a number of VaR diagnostic tests over an evaluation sample. The estimation results suggest a general trend towards a lower level of return volatility, accompanied by a rising trend in conditional cross correlations in most markets; possibly reflecting the advent of euro in 1999 and increased interdependence of financial markets.
Keywords: volatilities and correlations; futures market; multivariate t; financial interdependence; VaR diagnostics (search for similar items in EconPapers)
JEL-codes: C51 C52 G11 (search for similar items in EconPapers)
Pages: 37 pages
Date: 2007-07
New Economics Papers: this item is included in nep-ecm and nep-ets
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (30)
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Working Paper: Modelling Volatilities and Conditional Correlations in Futures Markets with a Multivariate t Distribution (2007) 
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