Asymmetric dynamics in the correlations of global equity and bond returns.

Journal article

This paper proposes a new generalized autoregressive conditionally heteroskedastic (GARCH) process, the asymmetric generalized dynamic conditional correlation (AG-DCC) model. The AG-DCC process extends previous specifications along two dimensions: it allows for series-specific news impact and smoothing parameters and permits conditional asymmetries in correlation dynamics. The AG-DCC specification is well suited to examine correlation dynamics among different asset classes and investigate the presence of asymmetric responses in conditional variances and correlations to negative returns. We employ the AG-DCC model to analyze the behavior of international equities and government bonds. While equity returns show strong evidence of asymmetries in conditional volatility, little is found for bond returns. However, both equities and bonds exhibit asymmetries in conditional correlations, with equities responding stronger than bonds to joint bad news. The article also finds that, during periods of financial turmoil, equity market volatilities show important linkages, and conditional equity correlations among regional groups increase dramatically. Furthermore, in January 1999 with the introduction of the euro, we document significant evidence of a structural break in correlation although not in volatility. The introduction of a fixed exchange rate regime leads to near-perfect correlation among bond returns within the European Monetary Union (EMU) countries, which is not surprising when considering the harmonization in monetary policy. However, the increase in return correlation is not restricted to bond returns in EMU countries: equity return correlation both within and outside the EMU also increases.

Authors: Cappiello, L; Engle, R; Sheppard, K

• Publisher: Oxford University Press
• Journal: Journal of Financial Econometrics
• Volume: 4
• Issue: 4
• Pages: 537 - 572
• Publication date: 2006-01-01
• DOI: 10.1093/jjfinec/nbl005
• ISSN: 1479-8409
• Language: English