ASSET CORRELATIONS IN TURBULENT MARKETS AND THE IMPACT OF DIFFERENT REGIMES ON ASSET MANAGEMENT

German Bernhart, Stephan Höcht (), Michael Neugebauer, Michael Neumann and Rudi Zagst
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German Bernhart: HVB Institute for Mathematical Finance, Technische Universität München, Boltzmannstr. 3, 85748 Garching, Germany
Stephan Höcht: HVB Institute for Mathematical Finance, Technische Universität München, Boltzmannstr. 3, 85748 Garching, Germany
Michael Neugebauer: HVB Institute for Mathematical Finance, Technische Universität München, Boltzmannstr. 3, 85748 Garching, Germany
Michael Neumann: HVB Institute for Mathematical Finance, Technische Universität München, Boltzmannstr. 3, 85748 Garching, Germany
Rudi Zagst: HVB Institute for Mathematical Finance, Technische Universität München, Boltzmannstr. 3, 85748 Garching, Germany

Asia-Pacific Journal of Operational Research (APJOR), 2011, vol. 28, issue 01, 1-23

Abstract: In this article, the dependence structure of the asset classes stocks, government bonds, and corporate bonds in different market environments and its implications on asset management are investigated for the US, European, and Asian market. Asset returns are modelled by a Markov-switching model which allows for two market regimes with completely different risk-return structures. Using major stock indices from all three regions, calm and turbulent market periods are identified for the time period between 1987 and 2009 and the correlation structures in the respective periods are compared. It turns out that the correlations between as well as within the asset classes under investigation are far from being stable and vary significantly between calm and turbulent market periods as well as in time. It also turns out that the US and European markets are much more integrated than the Asian and US/European ones. Moreover, the Asian market features more and longer turbulence phases. Finally, the impact of these findings is examined in a portfolio optimization context. To accomplish this, a case study using the mean-variance and the mean-conditional-value-at-risk framework as well as two levels of risk aversion is conducted. The results show that an explicit consideration of different market conditions in the modelling framework yields better portfolio performance as well as lower portfolio risk compared to standard approaches. These findings hold true for all investigated optimization frameworks and risk-aversion levels.

Keywords: Regime switching; correlation; financial crises; correlation breakdown; Markov switching; portfolio optimization (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (2)

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DOI: 10.1142/S0217595911003028

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