Market conditions and time varying conditional correlations

  • Johan Knif Hanken School of Economics
  • James Kolari Texas A&M University
  • Seppo Pynnönen University of Vaasa
Keywords: Conditional correlation, Volatility, GARCH


This paper shows how the dependency of time-varying conditional crosscorrelation on prevailing market conditions can be modeled. With this modelling approach it is possible to empirically investigate how correlations between different markets are dependent on market volatilities and other external factors. The paper shows that the modeling of conditional correlations can be simplified to modeling a univariate GARCH-process. The advantage of this approach is that it allows for utilization of existing GARCH methodology and software to estimate the dynamics of correlation. Our empirical results reveal that time-varying correlations between stock markets are largely unpredictable and are at best dependent on world market volatilities. Weaker evidence is found that correlations are driven by market downturns. 


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Author Biographies

Johan Knif, Hanken School of Economics

Johan Knif is Professor of Finance at Hanken School of Economics in Vaasa, Finland

James Kolari, Texas A&M University

James Kolari is Professor of Finance at Texas A&M University in Texas, USA

Seppo Pynnönen, University of Vaasa

Seppo Pynnönen is Professor of Statistics at University of Vaasa in Vaasa, Finland

How to Cite
Knif, J., Kolari, J., & Pynnönen, S. (2014). Market conditions and time varying conditional correlations. Applied Finance Letters, 3(1), 22-27.