Modeling conditional correlations of asset returns: a smooth transition approach. (English) Zbl 1491.62261
Summary: In this paper we propose a new multivariate GARCH model with time-varying conditional correlation structure. The time-varying conditional correlations change smoothly between two extreme states of constant correlations according to a predetermined or exogenous transition variable. An LM-test is derived to test the constancy of correlations and LM- and Wald tests to test the hypothesis of partially constant correlations. Analytical expressions for the test statistics and the required derivatives are provided to make computations feasible. An empirical example based on daily return series of five frequently traded stocks in the S&P 500 stock index completes the paper.
MSC:
| 62P20 | Applications of statistics to economics |
| 62M10 | Time series, auto-correlation, regression, etc. in statistics (GARCH) |
| 62P05 | Applications of statistics to actuarial sciences and financial mathematics |
| 91B84 | Economic time series analysis |
Keywords:
constant conditional correlation; dynamic conditional correlation; multivariate GARCH; return comovement; variable correlation GARCH model; volatility model evaluationReferences:
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