Modeling Conditional Correlations of Asset Returns: A Smooth Transition Approach
提出一种新的多元GARCH模型，允许条件相关性随时间平滑变化，并提供了检验相关性是否恒定的LM和Wald检验方法，适用于金融资产收益的动态相关性分析。
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.