Maximum likelihood estimation of skew t-copula
نویسنده
چکیده
We construct a copula from the multivariate skew t-distribution of Azzalini and Capitanio (2003). This copula can capture asymmetric and extreme dependence between variables, and it is one of the few that is effective when the number of dimensions is high. However, two problems arise when estimating the parameters by maximum likelihood estimation. Here, we solve these problems and provide a concrete maximum likelihood estimation algorithm. We test our solution by simulating trivariate data with realistic parameters. The parameters are estimated from the daily returns of three stock indices: the SP500, DAX, and Nikkei225.
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