Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5096027 | Journal of Econometrics | 2014 | 35 Pages |
Abstract
We propose a model that can capture the typical features of multivariate extreme events observed in financial time series, namely, clustering behaviors in magnitudes and arrival times of multivariate extreme events, and time-varying dependence. The model is developed within the framework of the peaks-over-threshold approach in extreme value theory and relies on a Poisson process with self-exciting intensity. We discuss the properties of the model, treat its estimation, and address testing its goodness-of-fit. The model is applied to the return data of two stock markets.
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Oliver Grothe, Volodymyr Korniichuk, Hans Manner,