Modeling Multivariate Extreme Events Using Self-Exciting Point Processes
Volodymyr Korniichuk and
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Oliver Grothe: Department of Economic and Social Statistics, University of Cologne
Volodymyr Korniichuk: CGS, University of Cologne
Hans Manner: Department of Economic and Social Statistics, University of Cologne
No 03-06, Cologne Graduate School Working Paper Series from Cologne Graduate School in Management, Economics and Social Sciences
We propose a new model that can capture the typical features of multivariate extreme events observed in financial time series, namely clustering behavior in magnitudes and arrival times of multivariate extreme events, and time-varying dependence. The model is developed in 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, deal with testing goodness-of-fit, and develop a simulation algorithm. The model is applied to return data of two stock markets and four major European banks.
Keywords: Time Series; Peaks Over Threshold; Hawkes Processes; Extreme Value Theory (search for similar items in EconPapers)
JEL-codes: C32 C51 C58 G15 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ban, nep-ecm and nep-rmg
Date: 2012-06-27, Revised 2013-06-20
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Persistent link: https://EconPapers.repec.org/RePEc:cgr:cgsser:03-06
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