Modeling multivariate extreme events using self-exciting point processes

Oliver Grothe, Volodymyr Korniichuk and Hans Manner

Journal of Econometrics, 2014, vol. 182, issue 2, 269-289

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.

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)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (17)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:182:y:2014:i:2:p:269-289

DOI: 10.1016/j.jeconom.2014.03.011

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