Filters and smoothers for self-exciting Markov modulated counting processes

Samuel N. Cohen and Robert J. Elliott

Papers from arXiv.org

Abstract: We consider a self-exciting counting process, the parameters of which depend on a hidden finite-state Markov chain. We derive the optimal filter and smoother for the hidden chain based on observation of the jump process. This filter is in closed form and is finite dimensional. We demonstrate the performance of this filter both with simulated data, and by analysing the `flash crash' of 6th May 2010 in this framework.

Date: 2013-11
New Economics Papers: this item is included in nep-ets
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