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Filters and smoothers for self-exciting Markov modulated counting processes
- Publication Year :
- 2013
-
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.
- Subjects :
- FOS: Economics and business
FOS: Computer and information sciences
Statistics - Other Statistics
Quantitative Finance - Computational Finance
Quantitative Finance - Trading and Market Microstructure
Other Statistics (stat.OT)
Probability (math.PR)
FOS: Mathematics
62M05, 60G55, 60J28, 91G70
Computational Finance (q-fin.CP)
Mathematics - Probability
Trading and Market Microstructure (q-fin.TR)
Subjects
Details
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....3c5d5481d742cead77c6b883df0a7ba8