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Filtering of Hidden Weak Markov Chain -Discrete Range Observations

In: Hidden Markov Models in Finance

Author

Listed:
  • Shangzhen Luo

    (University of Northern Iowa)

  • Allanus H. Tsoi

    (University of Missouri)

Abstract

Summary In this paper we consider a hidden discrete time finite state process X whose behavior at the present time t depends on its behavior at the previous k time steps, which is a generalization of the usual hidden finite state Markov chain, in which k equals to one. We consider the case when the range space of our observations is finite. We present filtering equations for certain functionals of the chain and perform related error analysis.

Suggested Citation

  • Shangzhen Luo & Allanus H. Tsoi, 2007. "Filtering of Hidden Weak Markov Chain -Discrete Range Observations," International Series in Operations Research & Management Science, in: Rogemar S. Mamon & Robert J. Elliott (ed.), Hidden Markov Models in Finance, chapter 7, pages 101-119, Springer.
    • Handle: RePEc:spr:isochp:978-0-387-71163-8_7
    DOI: 10.1007/0-387-71163-5_7
    as

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