DOI: 10.1142/s0218488523400160 ISSN: 0218-4885

Why Markov Switching Models Work Well: An Explanation

Woraphon Yamaka, Laxman Bokati
  • Artificial Intelligence
  • Information Systems
  • Control and Systems Engineering
  • Software

In general, the probability of the next state depends not only on the current state, but also on the whole pre-history. However, in practice, many real-life processes — including economic processes — can be well described by so-called Markov models, i.e., models in which the probability of the next state depends only on the current state. In this paper, we explain the empirical ubiquity of such models.

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