Markov Chain Process (Theory and Cases)

Computational Financial Issues

Author(s): Carlos Polanco * .

Pp: 78-86 (9)

DOI: 10.2174/9789815080476123010014

* (Excluding Mailing and Handling)

Abstract

This chapter defines Discrete or Continuous-Time Markov Chain Process aimed at predicting market trends, taking the ratings that the stock exchange gives to shares. The chapter is developed through two cases that affect in different ways the corresponding matrix of transition probabilities, in the discrete case conditional probabilities are assumed for each of the groups of shares that were registered in that matrix, and in the continuous case different forward and backward speeds between shares are assumed. 

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