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.
Keywords: A, AA, AAA, B, BB, BBB, C, CC, CCC, Conditional Probabilities, Continuous-Time Markov Chain Process, Discrete-Time Markov Chain Process, Initial State Vector, Market Trends, Stock Markets, Steady-State Vector, Transition Matrix.
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