# MARKOV PROCESSES

A Markov process is a stochastic process that has the Markov property. In other words, a stochastic process is called a Markov process if at every time t, the conditional probability law of the process given the past depends only on the present state. Intuitively, a Markov process is a process that does not have memory. In this chapter, we present the mathematical definition of Markov processes and relevant results.

# 29.1 Basic Concepts and Facts

Definition 29.1 (Conditional Independence). Let (Ω, , P) be a probability space. Let be sub-σ-algebras of . Then are said to be conditionally independent given if where Vi is an arbitrary positive random variable in m i, i = 1, 2,…, n. Here mi is the set of all i-measurable functions.

Definition 29.2 (Markov Process). Let ...

Get Measure, Probability, and Mathematical Finance: A Problem-Oriented Approach now with the O’Reilly learning platform.

O’Reilly members experience live online training, plus books, videos, and digital content from nearly 200 publishers.