Module 3:Branching process, Application of Markov chains, Markov Processes with discrete and                 continuous state space
  Lecture 13:Differential Equation for Weiner Process
 

Kolmogorov Equations

As usual let us again consider  as the Markov process in continuous time and continuous state set up such that the following assumptions are considered to be true:

  • ,

  • , where  is the drift coefficient.

  • , where  is the diffusion coefficient.

Then the corresponding forward Kolmorogov equation and backward Kolmorogov equation are given by:

Note

  • In case  then the Markov process is homogeneous and we have  and , i.e., both are independent of time .

  • If the Markov process is additive, then  depends only on  and  and not on , hence  and we have  and , i.e., both are independent of time .