Continuous Time Markov Chains

# Continuous Time Markov ChainsΒΆ

**Authors**: Thomas J. Sargent and John
Stachurski

These lectures provides a short introduction to continuous time Markov chains. Mathematical ideas are combined with computer code to build intuition and bridge the gap between theory and applications. There are many solved exercises.

The presentation is rigorous but aims toward applications rather than mathematical curiosities (which are plentiful, if one starts to look). Applications are drawn from economics, finance and operations research. I assume readers have some knowledge of discrete time Markov chains. Later lectures, use a small amount of analysis in Banach space.

Code is written in Python and accelerated using JIT compilation via Numba. QuantEcon provides an introduction to these topics.