EP30.TOKT1160 — Stochastic Processes

This course introduces fundamental concepts and methods of stochastic processes with applications in economics, finance, and actuarial science. Students will learn how to model randomness evolving over time, focusing on discrete and continuous time processes. Topics include Markov chains, branching processes, Poisson processes, continuous-time Markov processes, martingales, Brownian motion, and stochastic differential equations. Emphasis is placed on both theoretical foundations and applications, equipping students with tools for probabilistic modeling, risk management, and decision-making in uncertain environments.

Requirements for Final Examination

Attendance score must be at least 5 (according to University regulations).

See Appendix 2, Rubric 1 for attendance evaluation.

Requirements for Class Attendance

Students are responsible for attending all scheduled classes.

In case of absence due to force majeure, students must actively acquire the knowledge through the materials provided by the lecturer and other assigned readings.

Requirements for In-class Behaviour

The course is conducted on the principle of mutual respect between lecturers and students.

Students are required to take full notes and participate in answering questions.

Students must read assigned materials in advance.

Homework assignments must be completed as required.

Students must not make noise and disturb others.

Laptops, tablets, and mobile phones may only be used for note-taking, calculations, or learning purposes, and must not be used for any other activities.

The course content includes

• Introduction to stochastic processes
• Markov Chains 
• Branching Processes
• Poisson Process 
• Continuous Time Markov Process
• Martingales
• Brownian Motion