EP30.TOTC1119 — Stochastic Simulation and Applications In Finance
Course description
This course provides a self-contained introduction to Monte Carlo simulation methods with specific applications in financial engineering. Students will develop the mathematical tools and computational skills necessary to design and implement simulation schemes for pricing financial derivatives and analyzing risk. The course covers the generation of random variables, the simulation of Brownian motion and diffusion processes, and the implementation of arbitrage-free pricing models. A significant focus is placed on efficiency improvement through variance reduction techniques, including control variates, stratified sampling, and importance sampling. Additionally, the course explores stochastic calculus, the simulation of stochastic differential equations, and sensitivity analysis (Greeks). We use Python for all programming and implementation exercises.
Course requirements
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.
Detailed content
The course content includes
- Overview
- Monte Carlo Simulation
- Generating Random Variables
- Variance Reduction Techniques
- Simulation of Stochastic Processes
- Simulation of Diffusions
- Pricing Options using MC Simulations
- Sensitivity Analysis
- Simulation and Risk Management
- Markov Chain Monte Carlo methods
Lecturers
- Vuong Van Yen
- Nguyễn Quang Huy
Teaching plan
Week 1
Week 2
Week 4
Week 6
Learning resources
- Monte Carlo Simulation with Applications to Finance — Hui Wang, Chapman and Hall/CRC Financial Mathematics, 2012
- Stochastic Simulation and Applications in Finance — H. T. Huynh, V. S. Lai, I. Soumare, 2nd Edition, 2008
- Simulation Techniques in Financial Risk Management — N. Chan, H. Wong, Wiley, 2015
- R, Python