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IEOR E4703: Monte-Carlo Simulation (Columbia University, Spring 2017)

I last taught this advanced-level MS course in spring 2017 in the IE&OR Department at Columbia University. The focus of the course was on Monte-Carlo methods with applications in finance but other application areas were also considered, particularly when it came to the topic of MCMC and Bayesian modeling. I will not be posting solutions to the assignments or code / software so please don’t send me an email asking me to do so! Finally, please note that I do not have time to answer emails asking me to clarify or explain issues arising in these notes and assignments. A syllabus and description of the course logistics can be found here.

Lecture Notes

1. Generating Random Variables and Stochastic Processes and slides
2. Output Analysis and Run-Length Control and slides
3. Simulation Efficiency and an Introduction to Variance Reduction Methods and slides
4. Further Variance Reduction Methods and slides
5. Simulating Stochastic Differential Equations and slides
6. Estimating the Greeks and slides
7. MCMC and Bayesian Modeling and slides
8. Other Topics and slides

Assignments

1. Assignment 1
2. Assignment 2
3. Assignment 3
4. Assignment 4
5. Assignment 5
6. Assignment 6
7. Assignment 7
8. Assignment 8

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