Spring

IEORE4703 Monte Carlo Simulation


Instructor: Ali Hirsa


3 pts. Lect: 3. IEOR E4701: Stochastic Models for Financial Engineering, and IEOR E4706: Foundations of Financial Engineering, or instructor permission. This graduate course is only for MS Program in FE students. This course serves as an introduction to Monte Carlo stochastic simulation with its main focus on finance applications. Examples include simulating various random variables and then stochastic processes (random walks, point processes, geometric Brownian motion, other diffusions, binomial lattice model, etc.) for the purpose of numerically estimating quantities of interest (option prices, probabilities, other expected values and integrals, etc.) Methods to make the simulations more efficient (variance reduction methods), and statistical output analysis (confidence intervals) will be explored too. Although the main focus is on financial applications, other examples will sometimes be provided. Computer programming in MATLAB will be used. Students who have taken IEOR E4404 Simulation may not register for this course for credit.


Course Overview:
Monte Carlo simulation is a wide scope of computational algorithms that rely on recurrent random sampling from some distribution to obtain numerical results. They are often used in quantitative, mathematical, and physical problems and are most useful when dealing with problems which are dicult or not possible to use any other methods.

Monte Carlo methods are used in generating samples/draws from a probability distribution, numerical integration, optimization, and more. The computational platform for the course will be Python/R/Matlab.

Prerequisites: Core courses in the rst semester of MSFE should be sucient.



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