Simulation Methods for Financial Analytics . 3 credits

Catalog description

This course introduces Monte Carlo simulation methods for financial analytics, with an emphasis on their use in modern financial operations and risk analysis. Topics include the generation of random numbers and random variates, generation of Monte Carlo sample paths, variance reduction techniques, quasi-Monte Carlo, discretization methods, and sensitivity estimation. The course examines the simulation-based analysis of financial instruments and models, with applications to enterprise risk management, capital assessment, and stress testing. Students will develop a solid foundation in both the theoretical principles and practical implementation of simulation methodologies, supported by applied examples drawn from institutional financial contexts. Extensive hands-on experimentation using Python will be emphasized throughout the course. Offered by Systems Engr & Operations Rsch . Limited to two attempts.