Data Analysis and Financial Econometrics

QST MF 840

Graduate Prerequisites: (QSTMF793) - This is the second course of the econometrics sequence in the Mathematical Finance program. The course quickly reviews OLS, GLS, the Maximum Likelihood principle (MLE). Then, the core of the course concentrates on Bayesian Inference, now an unavoidable mainstay of Financial Econometrics. After learning the principles of Bayesian Inference, we study their implementation for key models in finance, especially related to portfolio design and volatility forecasting. We also briefly discuss the Lasso and Ridge methods, and contrast them with the Bayesian approach Over the last twenty years, radical developments in simulation methods, such as Markov Chain Monte Carlo (MCMC) have extended the capabilities of Bayesian methods. Therefore, after studying direct Monte Carlo simulation methods, the course covers non-trivial methods of simulation such as Markov Chain Monte Carlo (MCMC), applying them to implement models such as stochastic volatility. (Mathematical Finance courses are reserved for students enrolled in the Mathematical Finance program.)

SPRG 2025 Schedule

Section Instructor Location Schedule Notes
D1 Jacquier HAR 208 M 8:00 am-10:45 am

SPRG 2025 Schedule

Section Instructor Location Schedule Notes
D2 Jacquier HAR 208 M 11:00 am-1:45 pm

Note that this information may change at any time. Please visit the MyBU Student Portal for the most up-to-date course information.