I have taught a wide range of courses at all levels. Below are brief descriptions of many of these courses.
Course Name | Level | Description | ||
Applied Time Series Analysis | MPS, MEng, B.S. | Elective course. Introduces statistical tools for the analysis of time-dependent data. Topics include linear, nonlinear, seasonal, multivariate modeling, and financial time series. | ||
Statistics for Financial Engineering |
MEng |
Core course. Regression, ARIMA, GARCH, stochastic volatility, and factor models. Calibration of financial engineering models. Estimation of diffusion models. Estimation of risk measures. Multivariate models and copulas. Bayesian statistics. | ||
Applied Statistics MPS Data Analysis Project |
MPS |
Core course. Long-term, in-depth statistical analysis of real-world dataset using various statistical methods and computer packages. Students work in teams to solve business, managerial or scientific problems for clients. | ||
Theory of Linear Models |
Ph.D. | Core course. Properties of the multivariate normal distribution. Distribution theory for quadratic forms. Properties of least squares and maximum likelihood estimates. Methods for fixed-effect models of less than full rank. Analysis of balanced and unbalanced mixed-effects models. Restricted maximum likelihood estimation. | ||
Operations Research Tools for Financial Engineering |
B.S. |
Elective course. Introduction to the applications of OR techniques, e.g., probability, statistics, and optimization, to finance and financial engineering. | ||
Statistics for Spatio-Temporal Data |
Ph.D. |
Elective course. Selected topics in time series and spatial statistics. | ||
Selected Topics in Advanced Statistics: Time Series |
Ph.D. |
Elective course. Selected topics in time series analysis. | ||
Basic Engineering Probability and Statistics |
B.S. | Gives students a working knowledge of basic probability and statistics and their application to engineering. Includes computer analysis of data and simulation. Topics include random variables, probability distributions, expectation, estimation, testing, experimental design, quality control, and regression. | ||
Applied Financial Engineering MEng Project |
MEng | Core course. Identification, analysis, design, and evaluation of feasible solutions to some applied problem in the ORIE field. |