Course Descriptions

Prerequisites: Level IV Statistics. Basic concepts in Probability and Statistics and matrix algebra; Correlation and Portfolio management; Simple linear regression and capital asset pricing model;...

Read more: FSRM 16:958:563 Regression...

The emphasis of this course will be on (1) basic banking, financial market and risk management concepts and (2) on the use of discrete stochastic models and optimization for portfolio management,...

Read more: FSRM 16:958:590 Foundations of...

Prerequisites: One year of Calculus.  Probability spaces, distributions (with an emphasis on distributions that are important for financial applications, e.g. lognormal and heavy-tailed...

Read more: MSDS 16:954:581 Probability and...

This course added for first time in Spring 2017 as a required course for the Risk Management track option  bridges the gap  between 16:958:590 given in the first Fall semester and which establishes...

Read more: FSRM 16:958:534 Advanced Methods...

Prerequisites: 16:958:563. Conditional expectation and martingales, return and yield curve, portfolio theory, derivatives, risk neutral measure and complete market in discrete models,...

Read more: FSRM 16:958:535 Advanced...

Prerequisites: 16:958:563 or permission of instructor. Features of financial time series. Model-based forecasting methods, autoregressive and moving average models, ARIMA, ARMAX, ARCH, GARCH,...

Read more: FSRM 16:958:565 Financial Time...

The course covers the basic concepts of object oriented programming and the syntax of the Python language.  The course objectives include learning how to go from the different stages of designing a program...

Read more: FSRM 16:958:589 Advanced...

Prerequisites: 16:958:590, 16:958:534. This course deals with the practical application of risk management in financial institutions. Leading practitioners from industry teach case studies on the...

Read more: FSRM 16:958:536 Financial Risk...

Prerequisites: 16:958:563, and 16:198:443 or equivalent C++  course or permission of instructor. Modern simulation methods and advanced statistical computing techniques for financial applications....

Read more: FSRM 16:958:587 Advanced...

Prerequisites: 16:958:563. Supervised and unsupervised learning; shrinkage and regularization in regression; splines and kernel smoothing; linear discriminant analysis, logistic regression, supper...

Read more: FSRM 16:958:588 Financial Data...

The course will develop a general quantitative approach to modern portfolio theory, optimization, and trading. Topics to include: factor models and Arbitrage Pricing Theory (APT); modeling risk...

Read more: FSRM 16:958:694 Asset Allocation...

Prerequisites: Familiarity with Prim and Kruskal minimum spanning tree algorithms and Dijkstra shortest path algorithm. Discussion of representative algorithms and data structures encountered in...

Read more: CS 16:198:513 Design and Analysis...

Prerequisites: 16:198:513. Advanced data structures such as splay trees, link-cut dynamic trees, and finger search trees. Models of parallel computation; selected parallel algorithms. Approximation...

Read more: CS 16:198:514 Design and Analysis...

Prerequisites: Familiarity with an imperative programming language (e.g., C), an undergraduate or graduate compilers course, and an undergraduate or graduate data structures/algorithms course. This...

Read more: CS 16:198:515 Programming...

Prerequisites: 16:198:515. Focus on advanced, optimizing compiler design and typically includes a programming project to write an optimizing compiler.

Read more: CS 16:198:516 Programming...

Prerequisites: 16:198:510. Classes of computer methods: methods of points, methods of lines, finite elements, Ritz-Galerkin-type methods. Examples of simple computer programs. Stability, Consistency and...

Read more: CS 16:198:527 Computer Methods...

This is a design oriented course that meets in a computer lab/classroom for maximum emphasis on hands-on programming. Lectures will be reinforced with small programming examples during the lecture,...

Read more: ECE 16:332:503 Programming...

Prerequisites: 16:220:500 or permission of instructor. General equilibrium theory; the Arrow-Debreu model, decision making under uncertainty; the Von Neumann-Morgenstern theory, risk aversion,...

Read more: Econ 16:220:501 Microeconomics I

Prerequisites: 16:220:501. Introduction to the theory of games and related economic models with informational asymmetries. Topics include non-cooperative games and models of moral hazard and adverse...

Read more: Econ 16:220:502 Microeconomics II

Prerequisites: 16:220:503 or permission of instructor. Introduction to economic dynamics, economic growth, business cycles, and the role of macroeconomic policy.

Read more: Econ 16:220:504 Macroeconomics I

Prerequisites: 16:220:504. General equilibrium modeling of the macroeconomy. Topics will include the stochastic growth model and multiple equilibrium. Empirical validation will also be stressed.

Read more: Econ 16:220:505 Macroeconomics II

Prerequisites: 16:642:621, 16:642:573, and 16:332:503, or equivalent courses. Students learn how to implement financial option-pricing and risk-management models using C++, building on previous and...

Read more: Math 16:642:623 Computational...

Prerequisites: 16:642:622 and 16:642:573 or 16:642:574. In addition to equity, interest rates, FX, and commodity derivatives, credit derivatives play an increasingly important role in financial...

Read more: Math 16:642:624 Credit Risk...

16:642:622 and 16:960:563, or an equivalent graduate course on regression analysis. The course will introduce discuss quantitative portfolio theory and related topics. It will begin with classical...

Read more: Math 16:642:625 Portfolio Theory...

Prerequisites: One year of calculus, level V statistics or permission of instructor. Statistical methodology for survival and reliability data. Topics include life table techniques; competing risk...

Read more: Stat 16:960:542 Life Data Analysis

Prerequisites: Advanced calculus, 16:960:582 or equivalent. Markov chains, recurrence, random walk, gambler's ruin, ergodic theory and stationary distributions, continuous time Markov chains,...

Read more: Stat 16:960:554 Applied...

Prerequisites: Level V statistics or permission of instructor. Methods for reduction of dimensionality, including principal components analysis, factor analysis, and multidimensional scaling;...

Read more: Stat 16:960:567 Applied...