Master of Quantitative Finance

16:960:583 Statistical Methods of Inference (3) Statistical theory of inference follows the introduction to probability theory and emphasizes the fundamental concepts and underlying theories of point and interval estimation and hypothesis testing. Topics include sufficiency, unbiasedness, Bayes methods, and power function.
Prerequisite: 16:960:582.

22:390:608 Portfolio Management (3) Comprehensive coverage of the theory and practice of money management as well as in-depth analysis of the theory and practice involved when securities are combined into portfolios. Like 22:390:603, the course is designed for finance majors interested in a career in money management. Prerequisites: 22:223:581 or 591; 22:390:587 or 522; and 603.

22:711:685 Operations Research Models in Finance (3) Teaches students the use of operations research models in the areas of risk and portfolio management.

22:839:510 Numerical Analysis (3) This course derives, analyzes, and applies methods used to solve numerical problems with computers; solution of linear and nonlinear algebraic equations by iterations, linear equations and matrices, least squares, interpolation and approximation of functions, numerical differentiation and integration, and numerical solutions of ordinary differential equations.

22:839:571 Financial Modeling I (3) The first of the two-course sequence in financial theory for Ph.D. and master in quantitative finance (M.Q.F.) students. The course surveys the fundamental assumptions and the analytical techniques of the modern finance theory. It builds a foundation for the study of higher-level courses in investment theory and corporate finance. Topics include capital market equilibrium models, risk analysis using utility theory, state preference theory, portfolio selection, market efficiency, and empirical tests of asset pricing models.

22:839:614 Object Oriented Programming in Finance I (3) C++ is a higher-level computer language with multiple personalities. The objective for this two-part course is for the student to become proficient in C++ programming so as to be able to develop C++ functions and classes for independent and interrelated economic models via parametrization and/or class interrelation. Topics will include data structures from the simple data types and matrices to interrelated classes and inheritance; standard mathematics libraries, logic and processing from simple conditionals to iteration and multitasking, and the various forms of parametrization.

22:839:615 Object Oriented Programming in Finance II (3)  C++ is a higher-level computer language with multiple personalities. The objective for this two-part course is for the student to become proficient in C++ programming so as to be able to develop C++ functions and classes for independent and interrelated economic models via parametrization and/or class interrelation. Topics will include data structures from the simple data types and matrices to interrelated classes and inheritance; standard mathematics libraries, logic and processing from simple conditionals to iteration and multitasking, and the various forms of parametrization.

22:839:662 Financial Modeling II (3) This course covers continuous time finance, similar to an advanced Ph.D. course in asset pricing.  It follows Financial Modeling I which covers discrete time finance and continues with continuous time financial theories. Included are basic theories (backward and forward equations, change of measure, state pricing, arbitrage pricing, martingales); derivatives pricing (Black-Scholes model, Heston model, Geske model, Merton-Rabinovitch model); term structure of interest rates (Vasicek model, CIR model, HJM model, Hull-White model); multifactor models (Chen-Scott model, Bakshi-Cao-Chen-Scott model, Duffie-Pan-Singleton model); credit derivatives (Jarrow-Turnbull model, Duffie-Singleton model); and some numerical methods (binomial model, finite difference methods, Monte-Carlo). Interested students can get a good idea from the following books: Merton - Continuous Time Finance, Duffie - Dynamic Asset Pricing Theory, Ingersoll - Theory of Financial Decision Making, and similar others.

26:960:580 Applied Stochastic Processes (3) Reviews probability theory with emphasis on conditional expectations, Markov process, Poisson process, continuous-time Markov chains, renewal theory, martingale theory, and stochastic calculus such as Ito's lemma, Browian motion, and related topics.
Prerequisite: 16:960:582 or equivalent.