Courses

The listing of a course description here does not guarantee a course’s being offered in a particular term. Please refer to the published schedule of classes on the MyBU Student Portal for confirmation a class is actually being taught and for specific course meeting dates and times.

• QST LA 360: Real Estate Law
  Undergraduate Prerequisites: QST LA245. Pre-req for SHA students: SHA HF250 - Real estate can generate spectacular wealth and contribute to unprecedented financial losses. Real estate is an essential component of every business that requires a physical location to operate. Real estate is where we sleep, where we attend school, where we work, where we play, where we go when we are sick -it quite literally is beneath everything we do. Every real estate transaction begins and ends with legal principles. Mastering the basics of property law puts one in a superior position. Knowledge of real estate law is imperative for those who plan to invest in or manage property on a larger scale. This course provides an overview of real estate law for tenants, present and future property owners, developers, investors, and public policy advocates. We examine the nature of real property and property ownership, residential and commercial real estate transactions, and selected issues of real estate development.
• QST LA 365: Securities Regulation
  Undergraduate Prerequisites: (QSTLA245 & QSTFE323) - The securities industry is highly regulated by a complex set of federal laws designed to "protect investors, maintain fair, orderly, and efficient markets, and facilitate capital formation." (www.sec.gov/about/whatwedo.shtml) Federal law governs the issuance of securities ("going public"), regulates companies whose shares are being traded (known as "issuers"), and makes rules for everyone working in the securities industry, including bankers, brokers, dealers, and investment advisors. Those issuers and financial institutions (and their employees or directors) who violate the myriad of federal laws regulating securities face civil litigation from shareholders, enforcement actions by the Securities and Exchange Commission, and criminal charges from the Department of Justice. This course will focus upon the key federal statutes that regulate securities and participants in the securities markets: the Securities Act of 1933, the Securities Exchange Act of 1934, Sarbanes-Oxley, the Dodd-Frank Act of 2010, the Foreign Corrupt Practices Act, and several criminal statutes that are utilized for violations of securities regulation. We will read statutes and case law, and use examples and guest speakers to understand the application of the law in real life. The class is intended for students interested in careers in finance or leadership in a public company. The goal is not to create securities lawyers, but to give students an awareness of the regulation and the legal risks involved in the securities market.
• QST LA 450: Law and Risk Management
  Undergraduate Prerequisites: (QSTLA245) - Due to the financial crisis of 2008, the industry has re-aligned its business models to a risk-based approach for products and services. In response to this paradigm shift, Advanced Business Law, now known as Law and Risk Management, will focus on the identification, assessment, and management of operational and regulatory risk in the context of the law. Topics covered will continue to include contract risk, commercial financing, the Uniform Commercial Code, agency liability, bankruptcy, products liability, and real estate. The class will emphasize legal issues as a component of effective strategic business planning with a particular emphasis on duties and liabilities for corporate accounting. Group work includes contract drafting, interpretation, and negotiation. This course in part supplements many of the legal issues central to the accounting concentration and addresses many of the topics on the Regulation section of the CPA Exam.
• QST LA 498: Law Directed Study
  Directed study in Law. 2 or 4 cr. Application available on Undergraduate Program website.
• QST MF 600: Mathematics and Statistics Review
  Mathematical Finance as a discipline borrows concepts from probability theory, statistics, linear algebra, calculus and optimization, ordinary and partial differential equations, computer science and financial economics. This course reviews the essential prerequisites in mathematics, probability and statistics to prepare students for the MS in Mathematical Finance program. The course begins with a review of probability and the fundamentals of stochastic processes. Following this, statistical inference and linear algebra are reviewed. A review of comparative statics, optimization theory and dynamics, beginning with a review of integration, and continuing with first- and higher-order differential equations concludes the course.
• QST MF 601: Mathematical Finance Launch
  Mathematical Finance Launch is an orientation program for students entering the MS in Mathematical Finance program.
• QST MF 602: Program Refresher
  Program Refresher
• QST MF 610: Mathematical Finance Career Management
  This course prepares students in the MS Mathematical Finance program for the global employment market in quantitative finance. The course has the following objectives: to familiarize students with the foundational mathematics and statistics required for the MSMF program, to develop sound networking and job search strategies, to prepare students for 'quant' interviews, to develop good career management habits, and to familiarize students with important developments in financial markets and issues of the day that affect the global financial services industry.
• QST MF 650: Industry Internship
  MF 650 is offered to MS and PhD candidates in Mathematical Finance. The course affords graduate students the opportunity to complete an internship in the financial services (or a related) industry and serves to enhance the students' academic and/or research experience. MF 650 is required for all students pursuing the MSMF degree. It is an elective for PHD in Mathematical Finance students and has to be approved by the student's faculty advisor, department PhD Liaison and the PhD Program Director.
• QST MF 702: Fundamentals of Finance
  This course covers such topics as: financial markets (bonds, stocks, derivative securities, forward and futures contracts, exchanges, market indices, and margins); interest rates, present value, yields, term structure of interest rates, duration and immunization of bonds, risk preferences, asset valuation, Arrow-Debreu securities, complete and incomplete markets, pricing by arbitrage, the first and the second fundamental theorems of Finance, option pricing on event trees, risk and return (Sharpe ratios, risk premia), and the Capital Asset Pricing Model. (Mathematical Finance courses are reserved for students enrolled in the Mathematical Finance program.)
• QST MF 703: Programming for Mathematical Finance
  In-depth discussion of object-oriented programming with Python and C++ for finance and data applications. Topics include built-in-types, control structure, classes, constructors, destructors, function overloading, operator functions, friend functions, inheritance, and polymorphism with dynamic binding. Case study looks at the finite differences solutions for the basic models of financial derivatives; as well as the design and development of modular, scalable, and maintainable software for modeling financial derivatives. (Mathematical Finance courses are reserved for students enrolled in the Mathematical Finance program.)
• QST MF 728: Fixed Income Securities
  The course focuses on the valuation, hedging and management of fixed income securities. Theoretical and empirical term structure concepts are introduced. Short rate models and the Heath-Jarrow-Morton methodology are presented. Market models and their application for the valuation of forwards, swaps, caps, floors and swaptions, and other interest rate derivatives are discussed in detail. (Mathematical Finance courses are reserved for students enrolled in the Mathematical Finance program.)
• QST MF 730: Dynamic Portfolio Theory
  A concise introduction to recent results on optimal dynamic consumption- investment problems is provided. Lectures will cover standard mean-variance theory, dynamic asset allocation, asset-liability management, and lifecycle finance. The main focus of this course is to present a financial engineering approach to dynamic asset allocation problems of institutional investors such as pension funds, mutual funds, hedge funds, and sovereign wealth funds. Numerical methods for implementation of asset allocation models will also be presented. The course also covers empirical features and practical implementation of dynamic portfolio problems. (Mathematical Finance courses are reserved for students enrolled in the Mathematical Finance program.)
• QST MF 731: Corporate Risk Management
  This course is an introduction to modern methods of risk management. The first half of the course focuses on market risk. Here, lectures cover risk measures (such as Value at Risk and Expected Shortfall), with a focus on computation of such measures in a dynamic, multi-asset environment using real-world data. In particular, students will learn to compute, back-test, and account for risk measures when both monitoring and constructing portfolios. Additionally, lectures cover scenario analysis, stress testing, and the measurement of severe tail risk via extreme value theory. In the second half of the course, lectures cover alternate types of risk. These include operational, liquidity, model, and counter-party credit risk. In particular, students will derive formulas for the valuation adjustments due to counter-party default. The approach to the topic is quantitative. The course is ideal for students with strong quantitative backgrounds who are seeking to understand issues pertaining to risk management and to master modern methods and techniques of risk control. (Mathematical Finance courses are reserved for students enrolled in the Mathematical Finance program.)
• QST MF 740: Economics of FinTech
  The course covers the following topics: introduction to Blockchains and cryptocurrencies; contract theory for initial coin offerings; robo-advising; crowd wisdom; and privacy issues. Although the course introduces some Blockchain programming languages, e.g. Solidity, the emphasis of the course is on the economics of FinTech rather than on programming. Students are expected to be familiar with basic financial economics, econometrics, and stochastic processes.
• QST MF 770: Advanced Derivatives
  This course provides a comprehensive and in-depth treatment of valuation methods for derivative securities. Extensive use is made of continuous time stochastic processes, stochastic calculus and martingale methods. The main topics to be addressed include (i) European option valuation, (ii) Exotic options, (iii) Multiasset options, (iv) Stochastic interest rate, (v) Stochastic volatility, (vi) American options and (vii) Numerical methods. Additional topics may be covered depending on time constraints. (Mathematical Finance courses are reserved for students enrolled in the Mathematical Finance program.)
• QST MF 772: Credit Risk
  The derivatives market has experienced tremendous growth during the past decade as credit risk has become a major factor fostering rapid financial innovation. This course will provide an in-depth approach to credit risk modelling for the specific purpose of pricing fixed income securities and credit-risk derivatives. The course will explore the nature of factors underlying credit risk and develop models incorporating default risk. Types and structures of credit-derivatives will be presented and discussed. Valuation formulas for popular credit-derivatives will be derived. Numerical methods, for applications involving credit derivative structures and default risks, will be presented. (Mathematical Finance courses are reserved for students enrolled in the Mathematical Finance program.)
• QST MF 790: STOCH CALCULUS
  STOCH CALCULUS
• QST MF 793: Statistics for Mathematical Finance
  This course covers the fundamental principles of statistics and econometrics. It is mandatory for all tracks of the MSc. program. The course first reviews the needed concepts in probabilities, properties of random variables, the classic distributions encountered in Finance. Then, we cover the principles of random sampling, properties of estimators, e.g., the standard moment estimators (sample mean, variance, etc.). The next major topic is the regression analysis. We study the OLS and GLS principles, review their properties, in the standard case and when ideal assumptions are not correct. The course ends with a study of time series ARMA models and volatility models such as GARCH and Risk-Metrics. The course makes intensive use of the R package. (Mathematical Finance courses are reserved for students enrolled in the Mathematical Finance program.)
• QST MF 796: Computational Methods of Mathematical Finance
  This course introduces common algorithmic and numerical schemes that are used in practice for pricing and hedging financial derivative products. Among others, the course covers Monte-Carlo simulation methods (generation of random variables, exact simulation, discretization schemes), finite difference schemes to solve partial differential equations, numerical integration, and Fourier transforms. Special attention is given to the computational requirements of these different methods, and the trade-off between computational effort and accuracy. (Mathematical Finance courses are reserved for students enrolled in the Mathematical Finance program.)