Applied Mathematics Course Descriptions
MATH 481 Introduction to Stochastic Processes with Applications
This is an introductory course in stochastic processes. Its purpose is to introduce students into a range of stochastic processes, which are used as modeling tools in diverse fields of applications, especially in business applications. The course introduces the most fundamental ideas in the area of modeling and analysis of real World phenomena in terms of stochastic processes. The course covers different classes of Markov processes. It also presents some aspects of stochastic calculus with emphasis on the application to financial modeling and financial engineering. (Prerequisite: MATH 332 or MATH 333, MATH 475)
MATH 485 Introduction to Mathematical Finance
This is an introductory course in mathematical finance. Technical difficulty of the subject is kept at minimum by considering a discrete time framework. Nevertheless, the major ideas and concepts underlying modern mathematical finance and financial engineering will be explained and illustrated.
MATH 486 Mathematical Modeling I
This course is a general introduction to optimization problems. Linear programming: the simplex method. Elements of graphs and networks. Introduction to game theory. Applications. (Prerequisite: MATH 475 or instructor’s consent)
MATH 512 Partial Differential Equations
This course covers basic model equations describing wave propagation, diffusion and potential functions. Fourier transform, Green’s functions, eigenfunction expansions, perturbation techniques, multiple-scale methods, asymptotics, variational techniques, self-similar solutions. Prerequisite: MATH 400 or instructor’s consent.
MATH 513 PDEs for Finance*
This course provides an introduction to those aspects of partial differential equations and optimal control most relevant to finance. Linear parabolic PDEs and their relations with stochastic differential equations: the forward and backward Kolmogorov equation, exit times, fundamental solutions, boundary value problems, maximum principle. Deterministic and stochastic optimal control: dynamic programming, Hamilton-Jacobi-Bellman equation, verification arguments, optimal stopping. Applications to finance including portfolio optimization and option pricingare distributed throughout the course.
MATH 542 Stochastic Processes
This is an introductory course in stochastic processes. Its purpose is to introduce students into a range of stochastic processes, which are used as modeling tools in diverse fields of applications, especially in the risk management applications for finance and insurance. In addition, students will be introduced to some basic stochastic analysis.
MATH 543 Introduction to Stochastic Analysis
This course will introduce modern finite dimensional stochastic analysis and its applications in finance and insurance. The topics will include: (a) an overview of modern theory of stochastic processes, with focus on semimartingales and their characteristics; (b) stochastic calculus for semimartingales, including Ito formula and stochastic integration with respect to semimartingales; (c) stochastic differential equations (SDEs) driven by semimartingales, with focus on stochastic SDEs driven by Levy processes; (d) absolutely continuous changes of measures for Semimartingales, (e) some selected applications.
MATH 544Stochastic Dynamics
This is an introductory course in mathematical modeling by stochastic differential equations. It is especially appropriate for graduate students who would like to use stochastic methods in their research, or to learn these methods for long-term career development. Topics include random variables, mean and variance, Brownian motion, stochastic integration and Ito calculus, stochastic differential equations, random dynamics, numerical simulation, and applications to scientific, engineering and financial problems. Prerequisite: MATH 474, MATH 475 or equivalent.
MATH 565 Monte Carlo Methods in Finance
In addition to the theoretical constructs in financial mathematics, there is also a range of computational techniques that allow for the numerical evaluation of a wide range of financial securities. Monte Carlo and Quasi Monte Carlo techniques are computational sampling methods which track the behavior of the underlying securities in an option or portfolio and determine the derivative’s value by taking the expected value of the discounted payoffs at maturity. Recent developments with parallel programming techniques and computer clusters have made these methods widespread in the finance industry.
MATH 582 Mathematical Finance*
This course will introduce the student to modern continuous time mathematical finance. The major objective of the course is to present main mathematical methodologies and models underlying the area of financial engineering, and, in particular, those that provide a formal analytical basis for valuation and hedging of financial securities.
MATH 583 Quantitative Modeling of Derivative Securities
This course makes a connection between theory and application of mathematical finance and financial engineering.
MATH 584 Mathematical Portfolio and Investment Theory*
This course provides a mathematical view of mathematical theory and practice of optimal asset allocation.
MATH 586 Theory and Practice of Fixed Income Modeling*
The course covers basics of the modern interest rate modeling and fixed income asset pricing. The main goal is to develop a practical understanding of the core methods and approaches used in practice to model interest rates and to price and hedge interest rate contingent securities. The emphasis of the course is practical rather than purely theoretical. A fundamental objective of the course is to enable the students to gain a hand-on familiarity with and understanding of the modern approaches used in practice to model interest rate markets.
MATH 587 Theory and Practice of Modeling Credit Risk and Credit Derivatives*
This is an advanced course in the theory and practice of credit risk and credit derivatives.
MATH 589 Numerical Methods for PDEs
Finite difference method, finite volume method, spectral method; order of accuracy, stability and Fourier analysis of numerical scheme.
Management Science Course Descriptions
ECON 570 – Theory of the Firm
The basic objective of this course is to present in mathematical form the basic theories that comprise what is accepted today as orthodox microeconomics. Topics covered are economic models, comparative statistics applied to supply and demand, consumer choice, the economics of production, factor markets, market structure and resource allocation. (3, 0, 3)
MSC 530 – Probability & Statistics
The students will learn the fundamentals of probability and how to use this tool to solve common problems in industry. The course material includes a large variety of topics in business, engineering and management science. The topics include the fundaments of probability, random variables, transformations, discrete, continuous and joint distributions, normal, lognormal, bivariate and sampling distributions, parameter estimating methods, confidence intervals, hypothesis testing, and regression. (3, 0, 3)
MSC 534 – Queueing Theory
The students will learn how to solve many of the queueing problems that are found in common industry situations. The course will show how to formulate and solve the more complex queueing problems and the methods in probability that are used in formulating the queueing models. The fundamentals of matrix systems, priority systems, Erlang systems, simulated queues, stochastic processes and markoff chains are described. Prerequisite: MSC 530. (3, 0, 3)
MSC 538 – Simulation and Data Analysis
The objective is to learn how to generate solutions to problems, not known otherwise how to solve. The class emphasizes how a simulation project is formulated from computer programming. The student learns how to generate random responses for continuous, discrete, poison process and multivariate distributions. Methods to determine the probability distribution to use and the techniques to estimate the parameter values are shown along with examples. Ways to analyze the output results from transient, steady state and fixed event models are shown. The use of response surfaces, single-factor, multi-factor, fractional, and non-linear design of experiments, non-parametric methods and min and max distributions are given. Prerequisite: MSC 530. (3, 0, 3)
MSC 543 – Time Series
The course gives a cross section on the methods of forecasting – with emphasis on production and inventory. For each method, a description is given on the mathematical basis, the calculations to carryout and an example problem. The student becomes aware of the powerful tool of forecasting and how they apply in a wide range of business and industrial problems. The course covers filtering, horizontal, trend, seasonal, muli-location, smoothing, discounting, adaptive control, adaptive smoothing, trigonometric and Box-Jenkins forecast models and forecast errors. Also how the forecast are used in decision making in production and inventory operations. Prerequisite: MSC 530. (3, 0, 3)
MSC 550 – Topics in Quality Management
The understanding, development and implementation of total quality management approaches with a focus on customer satisfaction and economics of quality. Concepts and tools of design, quality of conformance and quality of performance will be discussed. Theoretical and empirical research will be the basis of this course. Prerequisite: MSC 530. (3, 0, 3)
MSC 560 – Optimization Techniques I
Optimization techniques, with the primary emphasis on linear programming, and application interspersed to illustrate the applicability of the optimization techniques. The majority of the course will be linear programming techniques, including the simplex-method and its variants, interior point algorithms, and duality and sensitivity analysis. The other part of the course discusses model formulation with integer variables and develops the theory of computational methods of integer linear programming: cutting plane, branch-and-bound, and Lagrangian relaxation methods. (3, 0, 3)
MSC 562 – Optimization Techniques II
The theory and computational methods of nonlinear programming is the majority of the course, including convex analysis and unconstrained methods, Kuhn-Tucker theory, saddle points and duality. Algorithms discussed include one for quadratic programming, linearly constrained, nonlinearly constrained, penalty and barrier methods. Prerequisite: MSC 560. (3, 0, 3)
MSC 564 – Optimization Techniques III
The course covers Dynamic programming formulation of deterministic decision process problems, analytical and computational methods of solution, application to problems of equipment replacement, resource allocation, scheduling, search and routing. Introduction to decision making under risk and uncertainty. Prerequisite: MSC 562. (3, 0, 3)
MSC 568 – Supply Chain Methods
The course gives a cross section on the production, distribution and retail stages along the supply chain. Emphasis is presented on the inventory needs at the various stages and the methods that are used in their control. A quantitative description on the tools and methods used are presented along with examples. The student becomes aware of the needs and techniques at the various stages across the supply chain. The course gives the fundamentals on forecasting, order quantity, safety stock, replenishment, stock-keeping units, production, reuseable inventory, assembly, logistics, multiple locations, low demand items, initial order quantity, all time requirements, late delivery and lost sales. Prerequisite: MSC 530, MSC 538. (3, 0, 3)
MSC 574 – Scheduling Theory
This course introduces students to theory, cases and current research in classic and new scheduling approaches. In addition to continuous scheduling systems found in the manufacturing sector and in the service sector, finite life project scheduling topics are also covered. New evolutionary optimization solution approaches such as Genetic Programming, Tabu Search and Simulated Annealing are explained in detail. Complexity theory, as applied to the modeling and the solution of large scale optimization problems, is also covered. Student initiated scheduling scenarios that may lead to further research or dissertation topics are encouraged and solved with the help of the professor. Prerequisite: MSC 564. (3, 0, 3) (3, 0, 3)
MSC 576 – Practicum in Teaching and Curriculum Skills
This course enables PhD students to address overall issues of pedagogy, as well as the development of personal classroom skills. The course covers curriculum development, sources of classroom materials and use of various teaching methods. (1 credit)
MSC 595 – Operations Management Seminar
This course focuses on the intersection of Economics and Operations Management. In particular, we examine the influence of micro-economic theory, particularly game theory, on analytical OM research. Topics covered will include incentives, information sharing, competition and coordination in inventory and supply chain management. The course material will revolve around classic and recent publications in well-known journals. The course is a discussion-based course. Prerequisite: Advanced standing and instructor’s consent. (3, 0, 3)
MS Finance Course Descriptions
MSF 501 Mathematics with Financial Applications
This course provides a systematic exposition of the primary mathematical methods used in financial economics. Mathematical concepts and methods include logarithmic and exponential functions, algebra, mean-variance analysis, summations, matrix algebra, differential and integral calculus, and optimization. The course will include a variety of financial applications including compound interest, present and future value, term structure of interest rates, asset pricing, expected return, risk and measures of risk aversion, capital asset pricing model (CAPM), portfolio optimization, expected utility, and consumption capital asset pricing (CCAPM).
MSF 502 Statistical Analysis in Financial Markets
This course presents the major conclusions of the econometric techniques used in finance. Ordinary least squares, maximum likelihood, generalized method of moments, and simulation methods are covered. These tools are presented through computer simulation of the various models, followed by detailed analysis of the distributions of estimators. Hypothesis testing is covered in detail. Particular attention is placed on the properties of various estimators when model assumptions do not hold. For students who qualify, a final project applying econometrics to a financial modeling problem may be chosen. Students not familiar with matrix algebra and elementary statistics should plan to make up the deficit early in the course. Additional lectures will be provided for these students.
MSF 503 Financial Modeling
Financial modeling in a spreadsheet environment is a pervasive feature of the modern workplace. In this course, students will learn how to implement financial models, using spreadsheet modeling and basic programming, via Microsoft Excel, VBA and Matlab. Financial models will include project valuation, bond pricing and hedging, option pricing via binomial trees and portfolio optimization. The course will also cover basic numerical techniques that are essential to financial modeling, including Monte Carlo simulation, root-finding and linear algebra.
MSF 504 Valuation and Portfolio Management
The course is a survey of asset pricing theory. The fundamentals of bond and option pricing are covered as well as the CAPM, APT and the Fama-French models. Excel spreadsheet modeling is used to illustrate and understand the concepts of Markowitz's Mean Variance Optimization, equity valuation, option pricing, and utility theory. The courses places a special emphasis on the relationship between macroeconomic conditions and investment opportunities.
MSF 505 Futures, Options and OTC Derivatives
This course provides the foundation for understanding the price and risk management of derivative securities. The course starts with simple derivatives, e.g., forwards and futures, and develops the concept of arbitrage-free pricing and hedging. Based upon the work of Black, Scholes, and Merton, the course extends their pricing model through the use of lattices, Monte Carlo simulation methods, and more advanced strategies. Mathematical tools in stochastic processes are gradually introduced throughout the course. Particular emphasis is given to the pricing of interest rate derivatives, e.g., FRAs, swaps, bond options, caps, collars, and floors.
MSF 506 Financial Statement Analysis
After reviewing the content of the major financial statements, the course examines ratios, inventories, long-lived assets, income taxes, debt, leases, and pensions, among other topics. U.S. practices are compared to practices in other major countries. This course is intended for those who will examine financial statements of outside organizations.
MSF 534 Corporate Finance
This course is an advanced introduction to modern corporate finance. Topics include cash flow forecasting, optimal dividend policies, mergers and acquisitions, structured finance, capital at risk, and the risk of adjusted return on capital. The philosophical foundation of the course is the concept of shareholder value added. Students will learn how financial decisions can contribute to the value of a modern corporation.
MSF 535 Investment Banking
This course covers the financing and formation process of private companies from product concept and angel investors to the Initial Public Offering. Exit strategies for private investments are discussed, including IPOs, mergers and acquisitions. Strategic and financial buyers play a key role in the valuation of a newly public or recently acquired firm. All of the players are discussed, including venture capitalists, entrepreneurs, investment bankers, attorneys, public shareholders, merger partners, institutional investors and private equity/buyout firms. Students will discuss business models; construct staffing and compensation schemes; practice valuation analysis; compare and contrast alternative financial sources; structure business plans; review the types of securities to offer; examine private placement processes; analyze negotiation strategies; and review the implications of financing terms and the role of venture capital and private equity investment in institutional portfolios. The challenges of completing mergers and integrating merged companies are also discussed. Sarbanes-Oxley, anti-trust requirements and other regulatory issues will be presented.
MSF 536 Marketing of Financial Products
Institutional financial products are the final manifestation of an evolutionary process that typically begins with advances in academic research. Examples include the development of index funds as a response to the concept of efficient markets, the development of structured financial products as a response to the concept of arbitrage pricing theory. This course explores the evolutionary process through a series of case studies focusing on companies that have introduced revolutionary financial products.
MSF 564 Financial Theory
This course covers the foundations of financial economics and the theoretical underpinnings of contemporary asset pricing models. We will explore the many uses and extensions of the fundamental pricing equation: , where Pt is the current price, is the pricing kernel or stochastic discount factor, and is a future random payoff. The “art” of asset pricing is in how one specifies the functional form of the pricing kernel. With different assumptions yields the Capital Asset Pricing Model, the Consumption-CAPM, the Black-Scholes-Merton option-pricing model, and many popular term structure models. The Consumption-CAPM does not fair well in the empirical literature motivating the study a promising group of next-generation risk/return models. The latter part of the course will be devoted to continuous-time asset pricing of options and the modeling of the term structure. The emphasis will be on risk-neutral, Martingale pricing methods, rather than solving partial differential equations. This material is a theoretical complement to the Computational Finance and Financial Modeling sequences.
MSF 565 International Finance Theory
This course will focus on the determination of prices, interest rates and exchange rates within the context of neo-classical equilibrium models. The theoretical foundations of the course will be supplemented by extensive exercises in econometric testing of maintained hypotheses and exercises in real time trading.
MSF 566 Time Series Analysis
This course develops a portfolio of techniques for the analysis of financial time series. Distribution theory covers the normal, Student T, Chi-squared and mixture of normals models. Technical analysis covers a variety of trading rules including filters, moving averages, channels and other systems. The first two topics are then combined into an analysis of non-linear time series models for the mean. The course concludes with a review of volatility models including GARCH, E-Garch and stochastic volatility models.
MSF 567 Bayesian Econometrics
Most statistical applications in finance require that the forecasting models be revised in response to the arrival of new information. This course develops the Dynamic Linear Model (DLM) as an updating model based upon Bayesian decision theory. Applications of the DLM, including regressions, autoregressions, and exponential trend models will be covered. Special emphasis will be given to the development of intervention and monitoring systems and the use of simulation methodologies. Students not familiar with matrix algebra and elementary statistics should plan to make up the deficit early in the course.
MSF 524 Models for Derivatives
In this course, students will learn mathematical and computational methods that are applicable to the pricing and risk management of derivatives. These will be implemented in Matlab. The class will include an introduction to option pricing theory, with some basic stochastic calculus, the Black-Scholes partial differential equation, risk-neutral valuation and hedging and portfolio replication. We may also touch on more advanced topics, such as jump processes and stochastic volatility. The course will focus on important numerical techniques used in finance, including variance reduction techniques in Monte Carlo Simulation, finite difference methods applied to partial differential equations, interpolation procedures (e.g. splines) and optimization theory applied to model calibration. These methods will be applied to price exotic options and to model volatility surfaces.
MSF 525 Interest Rates, Term Structure and Credit Models
Upon completion of this course, students should know the strengths, weaknesses, appropriate uses and ways of implementing the major term structure models that are in common use. The course will cover bootstrapping of forward curves, principal component analysis and review basic fixed income derivatives (swaps, swaptions, caps and floors). We will then implement short rate models, such as Ho-Lee, Black-Derman and Toy, and Extended Vasicek/Hull-White, followed by the Heath-Jarrow-Morton model and market rate models. The course will conclude with a brief introduction to credit modeling, covering risk-neutral default probabilities, credit default swap pricing, and structural and reduced-form models of credit risk. Students will implement these term-structure models in Excel/VBA and Matlab.
MSF 526 Computational Finance
Because of the widespread adoption of computer trading platforms, the computational efficiency of financial models has become an issue of increasing concern. This course concentrates on numerical techniques for pricing derivatives found in modern markets. It includes an extensive treatment of numerical solutions of the Black-Scholes equation, using techniques such as efficient binomial/trinomial trees, finite-difference solutions of partial differential equations and Fast Fourier transforms. We will cover optimization theory as used in model calibration. We will apply these methods to various pricing models, such as stochastic volatility models and models used to price credit derivatives. Model implementation will be in Matlab.
MSF 591 Global Financial Markets
This course will enable the student to understand the basics of financial markets and how they function in the global arena. The student will learn how the equities market, the bond market, the money market, the foreign exchange market and the derivatives markets are set up and operate. We will focus on the instruments, the players, the jargon, the details of the trade, and the institutional framework for each market. We cover both OTC and exchange-traded markets, and explore the dramatic transformation of these markets. The student will learn how each of these markets operates in the US, but will also learn how practices differ in Europe, Asia and Latin America.
MSF 592 Global Investment Strategies
This course provides an integrated framework describing the investment process in global markets. It starts with explanations of what drives the foreign exchange markets and the forecasting techniques to predict currency moves. Discussions include the benefits of international diversification, and studies in global equity markets, emerging markets stocks and bonds, and the global bond markets.
MSF 593 Market Microstructure
Market microstructure is one of the youngest but most rapidly growing areas of finance. It focuses on the organization of traded markets, including those for equities, bonds, money market instruments, foreign exchange and derivatives (including futures, options and swaps). It explores the concepts of liquidity, transparency, the information content of bids, offers and trades, information asymmetries, order flow externalities, principal-agent problems, the design of markets, the rules of markets, the volatility of markets, the failure of markets, the regulation of markets and the costs of trading. Empirical work in this area typically involves huge datasets. Students will leave this course with a thorough understanding of the structure of the markets in which they will likely spend their careers.
MSF 574 .NET and Database Management
The course provides students with a comprehensive knowledge of .NET (VB and C#) programming, relational database design and SQL as they apply to quant finance and real-time trading. Specifically, topics covered include the .NET framework and libraries, ADO.NET, OOP, generics, market data feeds, XML and the Unified Modeling Language, as well as an overview of the hardware and network infrastructure necessary to enable electronic trading.
MSF 575 C++ with Financial Applications
This course presents the C/C++ programming language. Students learn the language from the ground up, from data types, to functions, arrays, classes, dynamic memory management, data structures and the Standard Template Library. Object-oriented programming is also discussed, including a review of commonly used design patterns. The focus is to understand C/C++ as it applies to financial mathematics and several practical examples from computational finance are presented.
MSF 576 OOP and Algorithmic Trading Systems
In this course, students learn advanced programming topics in .NET for real-time financial applications and automated trading systems, including multithreading, sockets, APIs, synchronization, the FIX and FAST protocols, and object oriented design for event-driven applications. Also, project management and software quality are covered in depth. Lastly, topics related to latency in real-time financial applications and alternative network architectures are also discussed. Students are expected to propose, design, document and develop an original project combining concepts from quantitative finance and trading strategy (presented in other courses) into a working software application.
MSF 544 Equity Valuation
This course covers the various models available for equity valuation. It includes discussions of the dividend discount model, Porter analysis, DuPont decomposition of ROE, sustainable growth rates, earnings quality and accounting fraud, and relative valuation measures such as price/earnings and price/sales. The major deliverable for this course is a comprehensive analysis of a public company, modeled after the well-known Merck case study. Also required is a complete analysis of a convertible bond.
MSF 545 Structured Fixed Income Portfolios
Fixed income instruments differ from equities because the cash flows from fixed income instruments are known in the absence of issuer default. As a result, fixed income portfolios tend to have a longer time horizon, tend to be more highly leveraged, and tend to use derivatives for hedging relative to equities. This course develops portfolio management procedures for fixed income portfolios. The course begins at the short end of the curve with multi-currency portfolios of short-term non-deliverable swaps. The course then proceeds out the maturity spectrum to consider investment strategies based upon the shape of the yield curve. Concepts developed in the course will be tested using a simulated trading environment.
MSF 546 Quantitative Investment Strategies
This course develops the primary quantitative tools used in the portfolio selection process. The applied focus of the course centers on the process of moving from a data set of historical information to the formulation of a forecasting model, the estimation of mean-variance efficient portfolios, and the testing of efficiency hypotheses within an in-sample and post-sample setting. The course covers the estimation of efficient portfolios, factor models, forecasting models, and risk analysis.
MSF 547 Hedge Funds (1/2 Semester)
This course explores hedge funds and how they differ from regulated mutual funds. Topics covered include hedge fund business models and legal structures, performance and fee calculations, funds of funds, and risk management techniques. Further, students practice alternative trading strategies such as distressed investing, event driven trading, convertible bond, fixed income and merger arbitrage, and relative value, equity hedged, and market neutral strategies.
MSF 548 Real Estate (1/2 Semester)
This course will introduce students to real estate ownership and financing. The importance of legal issues will be discussed, including zoning, types of ownership, taxes and development regulations. The course may include several case studies to enhance students' skills in evaluating the economics of proposed real estate development projects. As a part of these studies, students will analyze compound interest, mortgage loans, amortization and internal rates of return to support their investment decisions. Finally, students will understand the importance of capital markets and institutional investment in real estate, including mortgage-backed securities, conduit loans and Real Estate Investment Trusts (REITs).
MSF 549 Commodities and Managed Futures
Commodity markets have experienced dramatic growth and increased institutional investment in recent years. This course explores cash and futures markets in energy, grains, metals and soft commodities, as well as equity investments in commodity related firms. Students will explore the role of hedgers, speculators and institutional investors in commodity markets. The value of commodities in the institutional portfolio will be presented, which may allow hedging against inflation and the risks of declining stock and bond prices. Commodity trading advisers, commodity pool operators and the managed futures industry will be discussed. These fund managers initiate both long and short positions in futures markets, typically constructing portfolios from either a systematic or discretionary perspective.
MSF 554 Market Risk Management
This course introduces the importance of financial risk management by developing practical risk measurement tools. The risk measurement aspect of the course begins with the development of the Value-at-Risk (VaR) methodology for financial instruments traded in open markets including equities, bonds, foreign currencies and their derivatives. The course develops analytic VaR models for instruments with non-linear payoffs and non-normal distributions and it also develops simulation methodologies for risk analysis. Statistical tools in volatility forecasting, tail events, and expected shortfall are introduced as appropriate. The emphasis of the course is on market risk, but in addition to the traditional analysis of trading rooms, the course also considers regulatory and compliance risk, corporate risk and risk analysis for investment managers.
MSF 555 Credit Risk Management
The extensive use of leverage by individuals, corporations, hedge funds and private equity managers has led to a significant increase in the demand for models that analyze credit risk exposures. For many users, the credit risk function has evolved from models used to analyze the quality of an individual borrower to models that aggregate exposure across borrowers, industries and geographic regions. This course provides an extended overview of the exciting and rapidly developing field of credit risk analysis.
MSF 556 Enterprise Risk Management
This course follows up on FIN 581 (Market Risk Management). It focuses on the other two main silos of risk in the financial industry, namely, credit risk and operational risk. The course will also discuss asset and liability management, interest risk management, integration of credit risk and market risk, regulatory and compliance issues, and performance measurement and capital management. The quantitative aspects of the course include: volatility and correlation modeling, Monte Carlo simulation, stress-testing and scenarios analysis, extreme and tail events modeling.
MSF 584 Equity and Equity Derivatives Trading
This course will provide students with an opportunity to learn the latest Equity Trading Strategies used by large banks, brokerages and hedge funds. The instructor will present strategies on equity option trading, pairs trading, program and basket trading, risk arbitrage trading, structured product trading, and dispersion trading (time permitting). Equity trading theory and practical examples will be discussed. Students will be required to structure and adapt equity trading positions based on a range of actual and theoretical market conditions. In addition, students will collaborate with each other and the course instructor to analyze and evaluate the implementation of the above-mentioned strategies.
MSF 585 Fixed Income Trading Strategies
This course will present basic trading concepts related to fixed income instruments. Also covered will be the analysis of repos and fixed income derivatives, such as forwards and futures, options and spreads. Trading strategies will be discussed, including yield curve strategies, basis trading, and various types of spread trading using many different instrument types. Students will make trading decisions and modify their portfolios in order to familiarize themselves with the instruments and techniques introduced. Swaps, Swaptions, Caps and Floors will be introduced, time permitting.