The Program consists of five courses, each with approximately 24-26 hours of instruction. Courses are offered approximately every four to six weeks.

Investment Science
The foundations of the theory and application of modern quantitative investment analysis are presented from an engineering perspective. The course explores how investment concepts are used to evaluate and manage opportunities, portfolios, and investment products including stocks, bonds, mortgages, and annuities. Topics will include: deterministic cash flows (term structure of interest rates, bond portfolio immunization, project optimization); mean-variance theory (Markowitz model, capital asset pricing); and arbitrage pricing theory.

Options Theory and Practice
The financial industry was revolutionized by the development of the Black-Scholes method for pricing options. This fundamental concept has been extended in several ways and now is used to analyze and construct new financial products for various purposes. This course covers the theory of derivatives in general, but with special emphasis on the underlying theory of options. In particular, we will show various ways that stock behavior is modeled, including lattices and differential equations. The theory of pricing will be presented for both types of models. In addition to the model of stock prices, we shall also consider the important models of interest rate fluctuations and the related theory of pricing interest rate derivatives. The class will include many examples of various derivatives and the calculation of appropriate prices. Students will learn that there are several computational methods for finding prices, including lattices, Black-Scholes partial differential equations, and Monte Carlo methods. A special feature will be the theory of real options, which are options on physical commodities, projects, and other assets that are not traded securities. Participants in the class will have the opportunity to actually calculate the prices of several complex financial derivatives and using a laptop computer and the theory presented in this module.

Quantitative Credit
Credit risk is the distribution of financial loss due to default of a counter party in a financial contract. This class will review the key elements of stochastic point processes that are needed to develop a unified perspective of the quantitative analysis of credit risk. These tools will then be applied to the analysis, pricing and hedging of credit sensitive securities that are referenced on a single name, such as corporate bonds, credit default swaps, forwards and options on credit swaps, constant maturity credit swaps, loan credit swaps and asset backed credit swaps. We discuss in detail the calibration of a pricing model to the market term structure of credit swap rates and the estimation of a dynamic intensity model from time series of credit swap rates. We analyze the problem of forecasting a default event based on equity and equity option data, the testing of prediction systems, and the pricing of credit/equity hybrid derivatives such as equity default swaps. We then cover the mechanics and the pricing and hedging of credit derivatives that are referenced on a portfolio of names, such as cash collateralized debt obligations, credit indexes (CDX, LCDX, ABCDX, iTraxx), index and bespoke tranches, and forwards and options on these instruments. We also consider the analysis of portfolio credit risk measurement and management, including the prediction of portfolio default rates from historical event incidences. Most topics are accompanied by hands-on data-driven case studies, which exemplify model implementation.

Financial Decisions from an Emerging Market Perspective
This class explores the mechanism and regulations of financial markets, investment tools, and portfolio management strategies; especially, how to utilize the financial environment in corporate value management. The module also addresses the influence of regulation—especially the highly regulated environment in China--on financial decisions for firms. The course extensively uses cases to illustrate financial decision theory in different environments and under varying constraints. In this course, a comparison between the developed, emerging, and transitional markets is presented. Related concepts are defined and typical emerging market problems are analyzed.

Two-Sided Market: A New Model for Business Innovation
Traditional business models are based on a value chain structure where value is created and combined at each stage of the chain, from upstream to downstream. This is a good paradigm for traditional manufacturing industries. However, for many service industries, especially various financial service industries and many new web-based industries, value does not only flow from supplier to customer, value also flows from customer to supplier. A firm can serve as a platform that facilitates the value flow from one side to the other and creates a positive network effect: more customers on one side give more value to the other side and verse versa. For example, in the credit card industry, VISA and MasterCard are platforms with this characteristic: more merchants accepting a particular credit card will give both the holder of that card more value; and conversely more people holding a particular credit card give merchants more value in accepting that card. A brokerage trading firm is also a platform that facilitates the two-way value flow between consumers and firms offering financial products. The new model perspective gives rise to strategic innovations that counter conventional wisdom based on the value chain model. In this course, we shall apply the results derived from a two-sided market perspective to develop service innovation strategies for a financial service enterprise. Extensive cases are used to illustrate the concept.

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