Courses

• GSM IS 832: Networks and Social Media
  As the penetration of online and mobile technologies continues to advance, instant messaging, mobile phone communication, micro-blogs, and online social networks are shaping how we interact with the world and each other. The explosion of data surrounding these interactions is a powerful microscope that permits research into behaviors and their social and economic outcomes at an unprecedented scale and level of detail orders of magnitude greater than what was previously possible. The emerging field of network science describes these interconnections and gives us tools to understand their importance to our natural, social and business environments. This course will introduce the theory and practice of network science and cover numerous applications in the realms of business, health and politics. We will explore questions such as: How can firms and policy makers harness the power of social media? How can we promote or discourage population level change? How do behavioral contagions form and become viral? What is the value of a tweet? Topics may include: network structure and dynamics; social network analysis; weak and strong ties; structural holes; homophily; community structure; information propagation and cascades in networks; the dynamics of influence; social and behavioral contagions; word of mouth; viral product design; strategic competition; crowdsourcing; incentives and gamification; and others.
• GSM IS 841: Advanced Business Analytics: Data Mining
  The widespread proliferation of IT-influenced economic activity leaves behind a rich trail of micro-level data about consumer, supplier and competitor preferences. This has led to the emergence of a new form of competition based on the extensive use of analytics, experimentation, and fact-based decision making. In virtually every industry the competitive strategies organizations are employing today rely extensively on data analysis to predict the consequences of alternative courses of action, and to guide executive decision making. This course provides a hands-on introduction to the concepts, methods and processes of business analytics. We will learn how to obtain and draw business inferences from data by asking the right questions and using the appropriate tools. Topics to be covered include data preparation, data visualization, data mining, text mining, recommender systems as well as the overall process of using analytics to solve business problems, its organizational implications and pitfalls. Students will work with real world business data and analytics software. Where possible cases will used to motivate the topic being covered. Prior courses in data management and statistics will be helpful but not required.
• GSM IS 854: Practicing IT Strategy, Management and Delivery
  For future business leaders who want to understand, influence and leverage technology investments more effectively. The course provides effective strategies, pragmatic options, and leading practice alternatives for linking Business and Technology Strategies, defining effective governance and organization models, and successfully delivering new technology innovation. Students will master the complex methods and practices needed to frame a problem and propose an actionable solution that would be expected from future Business Executives and Technology Managers. Students will master the complex methods and practices to frame a problem and propose an actionable solution that would be expected from Business Executives (e.g., CEO, Marketing Executive, CIO, CFO) and Technology Executives (e.g., Product Manager, Consultant, Program Manager, Sales).
• GSM IS 855: Digital Transformation: Immersive Interactions and Insights at Silicon Valley
  This course will be a one week intensive held in Silicon Valley. The course is designed to achieve two objectives. First, to develop an appreciation for the role of Silicon Valley in Digital Innovation and, secondly, to examine how digital innovations are impacting key shifts in specific sectors. This year, the course will focus on three sectors; Healthcare, Energy and Digital Content/education/media. Students will be placed into teams and be expected to develop specific insights as the basis to engage in interactions with corporate executives, alumni and follow classmates. Teams will also visit leading companies involved in each sector and develop and present their team's perspective on key digital trends and leadership challenges for their sector.
• GSM IS 883: Designing Systems for Data Management
  The first objective is to introduce the student the concept of design in information systems. Although the design concepts covered largely focus on data management, it will include high level systems design concepts as well. The second objective of this course is to introduce the student to the practical applications of databases and database management systems. The students will learn the fundamentals of data management starting with the basics of data design. The students will learn querying and managing the data in a database, defining the structures for storing data, and implementing business rules in relational databases using the Structured Query Language (SQL). The two objectives will tie in together as the students will be expected to integrate systems design with data design to design a prototype information system. This exercise will walk the students through the process of eliciting requirements, defining the scope, designing a restricted set of functions, designing the database, implementing the database, and explaining how restricted set of functions will use the data. The programming requirements will be very minimal. Besides the basics of data management, this course will also cover relevant ?in? topics in data management such as database security, data quality management, and data auditing (if time permits).
• GSM IS 889: Telecommunications and Business Networks
  Examines the data communication hardware and software characteristics that are relevant to the applications software designer and presents a general overview of communications network design. Topics include issues in the design and use of both local area networks and wide area networks, the impact of communications technology on organizations and trends in the communications industry are studied.
• GSM MF 702: Fundamentals of Finance
  This course covers such topics as: financial markets (bonds, stocks, derivative securities, forward and futures contracts, exchanges, market indexes, 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, the risk-premium puzzle), the Capital Asset Pricing Model, and Value-at-Risk.
• GSM MF 703: C++ Programing for Mathematical Finance
  In-depth discussion of object-oriented programming with C++ for mathematical finance. 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.
• GSM MF 728: Fixed Income Securities
  Term structure models are the basis for the valuation of any financial assets. Fixed income instruments are by far the most important asset class in today?s financial markets. The course focuses on the valuation, hedging, and management of fixed income securities. Basic theoretical and empirical term structure concepts are introduced. Basic short rate models are presented. The Heath-Jarrow-Morton term structure methodology is discussed in detail. Consistency requirements for the construction of term structure curves are presented. The Market LIBOR model and its application for the valuation of futures, forwards, swaps, caps, floors and swaptions, and other interest rate derivatives will be introduced. The course emphasizes both theoretical and practical aspects of term structure models and fixed income securities.
• GSM MF 730: 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 focuses on empirical features and practical implementation of dynamic portfolio problems.
• GSM MF 731: Corporate Risk Management
  This course provides an introduction to modern methods of risk management. Lectures cover risk metrics, measurement and estimation of extreme risks, management and control of risk exposures, and monitoring of risk positions. The impact of risk management tools, such as derivative securities, will be examined. Issues pertaining to the efficiency of communication architectures within the firm will be discussed. Regulatory constraints and their impact on risk management will be assessed. 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.
• GSM 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.
• GSM MF 772: Credit Risk
  This course covers asset pricing models (preferences, utility functions, risk aversion, basic consumption model, the mean-variance frontier, factor models, and robust preferences); and options pricing and risk management (arbitrage pricing in a complete market, delta-hedging, risk measure, and value-at-Risk).
• GSM MF 792: Stochastic Methods of Mathematical Finance I
  This course provides the necessary background for using the general tools of stochastic calculus in the domain of mathematical finance. The topics include: information structures and financial markets (sample spaces, event trees, ó-algebras, and partitions), random variables and random processes, expected values and conditional expected values, probability distributions and change of measure, convergence of random variables, martingales and convergence of martingales, and the Brownian motion process.
• GSM MF 793: Statistical Methods of Mathematical Finance
  This course provides an introduction to R and Exploratory Data Analysis, Time Series Analysis, Multivariate Data Analysis, and Elements of Extreme Value Theory. This course also covers an array of statistical techniques used for simulation, parameter estimation, and forecasting in Finance.
• GSM MF 794: Stochastic Optimal Control and Investment
  Classical problems for optimal control (Merton?s problem, etc.), the Hamilton-Jacobi-Bellman equation, the connection between asset pricing and free-boundary problems for PDEs, optimal exercise of American-style derivatives, optimal investment decisions, valuation of real options, policy intervention, Pontryagin?s principle of maximum, and applications to some macroeconomic models.
• GSM MF 795: Stochastic Methods of Mathematical Finance II
  This course focuses on developing the necessary tools from stochastic calculus to be applied in the mathematical theory of finance. Topics include: stochastic integration, equivalent changes of probability, fundamental theorems of finance, stochastic differential equations, pricing and hedging of contingent claims, short-rate models, introduction to American options, and changes of numeraire.
• GSM MF 796: Computational Methods of Mathematical Finance
  This course develops algorithmic and numerical schemes that are used in practice for pricing and hedging financial derivative products. Focus is given on Monte-Carlo simulation methods (generation of random variables, exact simulation of stochastic processes, discretization schemes for pricing and hedging of contingent claims, variance reduction techniques, and estimation of sensitivities with respect to model parameters), model calibration to market data, and estimation of model parameters.
• GSM MF 820: Quantitative Strategies and Algorithmic Trading
  In an increasing era of computerized trading, quantitative strategies are handling an ever greater share of market trading. This course details the use of quantitative methods in the development and implementation of trading strategies in the equity and debt markets with focus on both the market-making and proprietary trader perspectives. Both end-of-day and intraday strategies will be discussed with emphasis on the development, back testing methodology, and performance attribution of any strategy. Students will be grouped into market making and proprietary trading teams with the goal of generating positive P&L against each other.
• GSM MF 921: Topics in Dynamic Asset Pricing
  This course provides a selective survey of the methods and results of classic papers and recent advances in the asset pricing literature. Extensive use is made of continuous time techniques. Topics will include state dependent preferences, long run and business cycle risks, money, term structure models, transaction costs, intermediation.

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