NYU Stern

MBA Courses

IOMS MBA Courses

Two IOMS courses are included in the MBA Core:
  • COR1-GB.1305 Statistics and Data Analysis
  • COR1-GB.2314 Operations Management

IOMS MBA Courses can be applied towards the following specializations:
  • Business Analytics
  • Digital Marketing
  • Entertainment, Media and Technology
  • Financial Systems and Analytics
  • Management of Technology and Operations
  • Quantitative Finance
  • Supply Chain Management and Global Sourcing

View the NYU Stern Academic Affairs page to determine which courses count for which specializations.

Click on the tabs above to view individual course descriptions.

Information Systems MBA Courses

The Stern School of Business has always been a leader among management schools in teaching and research on information technology in business. In the current climate of rapid globalization and electronic commerce, an understanding of why and how information technology is driving changes in markets and businesses is essential for every business manager. Increasingly, many of the strategic and day-to-day decisions general managers face involve information technology.

The central question that Information Systems (IS) courses address is the following: Why do some organizations get value from their information technology investments while others do not? One set of courses answers this question primarily by examining how fundamental changes in market structure inducted by new technologies impact business models. The second set emphasizes the enabling potential of information technologies through increased efficiency or business intelligence. The third set focuses on the effective management of the information assets of organizations, be they internal, outsourced, or joint ventures.

The IS area provides a crucial part of business education necessary for students seeking careers in a variety of industries, from finance to management consulting. A specialization in information systems requires 9 credits in the IS courses listed on the Courses link to the left. Some of these courses also satisfy other specializations, as specified.

Course Descriptions -- M.B.A. Courses

INFO-GB.2317 (B20.2317) Information and Internet Technologies
INFO-GB.2318 (B20.2318) Digital Strategies
INFO-GB.2350 (B20.2350) Trading Strategies and Systems
INFO-GB.3339 Being Digital: Search, Social Media, Crowdsourcing (mini)
INFO-GB.3155 (B20.3155) Global Outsourcing Strategy (also offered as INFO-GB.3355)
INFO-GB.3322 (B20.3322) Design and Development of Web and Mobile Apps
INFO-GB.3335 (B20.3335) Electronic Communities
INFO-GB.3336 (B20.3336) Data Mining for Business Intelligence
INFO-GB.3338 (B20.3338) Business Strategy for the Digital Economy
INFO-GB.3347 Digital Marketing
INFO-GB.3350 (B20.3350) Financial Information Systems
INFO-GB.3351 (B20.3351) Risk Management Systems
INFO-GB.3355 (B20.3355) Global Sourcing and Open Innovation
INFO-GB.3356 (B20.3356) Business Process Design and Implementation
INFO-GB.3362 (B20.3362) Emerging Technology and Business Innovation


Information and Internet Technologies
INFO-GB.2317 (B20.2317)
3 credits

This course introduces the technology concepts underlying current and future information systems, with an emphasis on Internet-related technologies. It begins with the fundamentals of computer systems, databases, and networking. Special emphasis is given to technologies that underlie the World Wide Web and e-commerce, including HTML, XML, emerging interoperability standards, security, search, information retrieval, agent technologies, data warehousing, and data mining. It provides both a refresher to basic concepts as well as coverage of cutting-edge technologies. It assumes no prior knowledge of technology or programming, beyond experience with personal computers. Course requirements include homework assignments and a term paper.

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Digital Strategies
INFO-GB.2318 (B20.2318)
3 credits

The course explores the role of information technology (IT) in corporate strategy with specific attention paid to the Internet. Different Internet business models are identified and are used to explain competitive practices. Cases and lectures illustrate how technology is used to gain and sustain a competitive advantage. The course also describes different Internet technology infrastructures and identifies issues in managing a firm's technology as a strategic asset.

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Trading Strategies and Systems
INFO-GB.2350 (B20.2350)
3 credits
Prior to a major course revision, this course was offered as B20.3350 Financial Information Systems.

Course Description: As financial markets become more electronic and more liquid, a higher degree of knowledge about systems and analytics is required in order to compete. This course teaches students how to use the information emanating from the markets for decision making and building and implementing systematic computer-based models for trading. The course begins with a description of the financial markets, specifically, equity, currency, fixed income, and commodities, and the systems that enable them. We consider exchanges, ECNs, and other dealer markets and the information that emanates from them. This provides the backdrop for the bulk of the course which covers the design, evaluation and execution of trading strategies that are commonly used by professionals in the various markets. There is increasing interest in particular, on /systematic/ trading strategies and execution systems because of their scalability and transparency. The course should be of interest to students across the financial services industry. It will not transform you into a trading expert, which takes considerable effort, time, and pain. It will, however, bring the concepts of risk and return alive by working with real data and exercises, and through industry experts describing their approach to fund management and administration. More generally, the course should give you a clearer appreciation on the fact that understanding markets is a theory building exercise, where professionals spend a lot of time in understanding emerging market phenomena with the objective of translating their insights into profitable strategies. These concepts are useful regardless of your specific interest in the financial industry, i.e., whether you intend to be a trader, risk manager, controller, salesperson, or analyst.

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Being Digital: Search, Social Media, Crowdsourcing
INFO-GB.3339
3 credits

The emergence of search engines over the last decade change drastically the business landscape in many industries. Traditional business models are now completely outdated, other business models are deeply transformed, and many new models emerge now, which are based on the unprecedented access to vast amounts of information. In particular, this course will examine how search technologies affect business and society. Students will first gain an understanding of the basics of how search engines work, and then explore topics such as search ranking, spam and anti‐ efforts, search engine marketing, keyword auctions, collective intelligence, search and privacy, intellectual property, and search of blogs and online communities.

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Global Outsourcing Strategy
INFO-GB.3155 (B20.3155)
3 credits
This course focuses on professional services outsourcing and offshoring including examples from IT outsourcing (ITO), business process outsourcing (BPO), and Knowledge Process Outsourcing (KPO) as well as on getting innovation from outside the firm by engaging consultants and using crowdsourcing websites. The course covers three broad areas: (1) global sourcing models, (2) the design and implementation of a sourcing strategy; and (3) open innovation and crowdsourcing. It draws on economics, international business, and management theories as well as real-world examples from managerial practice. The course will introduce you to frameworks for deciding which areas of activities to keep inside the firm and which to source out, how to choose the right partner and geography, how to structure contracts and relationships to achieve desired outcomes, how to manage projects and teams across organizational, national, spatial, and temporal boundaries, and, finally, how to engage the crowd to achieve best results. Students are given opportunities to research a situation of their choice in the area of global sourcing.

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Design and Development of Web and Mobile Apps
INFO-GB.3322 (B20.3322)
3 credits
Prerequisites: B20.2317 or equivalent background as well as the ability to program in some programming language.

The World Wide Web and the new technologies and standards surrounding it have dramatically changed the way systems are developed and used in organizations and markets. This course covers the issues and concepts in developing data-driven Web sites. Students evaluate a variety of different Web development approaches and architectures, including the common gateway interface model, Java, Active Server Pages, Dot Net, and Web Services. A variety of alternative development approaches are compared, looking at issues such as the development environment and the security, performance, scalability, and maintainability of systems developed with the different approaches. The class is divided into student teams. Each team implements a small system using one of the supported technologies and evaluates their experience. Students should have the ability to build a simple Web page and be proficient with common Microsoft office business applications, especially ACCESS. There is light programming, which is used as an example of how to build dynamic Web pages for B2C and B2B sites. Assignments include both Active Server Pages as well as J2EE. Unix, Windows 2000, and Linux platforms are available to host projects.

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Electronic Communities
INFO-GB.3335 (B20.3335)
3.0 credits

An electronic community is generally defined as a group of people organized online around a topic or issue. This course introduces student designing, building, managing, and maintaining online communities for businesses. This includes company websites, managed social media outlets such as social networks, and participating communities such as review sites. Students will identify the target audience, business objectives, strategy, and technologies needed to run a successful online community for a real business. Examples and case studies will be discussed and analyzed to identify the characteristics of effective communities and methods for evaluation. To provide cutting edge perspectives, several industry professionals will be invited to lead class discussions on special topics. The format of the course is blended; course meetings are held in the classroom in addition to scheduled real-time online meetings.

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Data Mining for Business Intelligence
INFO-GB.3336 (B20.3336)
3 credits

Businesses, governments, and society leave behind massive trails of data as a by-product of their activity. Increasingly, decision makers rely on intelligent systems to analyze these data systematically and assist them in their decision making. In many cases, automating the decision-making process is necessary because of the speed with which new data are generated. This course connects real-world data to decision making. Cases from finance, marketing, and operations are used to illustrate applications of a number of data visualization, statistical, and machine learning methods. The latter include induction, neural networks, genetic algorithms, clustering, nearest neighbor algorithms, case-based reasoning, and Bayesian learning. The use of real-world cases is designed to teach students how to avoid the common pitfalls of data mining, emphasizing that proper applications of data mining techniques is as much an art as it a science. In addition to the cases, the course features Excelbased exercises and the use of data mining software. Real-world datasets are included as an optional data mining exercise for students interested in hands-on experimentation. The course is suitable for those interested in working with and getting the most out of data as well as those interested in understanding data mining from a strategic business perspective. It will change the way you think about data in organizations.

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Business Strategy for the Digital Economy
INFO-GB.3338 (B20.3338)
3 credits

Digital markets have profound differences from traditional markets. For instance, copies of digital goods can be produced at almost zero cost, and online markets enable buyers to easily compare the offerings of many different sellers. The goal of this course is to provide students with a fundamental understanding of digital markets and to equip them with the concepts and principles necessary to understand current and future developments in digital markets; to separate the value from the hype; and to function in and take advantage of these markets. The first half of the course focuses on the markets for digital goods such as software, news, music, or movies, which can be delivered through the Internet, and covers their delivery infrastructure, pricing, digital rights management, and economics. The second half of the course focuses on online marketplaces, covering consumer search, advertising, product differentiation and customization, competitive dynamics, and the impact of the Internet on industry structure, organizations, markets, and business-to-business commerce.

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Digital Marketing NEW COURSE, SPRING 2012
INFO-GB.3347
3 credits

This core course of the Digital Marketing specialization at Stern addresses a fundamental business question of the digital age: how to increase shareholder value through digital media. This is a question that all firms are currently struggling to answer in an era where they can, for the first time, truly engage in rapid two-way conversations with potential and current customers. If firms ask themselves the question “how do we attract and retain customers?” chances that the answer to this looks very different from what it was a decade ago when the Internet was still in its infancy. At the current time, reputations can be made or destroyed within minutes, presenting great opportunity as well as a high degree of risk.

The focus of the course is on how to make firms more intelligent in how they conduct business in the digital age. This requires a fundamental understanding of the technologies and platforms that form the backbone of electronic commerce, the ability to govern and leverage large amounts of data that are generated as a by-product of electronic interactions, and sociological norms and individual preferences. Measurement plays a big role in this space. As a modern-day famously remarked “In God we believe, everyone else please bring data.”

The course will feature (at least) two instructors who will provide complementary perspectives on branding, analytics, social media, and strategy. There will be several (roughly 6) senior executives from companies providing a detailed look at what their companies are doing in the digital space. There will be several assignments and a term project for this course. The project, done in teams, will involve the assessment of the "Digital IQ" of a firm of your choice and a set of actionable recommendations for the firm based on your audit. Considering the nature of the material there is no textbook for this course. Materials will consist of readings, links to websites, and datasets.

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Financial Information Systems
INFO-GB.3350 (B20.3350)
3 credits

As financial markets become more electronic and more liquid, a higher degree of knowledge about systems and analytics is required in order to compete. This course teaches students how modern financial markets function as a network of systems and information flows, and how to use information technology for decision making in trading and managing customer relationships. Information systems serve two purposes in the financial industry. First, they facilitate markets and their supporting services such as payment, settlement, authentication, and representation. Second, they facilitate or engage in making decisions such as when and how much to invest in various instruments and markets. The first part of the course describes how systems facilitate various kinds of payment and settlement mechanisms, enable financial markets such as exchanges and ECNs, and support inter-institution communication. The second part of the course describes how traders, analysts, and risk managers use systems to cope with the vast amounts of data on the economy, markets, and customers that flow into their systems each day. It covers automated trading systems and other types of customer-oriented analytic systems that are becoming increasingly intelligent in how they make or support decisions. The course features a mix of case studies, Excel-based illustrations and assignments, and the latest industry tools. It is particularly suited for finance and marketing students interested in understanding information technologies in financial services from a practical career standpoint.

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Risk Management Systems
INFO-GB.3351 (B20.3351)
3 credits

In today's world of complex financial engineering, rising volatility, and regulatory oversight, prudent management increasingly requires understanding, measuring, and managing risk. Banks, securities dealers, asset managers, insurance companies, and firms with significant financing operations all require real-time, enterprise-wide risk management systems for handling market, credit, and operational risk. Such systems establish standards for aggregating disparate information, including positions and market data and operational risk, calculating consistent risk measures, and creating timely reporting tools. This course is directed toward both finance and technology oriented students who are interested in understanding how large-scale risk systems need to be evaluated, acquired, architected, and managed. It identifies the business and technical issues, regulatory requirements, and techniques to measure and report risk across an organization or market.

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Global Sourcing and Open Innovation
INFO-GB.3355 (B20.3355)
3 credits

Exporting of white collar jobs is receiving increasing attention both at business and political levels. Whether you are a proponent or an opponent of this trend, you need to know how to make sound decisions about your global sourcing strategy. This course focuses on services outsourcing, with special attention paid to Information Technology (IT) outsourcing - currently the largest area of global professional services outsourcing. The course covers two broad areas:
  • Global Services Sourcing Landscape: Past, Present, and Future
  • Developing Managerial Competence in Global Sourcing: Strategy and Management
This course draws on economic and management theories as well as real world examples from managerial practice. The goal of the course is to help you identify the challenges of global sourcing as well as the costs, risks, rewards, and strategies involved in making sourcing decisions.

Some of the topics covered are:
  • Historical and economic perspectives on outsourcing and offshoring.
  • Trade-offs among global sourcing models (Domestic Outsourcing, Offshore outsourcing, Domestic In-sourcing Captive Models).
  • Types of global outsourcing services (IT, BPO, Infrastructure)
  • Developing an outsourcing strategy
  • Sourcing in different geographies
  • The vendor landscape (local/multinational, niche players/generalists)
  • Legal Issues: Contracts, Taxes, IP, Privacy, Compliance
  • Critical success factors in managing outsourcing relationships
  • Managing distributed work teams: overcoming distance, time, and culture
  • Innovating through global sourcing
During the course we will analyze several case studies which highlight various aspects that organizations undergo while developing a global sourcing strategy. The case studies will be based on real world examples and will illustrate the intersection of business rationale with human emotions. The course delivery format will be a mixture of instructor-led sessions and guest speakers from vendor, client, consulting, and legal firms. As their final project, student groups will be given an opportunity to investigate a topic of their choice pertaining to global sourcing.

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Business Process Design and Implementation
INFO-GB.3356 (B20.3356)
3 credits

This course focuses on the design, management, and implementation of IT-supported business processes. The evolution of information technology and the near ubiquity of the Internet give business firms the opportunity to completely redesign their business processes, to develop systems faster, and to implement systems in entirely new ways. Topics covered include business process analysis and design, implementation, change management, and performance measurement systems. Relevant technologies include Web-based application service providers, workflow management systems, knowledge management systems, and enterprise systems. Students learn how to analyze a business problem, design new business processes, and manage the implementation process. They also gain an understanding of the technology support structure required for successful implementation of organizational and interorganizational processes.

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Emerging Technology and Business Innovation
INFO-GB.3362 (B20.3362)
3 credits

This course provides a thorough examination of several key technologies that enable major advances in e-business and other high-tech industries, and explores the new business opportunities that these technologies create. For each of these technologies, it provides an overview of the "space" corresponding to this class, examines who the major players are, and how they use these technologies. Students then study the underlying technologies; examine the business problems to which they can be applied; and discuss how these problems are solved. Key companies in the "spaces" created by these technologies are also studied: what these companies do; which technologies they use; how these technologies support their critical applications; and how these companies compete and collaborate among themselves. Moreover, the course examines possible future directions and trends for the technologies being studied; novel applications that they enable; and how high-tech companies can leverage applications of these technologies. This is an advanced course, and it is intended for the students who have already acquired basic knowledge of technical concepts and who want to advance their knowledge of technologies beyond the basics and to further develop an understanding of the dynamics of the "spaces" associated with these technologies.

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Operations Management MBA Courses

Effectively managing operations enables firms to gain a competitive advantage by creating cost leadership, quality superiority, flexible response to customer needs, and getting products and services to market quickly. Our mission is to equip 21st century managers with the ability and analytical skills to lead and manage complex and dynamic operating systems.

Our faculty is known for cutting-edge research on critical emerging operations and strategy issues. This research is reflected not only in the foundation core course, but also in the six advanced electives offered. We are a multidisciplinary group with expertise in mass customization, business process design, service operations, value chain management, environmental management, quality, distribution channel management, risk analysis, manufacturing systems design, and global operations strategy.

We consult and conduct research on real-world problems in a variety of industries and governmental agencies. These include banking, automobiles, telecommunications, electronics, machine tools, cosmetics, chemicals, pollution control, waste management, consumer goods, airlines, health care, steel, retailing, computers, utilities, and NASA.

We emphasize learning through experiential exercises, real-world cases, guest speakers, field visits, and hands-on field projects. We constantly stress the relationships between analytic and strategic perspectives.

Our business students envision themselves working in the fields of finance, accounting, marketing, information systems, product design, or human resources. All of these areas are closely involved with the production and distribution of goods and services, and the more managers know about the system that produces the firm's product, the better they are able to design, market, finance, or manage the activities of the organization.

Working knowledge of today's key operations issues provides the ability and skills to build successful careers and contribute to the firm in many fields. As firms restructure in response to global challenges, ample opportunities exist for managers in every field to excel by analyzing and improving business operations. For example, an operations consultant or manager would acquire the skills necessary to undertake business process improvements, total quality management initiatives, and customer service improvements. A financial analyst or management consultant would be in a better position to evaluate a firm's strengths, weaknesses, and valuation by understanding how operations affect the firm's competitive position and long-term cash flow. A marketing manager, who understands operations would be better positioned to take multiple, simultaneous product development projects from conception through delivery, on time and on budget. This would allow firms to bring products to market more quickly, cheaply, and with better quality. A chief information officer or logistics director who understands operations would be in a better position to design and implement state-of-the-art manufacturing and service delivery systems.


M.B.A. Courses in Operations Management

M.B.A. Core Course
COR1-GB.2314 (B01.2314) Operations Management (formerly Competitive Advantage from Operations)

M.B.A. Elective Courses

  • OPMG-GB.2306 (B60.2306) Supply Chain Management
  • OPMG-GB.2307 (B60.2307) Operations Consulting: Design of Operations
  • OPMG-GB.2310 (B60.2310) Managing for Quality
  • OPMG-GB.2313 (B60.2313) Operations in Entertainment: Las Vegas
  • OPMG-GB.2310 (B60.2320) IT in Supply Chains
  • OPMG-GB.2330 (B60.2330) Retail Operations
  • OPMG-GB.2350 (B60.2350) Decision Models
  • OPMG-GB.2351 (B60.2351) Advanced Decision Models
  • OPMG-GB.2360 (B60.2360) Operations in Real Estate Development
  • OPMG-GB.2365 (B60.2365) Operational Risk
  • OPMG-GB.3335 (B60.3335) Operations for Global Entrepreneurs
  • OPMG-GB.3355 (B60.3355) Operations Strategy
  • OPMG-GB.3356 (B60.3357) Service Operations and Strategy

M.B.A. Core Course

Operations Management
COR1-GB.2314 (B01.2314)

3 credits.

This course serves as an introduction to operations, viewed from the perspective of the general manager, rather than from that of the operations specialist. The coverage is very selective; the course concentrates on a small number of themes from the areas of operations management and information technology that have emerged as the central building blocks of world-class operations. It also presents a sample of key tools and techniques that have proven extremely useful. The topics covered are equally relevant to the manufacturing and service sectors.


M.B.A. Elective Courses

Supply Chain Management (Business Logistics)
OPMG-GB.2306 (
B60.2306)
Prerequisite: COR1-GB.2314 (B01.2314). 3 credits.

The function of supply chain management is to design and manage the flow of material and information, starting from the raw materials until finished goods reach customers. Typically, logistics-related costs account for 20 to 25 percent of firms' total costs. On the revenue side, the supply chain decisions have a direct impact on market penetration and customer service. With the globalization of the economy and advances in information technology, supply chain design and coordination have become important tools for gaining competitive advantage.

Therefore, the objectives of the course are to:

  1. develop an understanding of individual components of the supply chain (such as order management, transportation, network design, distribution channel management, after-sales service, and customer service strategy) and their interrelationships with other functions of firms, such as marketing, manufacturing, and accounting;
  2. impart analytical and problem-solving skills necessary to develop solutions for a variety of logistics problems;
  3. understand the complexity of interfirm and intrafirm coordination in implementing programs such as “quick response” and “vendor managed inventories;” and
  4. develop the ability to design logistics systems and formulate integrated supply chain strategy, so that all components are not only internally synchronized but also tuned to fit corporate strategy, competitive realities, and market needs.

Operations Consulting: Design of Operation
OPMG-GB.2307 (B60.2307)
Prerequisite: COR1-GB.2314 (B01.2314). 3 credits.

Enhancing the effectiveness and productivity of operations is a major goal of most organizations. Designing the operations of a firm will be critical to achieving this goal. This course aims to develop an understanding of the components that make up an integrated operating system and to impart modeling skills for understanding the design tradeoffs. The objectives of the course are

  • To develop skills for designing and improving operations.
  • To demonstrate the wide applicability of modeling methodology to different functional areas, with emphasis on manufacturing and service operations.
  • To provide insights into actual business practices and outline the scope for applying the modeling and design ideas developed in this course.
  • To develop optimization and simulation modeling skills.

Managing for Quality
OPMG-GB.2310 (B60.2310)
Prerequisite: COR1-GB.2314 (B01.2314). 3 credits.

This course introduces the basic principles and techniques of managing for quality. Students learn the most important principles and tools by which organizations create value for their customers, including quality measurement and assessment, quality planning, quality control, quality improvement, and quality strategy. Students learn to

  • Understand the historical development of modern quality methods, including the unrivalled contributions of New York University to this field.
  • Analyze systems with respect to quality, using such tools as Six Sigma, Pareto analysis, statistical process control, quality function deployment, reliability analysis, and design of experiments.
  • Apply different philosophies and approaches to quality intelligently, including those of Deming, Hackman and Oldham, Ishikawa, Juran, Shewhart, and Taguchi.
  • Make use of the Malcolm Baldrige National Quality Award criteria, as well as those of other quality examination, certification, and evaluation tools.

The focus is on management planning and decision making, not advanced statistical inference. This course is aimed at M.B.A. students who have already completed the core requirements in operations, marketing, and management. The emphasis is on methods with wide application across diverse industries and organizations, including recent developments in information technology and electronic commerce.


Operation in Entertainment: Las Vegas
OPMG-GB.2313 (B60.2313)
Prerequisite: COR1-GB.2314 (B01.2314). 3 credits.

When we think of entertainment, perhaps the most popular location that comes to mind is Las Vegas. Behind the glitter and excitement in Las Vegas are industries dedicated to supplying entertainment to customers. Operations Management addresses the supply side of business, including how products are produced and how services are supplied. This course goes behind the scenes in Las Vegas to observe and analyze the operations involved in performing this supply function. The course presents an opportunity to observe and study the entertainment industry including strategy formation and decision making that are quite unique.

The entertainment comes in various forms. The underlying driver is certainly gaming, but the industries surrounding the various forms of gambling have become major profit centers separate from the millions made on the casino floors.

During a one-week visit to Las Vegas, students will observe and study some of the major operating industries that comprise the broad scope of entertainment in this city. Although the Operations Management models, techniques and strategies in this field are applicable anywhere, Las Vegas is the epicenter of the industry.

The specific areas that will be studied include:

  • Hotel/Resort operations
  • Gaming
  • Marketing strategy and consumer relations
  • Analytics and technology
  • Real estate development
  • Food/Beverage operations
  • Nightlife, nightclubs and the Theatre of Las Vegas

The class will have an opportunity to tour the major entertainment centers of Las Vegas, and have presentations and question and answer sessions concerning the back-of-the-house operations strategies in each industry. Executives from the top hotel/casino resorts will make presentations to the class and work in small groups with students to explain the strategies that drive the industry. Delivering the information will be top executives and department heads from Station Casinos Red Rock Resort, Harrah's Caesars Palace, MGM Mirage Treasure Island, Light Group Nightclubs, Ultimate Fighting Championship (UFC), Cirque du Soleil and MGM City Center Real Estate Development.


Information Technology (IT) in Supply Chains
OPMG-GB.2320 (B60.2320)
Prerequisite: COR1-GB.2314 (B01.2314). 3 credits..

The course presents an introduction into Supply Chain Management from an IT point of view. It shows an integrated business framework of modern flexible Supply Chain Management, which is based on the principles of demand driven synchronization of supply to demand and network wide visibility and collaboration. The underlying corresponding IT systems to support such a business framework, namely ERP-, Supply Chain Planning-, Event Management- (incl. RFID) and Collaboration Systems, are explained. A focus of the course is Supply Chain Planning, where the different planning areas and their integration to each other are explained. Latest trends in SCM and IT, like Service Oriented Architectures, which facilitates the integration of new business processes into an existing Supply Chain Management solution, will end the course.


Retail Operations
OPMG-GB.2330 (B60.2330)
Prerequisite: COR1-GB.2314 (B01.2314). 3 credits.

This course is highly recommended for students interested in careers in retailing and retail supply chains, businesses like banking, consulting and information technology that provide services to retail firms, and manufacturing companies that sell their products through retail firms.

Retailing is a huge industry (40% of the U.S. economy and the largest employer) that has consistently been an incubator for new business concepts. In the 80's and early 90's Wal-mart pioneered new approaches to supply chain management, and also influenced major established firms like P & G. More recently, Dell has revolutionized the supply chain for PCs using the direct model. Finally, Amazon.com, more than any other firm, has been credited with transforming the Internet from an academic toy to the primary technology influencing business today. Even if you don't expect to work for a retailer, this course can be useful to you in two ways:

  • First, because retailers are such dominant players in many supply chains today, it is important that the processes they follow be understood by manufacturers and distributors, or by the consultants and bankers that service retailers and their suppliers.
  • Second, the problems retailers face (e.g., making data accessible, interpreting large amounts of data, reducing lead-times, eliciting the best efforts from employees, etc.), are shared by firms in many other industries. It's easier to understand these issues through case studies in retailing because we all experience the industry as consumers and can readily relate to chronic problems such as stock outs and markdowns.
The course will examine how retailers understand their customers' preferences and respond with appropriate products through effective supply chain management. Supply chain management is vitally important for retailers and has been noted as the source of success for many retailers such as Wal-mart and Zara, and as an inhibitor of success for e-tailers as they struggle with delivery reliability.

Decision Models
OPMG-GB.2350 (B60.2350)
Prerequisite: COR1-GB.2314 (B01.2314). 3 credits.

This course introduces the basic principles and techniques of applied mathematical modeling for managerial decision making. Students learn to use some of the more important analytic methods (e.g., spreadsheet modeling, optimization, Monte Carlo simulation) to recognize their assumptions and limitations and to employ them in decision making. Students learn to

  • Develop mathematical models that can be used to improve decision making within an organization.
  • Sharpen their ability to structure problems and to perform logical analyses.
  • Translate descriptions of decision problems into formal models and investigate those models in an organized fashion.
  • Identify settings in which models can be used effectively, and apply modeling concepts in practical situations.
  • Strengthen their computer skills, focusing on how to use the computer to support decision making.

The emphasis is on model formulation and interpretation of results, not on mathematical theory. This course is aimed at M.B.A. students with little prior exposure to modeling and quantitative analysis, but it is appropriate for all students who wish to strengthen their quantitative skills. The emphasis is on models that are widely used in diverse industries and functional areas, including finance, operations, and marketing.


Advanced Decision Models
OPMG-GB.2351 (B60.2351)
Prerequisite: COR1-GB.2314 (B01.2314). 3 credits.

This course is designed for students who have taken Decision Models (B60.2350) and would like develop further their quantitative modeling skills for managerial decision making. Students will learn more advanced modeling tools including: static stochastic optimization, two-stage stochastic optimization with recourse, chance-constrained stochastic optimization, and dynamic programming. We explore their applications in various business domains, such as marketing, finance, inventory management, revenue management, supply chain management, project management, among others. Students will learn how these models can be solved using Risk Solver Platform for Excel, a powerful tool for risk analysis, simulation, and optimization. The emphasis throughout the course will be model formulation, solution methods, and managerial interpretation of the results, rather than on the mathematical algorithms used to solve models.


Operations in Real Estate Development
OPMG-GB.2360 (B60.2360)
Prerequisite: COR1-GB.2314 (B01.2314). 3 credits.

This is course will introduce students to the wide ranging aspects of real estate development from an operations perspective. It is directed to students interested in real estate development from the point of view of three classes of investors:

  • an entrepreneurial investor, looking to buy a coop, condo or small property for individual use or rental
  • a working general partner of a small group of investors, who will actually manage &/or be responsible for overseeing the property after purchase
  • a passive outside investor, who may be searching for an investment that is limited in liability to the original investment

Operations Management involves the decisions made at the operating level of a business or project to assure the attainment of higher level goals and strategies. In real estate development, these operating decisions will determine whether or not a deal will be successful and meet overall financial goals. Many students may choose to pursue investments in real estate, and often to actually operate these deals and manage the investments. Although most students will not work full-time in the real estate industry, property investments will arise as opportunities to increase passive income and wealth. Understanding how these deals are created and managed will allow investors to choose deals with the highest probability of success. The real estate topics discussed in the course will investigate all types of development: single family, multifamily, hotel, office, retail and industrial properties. In addition to case studies, class lectures and discussions, some outstanding industry developers will be invited as guest speakers to reinforce the ideas taught in class. The class will culminate in a real estate development simulation with group presentations to the class, and a panel of outside investors.


Operational Risk
OPMG-GB.2365 (B60.2365)
Prerequisite: COR1-GB.2314 (B01.2314). 3 credits.

Operational risk is a new branch of risk management that assesses and mitigates the risk of operational errors to affect the profitability or even the existence of a firm (financial or not). Some examples of these events are: flawed data processing, legal suits, frauds (internal and external), natural or man-made disasters (e.g., terrorist acts), power outages, system problems, etc. Although these issues were always a part of the business, with the advent of operational risk management for the first time they are being seen on an integrated framework with specialized teams responsible for its modeling, measurement and management.

In the particular case of financial institutions, with the sign off of the Basel 2 Accord by the G-10, a new set of standards was established that will regulate the industry. The new Accord established a new capital charge for operational risk as well as detailed new standards that financial firms need to follow. This new environment created a demand for talents with knowledge in the area, and the size of operational risk departments has been increasing significantly. However, as operational risk is such a new concept in the industry, there are major gaps in the development of these risk managers.

This course has the objective to provide the student with an excellent overview of the current industry issues and to give in-depth training on the most important techniques used to model, measure and manage operational risk. The course will provide the students with basic general concepts of risk management techniques. It will be shown techniques to identify operational risk in processes as well as modeling techniques and hedging possibilities available in the market. The course will be given in 12 classes of three hours each in the evenings.


Operations for Global Entrepreneurs
OPMG-GB.3335 (B60.3335)
Prerequisite: COR1-GB.2314 (B01.2314). 3 credits.

This course deals with international operations and strategy for international business ventures and small and medium enterprises (SMEs). It is intended for current and would-be executives of, investors in and management consultants to ventures going global. The discussions are based on current business situations and augmented through presentations by industry partners. Integrated learning, through cases and readings, provides an opportunity to expand the educational experience beyond the theory in the classroom into the local and international business community.

Consider the following questions regarding international new ventures:

  • What are the key success factors of a global operations strategy?
  • How to sustain and expand global operations?
  • What is behind the success of ventures that went international early in the business life cycle?
  • How to manage the risks entailed in global operations?

Students are assigned to work on real cases discussing issues such as:

  • Global operations strategy
  • Global supply chain management
  • Foreign market entrepreneurial entry modes
  • Operations financing and controls
  • Global outsourcing/insourcing
  • International location of facilities and regional headquarters

Here are some examples:

  • A small generic pharmaceutical company based in the Middle East wants to expand globally and is considering whether to enter North America, Europe or Asia as their first step and what the best entry mode would be?
  • A small telecom equipment company in the US has expanded into Europe through the acquisition of another similar company, how do they rationalize the research, product development, manufacturing, marketing and sales operations to accelerate the success, globally, of both?
  • A hi-tech company based in Europe is looking to sell its software and/or IP to the US market through regional partners, how do they choose the right ones, and what terms should they pursue?
  • A successful medium sized Chinese motorcycle manufacturer wants to sell to the US market but wants to understand how to account for local manufacturing requirements, exchange rate exposure?

During the course, teams of four to six students each will be presented with real life strategic operational challenges through a case or by an international business manager. Each team will make two presentations: the first specifying the business dilemma and the second, presenting the results of the analysis. Students will have an opportunity to work with their respective groups and meet or video-conference with the project sponsors or executives.

Prof. Ehud Menipaz lectures and conducts research on international business strategy, entrepreneurship and derivatives. He is a former senior partner with Ernst & Young International, a co-founder of an international memory devices venture, a chaired professor of entrepreneurship management and the founding chair of a center of business, technology and society. He is a national director of the Global Entrepreneurship Monitor project, the leading longitudinal, in depth, study of entrepreneurship, conducted concurrently in over forty countries. In addition to Prof. Menipaz, several guest executives will address the class.


Operations Strategy
OPMG-GB.3355 (B60.3355)
Prerequisite: COR1-GB.2314 (B01.2314). 3 credits.

There is an increasing awareness that operations should contribute to the global competitive stance of a business and not merely be a place where the firm's products or services are produced. This can be done by contributing distinctive competence or capability to the business, and continually improving the products and process of the business. In the OM core course, students study the basic aspects of how firms produce their products and services to gain a competitive advantage, and take a tactical or short-term look at operations.

This course is a natural follow-up to the core course. Students examine the strategic and long-term policies of the firm, and learn how the operations strategies and policies are developed to be consistent with corporate and overall business strategies. To do this effectively, students examine, through case studies, how firms' operations play an important role in building and shaping their competitive posture. This course helps students to

  • recognize the strategic and policy implications that can be gained from managing operations;
  • develop a framework for allocating resources and managing the operations function in ways that distinguish firms from their competitors;
  • analyze, develop, and formulate operations strategies to exploit competitive opportunities;
  • visualize how operations strategies can and must be linked to overall business strategies, as well as the financial and marketing strategies; and
  • highlight effective examples involving continuous improvement and implementation of operations strategies.

Service Operations & Strategy
OPMG-GB.3357 (B60.3357)
Prerequisite: COR1-GB.2314 (B01.2314). 3 credits.

This course is designed to prepare students to manage service businesses and/or service operations in manufacturing firms. The objective is to focus attention on some unique aspects of service businesses and relate these aspects to service operations and strategy. For example, some of the issues this course covers include the following:

  • What impact does intangibility have on corporate and business strategy and operations in service businesses?
  • What is the impact of simultaneous production and consumption of services on how service delivery systems are designed and managed?
  • What impact do customers have on service quality and productivity of service firms?
  • What unique organizational designs are needed to manage a service business?

Consistent with the need to emphasize an integrative multidisciplinary perspective on service operations and strategy, students are asked to undertake a project assignment to design a complete service business, starting from idea to incorporation.


Statistics MBA Courses


Courses in Statistics fall into two categories: statistics and actuarial science.

Statistics courses cover techniques relating to the application of the theory of probability to decisions that must be made in the face of uncertainty. Statistical theory and methods are used in a variety of applications, such as

  • sampling
  • data analysis
  • design of market research studies
  • quantitative methods in cost accounting
  • statistical quality control of manufactured products
  • economic forecasting
  • financial modeling

Statistical computing algorithms are used for analyzing data and statistical estimation.

Actuarial science courses prepare students for an actuarial career, applying probability and statistics to the fields of insurance and pensions. The courses in actuarial science and related fields of probability, statistics, economics, and finance cover all of the material that appears in the first two examinations jointly sponsored by the Society of Actuaries and the Casualty Actuarial Society. Other courses at Stern cover portions of examinations three and four.

The program offers students the theory and techniques to solve business problems. Each course emphasizes the application of statistical research methods to actual business problems. The applied courses make extensive use of computers.

A student considering statistics courses beyond the core course should speak to a faculty member about prerequisites and career objectives before registering. In certain instances, instructors may waive prerequisites for an advanced course.

Graduate-level courses are also offered for students who have less formal mathematical backgrounds. These are generally, but not exclusively, computer-intensive courses that develop skills in quantitative techniques. For the most part, the only prerequisite for these courses is the M.B.A. core course, Statistics and Data Analysis, COR1-GB.1305 (B01.1305). These courses are open to students regardless of their areas of specialization. Follow the links to the left for a description of Statistics courses.


M.B.A. Course in Statistics
  • COR1-GB.1305 (B01.1305) Statistics and Data Analysis
M.B.A. Electives - All Specializations
  • STAT-GB.2301 (B90.2301) Regression and Multivariate Data Analysis
  • STAT-GB.2302 (B90.2302) Forecasting Time Series Data
  • STAT-GB.2308 (B90.2308) Applied Stochastic Processes for Financial Models
  • STAT-GB.2309 (B90.2309) Mathematics of Investment
M.B.A. Electives - Statistics and Actuarial Science
  • STAT-GB.3301 (B90.3301) Introduction to the Theory of Probability
  • STAT-GB.3302 (B90.3302) Statistical Inference and Regression Analysis
  • STAT-GB.3303 (B90.3303) Multivariate Statistical Analysis
  • STAT-GB.3304 (B90.3304) Advanced Theory of Statistics
  • STAT-GB.3305 (B90.3305) Bayesian Inference and Statistical Decision Theory
  • STAT-GB.3306 (B90.3306) Time Series Analysis
  • STAT-GB.3307 (B90.3307) Categorical Data
  • STAT-GB.3308 (B90.3308) Sampling Techniques
  • STAT-GB.3309 (B90.3309) Experimental Design
  • STAT-GB.3314 (B90.3314) Statistical Computing and Sampling Methods with Applications to Finance
  • STAT-GB.3352 (B90.3352) Advanced Theory of Probability
  • STAT-GB.3383 (B90.3383) Frequency Domain Time Series Analysis

M.B.A. Electives - Actuarial Science Focus
  • FINC-GB.2302 (B40.2302) Corporate Finance (See course descriptions in Finance website)
  • STAT-GB.2302 (B90.2302) Forecasting Time Series Data
  • STAT-GB.2309 (B90.2309) Mathematics of Investment
  • STAT-GB.3301 (B90.3301) Introduction to the Theory of Probability
  • STAT-GB.3335 (B90.3335) Life Contingencies
M.B.A. Electives - Stochastic Processes
  • BSTAT-GB.3321 (B90.3321) Introduction to Stochastic Processes


MBA Core Course in Statistics

Statistics and Data Analysis
COR1-GB.1305 (B01.1305). 3 credits.

This course is designed to achieve an understanding of fundamental notions of data presentation and analysis and to use statistical thinking in the context of business problems. The course deals with modern methods of data exploration (designed to reveal unusual or problematic aspects of databases), the uses and abuses of the basic techniques of inference, and the use of regression as a tool for management and for financial analysis.


Electives - All Specializations

Statistics group faculty members offer courses for M.B.A. students interested in applications of quantitative methods to various aspects of business activity. These courses may also be taken to meet requirements for a specialization in statistics. The only prerequisite for these courses is Statistics and Data Analysis, COR1-GB.1305 B01.1305, with the exception of Mathematics of Investment, STAT-GB.2309 (formerly B90.2309), (which requires one semester of undergraduate calculus or the instructor's permission). The STAT-GB.2XXX (STAT-GB.2XXX, formerly B90.2XXX) courses emphasize applications and present the theory at the level of intuitive arguments. The STAT-GB.3XXX (formerly B90.3XXX) courses emphasize the theory and methodology, using the applications as illustrations.


Regression and Multivariate Data Analysis
STAT-GB.2301 (B90.2301)
Prerequisite: COR1-GB.1305 (B01.1305). 3 credits.

This is a data-driven, applied statistics course focusing on the analysis of data using regression models. It emphasizes applications to the analysis of business and other data and makes extensive use of computer statistical packages. Topics include simple and multiple linear regression, residual analysis and other regression diagnostics, multicollinearity and model selection, autoregression, heteroscedasticity, regression models using categorical predictors, and logistic regression. All topics are illustrated on real data sets obtained from financial markets, market research studies, and other scientific inquiries.

Forecasting Time Series Data
STAT-GB.2302 (B90.2302)
Prerequisite: COR1-GB.1305 (B01.1305). 3 credits.

Presented in this course are practical time series forecasting techniques with emphasis on the Box-Jenkins ARIMA (autoregressive integrated moving average) method and conditional volatility ARCH (autoregressive conditional heterogeneity) and GARCH (generalized autoregressive conditional heterogeneity) models. The course gives a mix of practical data analysis along with an introduction to the relevant theory. The ARIMA models are used to forecast series like interest spreads, while ARCH models are used in estimating and forecasting the volatility of series like stock returns and exchange rate returns. Students analyze data sets of their own choice in projects. Additional topics of interest covered in the course are methods of testing for nonstationary (Dickey-Fuller tests) as well as models for capturing seasonality as seen, for example, in series of monthly sales figures. The low-cost forecasting method of exponential smoothing is discussed, and its connection to the RiskMetricsTM methods of J. P. Morgan and GARCH models is explored. If time permits, we also study methods of forecasting multivariate time series, where information from several series is pooled to forecast a single series. The concept of co-integration or comovement of multivariate series is discussed (interest rates being a prime example), along with their implications for forecasts. Other potential topics in the course include the use of ARCH models in value at risk (VAR) analysis and in option pricing.

Applied Stochastic Processes for Financial Models
STAT-GB.2308 (B90.2308)
Prerequisite: COR1-GB.1305 (B01.1305). 3 credits.


The purpose of this course is to present mathematical background for the stochastic processes that are widely employed as modeling tools in finance. Emphasis is on the intuitive approach and examples rather than on proofs or mathematical rigor. The following topics are included: random walks, martingales, Brownian motion, and Geometric Brownian motion. The relevance of the considered processes to financial modeling is stressed throughout. In particular, the Cox, Ross, and Rubinstein and the Black-Scholes models for pricing stock options are discussed. In addition, the Ho and Lee, Black-Derman and Toy, and the Cox-Ingersoll-Ross models for pricing interest rate derivative securities are discussed.

Mathematics of Investments
STAT-GB.2309 (B90.2309)
Prerequisite: one semester of undergraduate calculus or permission of the instructor. 3 credits.


The course discusses mathematical and technical aspects of investments. Topics include measurement of interest and discount rates, accumulated value and present value, annuities, sinking funds, amortization of debt, and determination of yield rates on securities. Applications include bond evaluation, mortgages, capital budgeting, depreciation methods, and insurance.


Electives - Statistics and Actuarial Science

These electives are open to all students (MBA and PhD) who have the required mathematical prerequisites (two semesters of calculus and one semester of matrix algebra at the graduate or undergraduate level). Typically, students who majored in engineering or mathematics would automatically satisfy this requirement.

Introduction to the Theory of Probability
STAT-GB.3301 (B90.3301)
Prerequisites: two semesters of calculus. 3 credits.


This course covers the basic concepts of probability. Topics include the axiomatic definition of probability; combinatorial theorems; conditional probability and independent events; random variables and probability distributions; expectation of functions of random variables; special discrete and continuous distributions, including the chisquare, t, and F distributions; joint distributions with emphasis on the bivariate normal distribution; law of large numbers, central limit theorem; and moment generating functions. The theory of statistical estimation is introduced with a discussion on maximum likelihood estimation.

Statistical Inference and Regressional Analysis
STAT-GB.3302 (B90.3302)
Prerequisites: STAT-GB.3301 (B90.3301) and one semester of linear algebra. 3 credits.

The course has two distinct components: statistical inference and regression analysis. Topics included in statistical inference are principles of statistical estimation and inference, Neyman-Pearson Lemma, testing of means, variances, tests of independence, and nonparametric methods. Regression analysis focuses on the general linear regression model, least squares estimation, departures from standard assumptions, autocorrelation, multicollinearity, analysis of residuals, choice of variables, and nonlinear models.

Multivariate Statistical Analysis
STAT-GB.3303 (B90.3303)
Prerequisite: STAT-GB.3302 (B90.3302). 3 credits.

This course covers multivariate distributions. It focuses on the multivariate normal, geometric principle of sampling, multivariate asymptotics, principles of multivariate inference, tests of the mean vector for one and several populations leading to Hotelling's T2 statistic and MANOVA (multiple analysis of variance), techniques of multiple comparisons, multivariate linear regression models, principal components, factor analysis, canonical correlations, discrimination and classification, clustering, and graphical displays of multivariate data.

Advanced Theory of Statistics
STAT-GB.3304 (B90.3304)
Prerequisite: STAT-GB.3302 (B90.3302). 3 credits.

The course covers topics in statistical estimation and hypothesis testing. Topics on estimation include sufficiency, exponential family, Pitman Koopman Theorem, criteria for choice of estimators, lower bounds for variance of estimators, sufficiency and completeness, maximum likelihood estimation, theorems on limiting distributions, and robust estimation. Topics on hypothesis testing include theory of optimum tests, Neyman- Pearson Lemma, M.P. (most powerful) and U.M.P. (uniformly most powerful) tests, unbiased tests, composite hypotheses, Neyman structure, likelihood principle, and likelihood ratio tests.

Bayesian Inference and Statistical Decision Theory
STAT-GB.3305 (B90.3305)
Prerequisite: STAT-GB.3302 (B90.3302). 3 credits.

This course has two components: statistical decision theory and the Bayesian paradigm for statistical inference. Statistical decision theory is concerned with the problem of making decisions in the presence of relevant statistical knowledge. Topics include decision rules, utility, risk functions, admissibility, consistency, expected loss, randomized decision rules, minimax decision rules, Bayes decision rules, and game theory. Both Frequentist and Bayesian concepts are considered. The Bayesian paradigm is the approach to statistics that formally seeks to utilize prior information. Topics include the notion of subjective probability, the specification of prior information, credibility sets, predictive distributions, empirical and hierarchical Bayes analysis, Bayesian robustness, and computation. Comparisons are made with the classical approaches to typical problems. Business case studies are used to illustrate both components.

Time Series Analysis
STAT-GB.3306 (B90.3306)
Prerequisite: STAT-GB.3302 (B90.3302). 3 credits.

This course presents the Fourier analysis of time series. The frequency domain approach covered here provides a complementary outlook on time series to the usual time domain Box-Jenkins approach. Topics include periodicity (cycles) in time series data, the periodogram and its distribution, linear filters and transfer functions, spectral density, spectral representations of autocovariances and stationary processes, ARMA (autoregressive moving average) models and their spectra, model selection, the linear forecasting problem, and spectral estimation. We also discuss long memory models, including fractional ARIMA (autoregressive integrated moving average) and nonlinear time series, including ARCH (autoregressive conditional heterogeneity) models and chaos, as time permits.

Categorical Data
STAT-GB.3307 (B90.3307)
Prerequisite: STAT-GB.3302 (B90.3302). 3 credits.

Discrete random variables are the subject of this course, with most of the emphasis going to the bivariate and multivariate situations. The major topics are the chi-squared statistic, Fisher's exact test, odds ratio estimates and intervals, sets of tables, the log-linear model, model fitting, and logit analysis. The fundamental paper by Leo Goodman in the 1970 issue of the Journal of the American Statistical Association is discussed. M.B.A. and undergraduate students registering for this course are evaluated primarily on their ability to formulate and analyze data-based problems. All other students are evaluated primarily on their understanding of methodological and theoretical issues associated with the analysis of categorical data.

Sampling Techniques
STAT-GB.3308 (B90.3308)
Prerequisite: STAT-GB.3302 (B90.3302). 3 credits.

The course considers commonly used sampling schemes, such as simple, random, stratified, multistage, and double sampling. The efficiencies of these plans are discussed in detail. Also included are methods of estimation, including ratio and regression. Other topics include poststratification, multivariate surveys, analytic studies, problems of nonresponse, nonsampling errors, and randomized response technique. Theory is illustrated with examples from diverse fields.

Experimental Design
STAT-GB.3309 (B90.3309)
Prerequisite: STAT-GB.3302 (B90.3302). 3 credits.


This course develops the analysis of variance model in detail through the “one-way” and “two-way” designs, including partitioning sums of squares, orthogonal polynomials, interactions, multiple comparisons, and fixed and random effects. The concepts of randomization and blocking lead to discussions of design strategy. Further topics, covered if time permits, are the higher-order designs, split-plot designs, and fractional factorials. The material of this course is vital to those performing designed experiments, and the information can also be helpful in observational studies.

Statistical Computing and Sampling Methods with Applications to Finance
STAT-GB.3314 (B90.3314)
Prerequisite: STAT-GB.3302 (B90.3302). 3 credits.

This course covers most of the classical and modern Monte Carlo methods for statistical estimation. In particular, the fast growth of Monte Carlo Markov Chain (MCMC) methods has enabled the use of Bayesian inference in many applied fields. Methodologies are illustrated with financial applications such as estimation of implied volatility and risk measures. Examples are drawn from published research and survey papers in current literature (Risk magazine, J. P. Morgan's Risk Metrics). The course integrates three basic components of statistical analysis in financial areas: (1) modeling and inference (with emphasis on Bayesian methodology), (2) computing and sampling methods for statistical estimation (with emphasis on MCMC), and (3) applications to financial data (with emphasis on volatility and risk). The focus is placed on the second component, bridging the gap between what can be said in theory (first component) and what can be done in practice (third component). The goals of the course are modest so that a full treatment of all major topics can be achieved.

Advanced Theory of Probability
STAT-GB.3352 (B90.3352)
Prerequisite: STAT-GB.3302 (B90.3302). 3 credits.

The aim of the course is to establish a comprehensive foundation of the theory of probability. The topics covered are basic measure theory, random variables, and induced measures and distributions; independence of random variables; integration in a probability space with emphasis on conditional expectation and martingales; modes of convergence of random variables, including almost sure convergence, convergence in LP, convergence in probability, and convergence in distribution; characteristic functions and the inversion formula; and the central limit theorem for independent identically distributed random variables and also for martingale differences. If time permits, additional topics will include functional central limit theorems and their applications.

Frequency Domain Time Series Analysis
STAT-GB.3383 (B90.3383). 3 credits.

Frequency Domain Time Series is an advanced course on foundations and applications of time Series. Methods involving periodograms and spectral densities are emphasized. Linear filtering and spectral representations (stochastic integrals) for stationary time series are used as unifying themes. The second half of the course considers GARCH models, fractals, long memory and fractional cointegration. Again, emphasis is on insights gained from the frequency domain viewpoint.

The mathematics used in the course is Fourier analysis, a useful tool for all technically-oriented students. All mathematical results are presented in a self-contained manner.

The course grades are based on homework assignments (70% of the grade) and an in-class open-book final exam (30% of the grade). Homeworks can be re-submitted for further credit, at any time.

There is a clear need for advanced students in statistics, finance and economics to have a deep understanding of time series in the frequency domain. Increasingly, frequency domain methods and models are being used by practitioners. If time permits, we will discuss some of these methods along with papers that have appeared in the literature. Examples include:
  • "The distribution of realized exchange rate volatility" (Anderson, Bollerslev, Diebold and Labys, Journal of the American Statistical Association, 2001).
  • "Unit root tests in ARMA models with data-dependent methods for the selection of the truncation lag" (Ng and Perron, Journal of the American Statistical Association, 1995).
  • "The size and power of the variance ratio test in finite samples: A Monte Carlo investigation" (Lo and MacKinlay, J. Econometrics, 1989).
  • "Long memory in continuous time stochastic volatility models" (Comte and Renault, Mathematical Finance, 1998).
  • "An asymptotic approximation for heteroskedasticity autocorrelation robust tests" (T. Vogelsang, 2002).
  • "A fractional cointegration analysis of purchasing power parity" (Cheung and Lai, Journal of Business and Economic Statistics, 1993).
  • "On the power of Dickey-Fuller tests against fractional alternatives" (Diebold and Rudebusch, Economics Letters, 1991).
  • "Long Memory in Stock-Market Trading Volume" (Lobato and Velasco, Journal of Business and Economic Statistics, 2000).
  • "Non-Stationary log-periodogram regression" (Velasco, J. Econometrics, 1999).
  • "A bias-reduced log-periodogram regression estimator for the long memory parameter" (D.W.K. Andrews and Patrik Guggenberger, Coes Foundation for Research in Economics, Yale University, 1999).


Electives - Actuarial Science Focus


Students completing the M.B.A. with a focus in actuarial science will be prepared for the actuarial examinations of the Society of Actuaries and the Casualty Actuarial Society. The M.B.A. Program meets the needs of students wishing to focus in actuarial science and to obtain a broad background in applied business areas that interest the actuary (such as information systems, accounting, finance, economics, marketing, and management). A student enrolled in the M.B.A. Program should complete the courses listed below, in addition to the core.

Corporate Finance
FINC-GB.2302 (B40.2302)
For description, see course listings in Finance department web site.

Forecasting Time Series Data
STAT-GB.2302 (B90.2302). 3 credits.

Mathematics of Investment
STAT-GB.2309 (B90.2309). 3 credits.

Introduction to the Theory of Probability
STAT-GB.3301 (B90.3301). 3 credits.

Life Contingencies
STAT-GB.3335 (B90.3335)
Prerequisite: STAT-GB.3301 (B90.3301). 3 credits.


Applies probability and mathematics of investment to problems of premiums and reserves on annuities and insurance policies. Topics include probabilities of mortality, laws of mortality, joint life probabilities and annuities, and multiple decrement theory. Application to pension plans is discussed.



Electives - Stochastic Processes

Introduction to Stochastic Processes

STAT-GB.3321 (B90.3321)
Prerequisite: STAT-GB.3301 (B90.3301). 3 credits.

This is an introductory course in stochastic processes. The course places emphasis on probabilistic thinking and on learning how to model the real-life phenomena, which evolve over time. It presents classes of stochastic processes which are widely used as modeling tools in diverse fields of applications including finance, economics, accounting, marketing and actuarial science. It covers basic theory and applications of discrete and continuous-time Markov chains; discrete and continuous time martingales; and Brownian motion and its generalizations. The introduction to Ito stochastic calculus is presented with a view towards financial applications. The course also discusses some statistical aspects of considered processes.