This course covers the fundamental principles of finance. The primary concepts covered include the time value of money, principles of valuation and risk. Specific applications include the valuation of debt and equity securities as well as capital budgeting analysis, financial manager’s functions, liquidity vs. profitability, financial planning, capital budgeting, management of long term funds, money and capital markets, debt and equity, management of assets, cash and accounts receivable, inventory and fixed assets. Additional topics include derivative markets.

This course introduces managers to the essence of business economics — the theories, concepts and ideas that form the economist’s tool kit encompassing both the microeconomic and macroeconomic environments. Microeconomic topics include demand and supply, elasticity, consumer choice, production, cost, profit maximization, market structure, and game theory while the macroeconomic topics will be GDP, inflation, unemployment, aggregate demand, aggregate supply, fiscal and monetary policies. In addition, the basic concepts in international trade and finance will be discussed.

Project success depends, largely, on the human side. Success in motivating project workers, organizing and leading project teams, communication and sharing information, and conflict resolution, are just a few areas that are critical for project success. However, being primarily technical people, many project managers tend to neglect these “soft” issues, assuming they are less important or that they should be addressed by direct functional managers. The purpose of this course is to increase awareness of project managers to the critical issues of managing people and to present some of the theories and practices of leading project workers and teams.

This course explores data-driven methods that are used to analyze and solve complex business problems. Students will acquire analytical skills in building, applying and evaluating various models with hands-on computer applications. Topics include descriptive statistics, time-series analysis, regression models, decision analysis, Monte Carlo simulation, and optimization models.

The study of marketing principles from the conceptual, analytical, and managerial points of view. Topics include: strategic planning, market segmentation, product life-cycle, new product development, advertising and selling, pricing, distribution, governmental, and other environmental influences as these factors relate to markets and the business structure.

This course is intended to integrate all previously taken courses in the program by presenting a set of increasingly complex business problems. These problems can be solved through analytic skills taught in this course and previous courses. In particular, the course is intended to reinforce the understanding of analysis as a way to build models that can focus attention on parts of the system that can be improved through intervention. The early part of the course uses synthetic data and empirical data readily available for analysis. The second part of the course encourages students to state and solve their own problem, gathering their own data as a part of the analytic process.

This course covers the general area of management of operations, both manufacturing and non-manufacturing. The focus of the course is on productivity and total quality management. Topics include quality control and quality management, systems of inventory control, work and materials scheduling, and process management.

Executives make decisions every day in the face of uncertainty. The objective of this course is to help students understand how decisions are made, why they are often less than optimal, and how decision-making can be improved. This course will contrast how managers do make decisions with how they should make decisions, by thinking about how “rational” decision makers should act, by conducting in-class exercises and examining empirical evidence of how individuals do act (often erroneously) in managerial situations. The course will include statistical tools for decision-making, as well as treatment of the psychological factors involved in making decisions.

In this course, students will evaluate and create their own prospective business strategies. They will develop an understanding of entrepreneurship and innovation in starting and growing a business venture. Students will be given an opportunity to actually start their own business or create a business in their company by learning how to take advantage of the new order of business opportunities of the information age. This course’s main objective is to show students how to identify these opportunities, be able to formulate and evaluate both qualitatively and quantitatively whether the opportunity is worth pursuing, and, of course, how it may be pursued. Actual case studies and experiences will be intertwined with the course content.

An interdisciplinary course which examines the elements of, and the framework for, developing and implementing organizational strategy and policy in competitive environments. The course analyzes management problems both from a technical-economic perspective and from a behavioral perspective. Topics treated include: assessment of organizational strengths and weaknesses, threats, and opportunities; sources of competitive advantage; organizational structure and strategic planning; and leadership, organizational development, and total quality management. The case method of instruction is used extensively in this course.

Covers marketing analytics techniques such as segmentation, positioning, and forecasting, which form the cornerstone of marketing strategy in industry. Students will work on cases and data from real companies, analyze the data, and learn to present their conclusions and make strategic recommendations.

Introduces the tactical and strategic issues surrounding the design and operation of supply chains, to develop supply chain analytical skills for solving real life problems. Topics covered include: supplier analytics, capacity planning, demand-supply matching, sales and operations planning, location analysis and network management, inventory management and sourcing.

This course focuses on network concepts, including graph-theoretic fundamentals, centrality, cohesion, affiliations, equivalence and roles, as well as design issues, including data sampling and hypothesis testing. Another focus of this course is on marketing applications of social network analysis — in particular, the use of knowledge about network properties and behavior, such as hubs and paths, the robustness of the network, and information cascades — to better broadcast products and search targets.

Theoretical and practical aspects of risk assessment and management will be covered. Major topics include: Importance of innovation and technological changes in current competitive environment, risk and uncertainty, decision trees, binomial methods and derivation of Black-Scholes option pricing formula, extension of option methodology to non-financial (real) options, VAR (value at risk), a framework of risk assessment, and several real-world case studies.

This course addresses the fundamentals of venture capital, which includes the venture capital industry, the structure of venture capital firms and venture capital investments. It addresses in some detail the relationship between venture risk and return, the cost of venture capital and the valuation of high growth companies. The course covers a variety of valuation methods as well as analysis of company capital structure or “cap tables.”Students use software tools to determine the value of stocks, options and special features of preferred stock. Topics related to the finance of innovation and the relationship between strategy and venture finance are also covered. Lessons learned are reinforced through case analyses and real examples from the industry.

This course takes a practical approach to managing investments. It covers a wide variety of investment vehicles ranging from pure equity and debt offerings to complex derivatives and options. Various investment strategies are presented, which focus on the different fundamental approaches and tactics used by leading investors to achieve their financial goals. The course also focuses on investment styles, including momentum, growth, income, asset allocation and vulture investing. Students participate in real-time simulation experiences to create viable portfolios of stocks, bonds and other investments, while tracking their performance against the overall market and the class on a weekly basis.

This course covers the fundamentals of financial derivatives, including the basic properties and the pricing of futures, options and swaps. It also explores trading and hedging strategies involving financial derivatives. Special topics, such as exotic options and credit derivatives, are explored. The course provides the foundation of financial derivatives and lays the ground for a rigorous risk management course and other advanced quantitative courses, such as stochastic finance.

Topics covered in this course include: leverage on the balance sheet and weighted average cost of capital; bankruptcy, turnarounds, and recapitalizations; international currency hedging; stock options; private equity valuation; mergers and acquisitions; and the issuance of public and private securities.

This course is designed to teach students the nature and availability of the financial data available at Stevens. The focus of the course will be on equity, futures, FX, options, swaps, CDSs, interest rate swaps, etc. They will learn how to use a Bloomberg terminal. As part of the course the students will be certified in the 4 areas that Bloomberg offers certification. We will cover the Thomson-Reuters Tick history data and basics of using this data. The course also introduces basics of applied statistics. Bloomberg terminal access will be required for any student taking the course on the web.

In this course, students will learn the basics of the open-source programming language R using financial data and applications. Basic statistical knowledge is required to complete the course. Upon completion, students will be able to use R for assignments and research using data in finance.

This course is a primer on Python (language syntax, data structures, basic data processing, Python functions, modules and classes). The remainder of the course covers open-source Python tools relevant to solving financial programming problems. There will be reading assignments of the corresponding chapters in the textbook and additional materials will be provided.

This course will provide an overview of issues and trends in data quality, data storage, data scrubbing, data flows and data encryption. Topics will include data abstractions and integration, enterprise-level data issues, data management issues with collection, warehousing, preprocessing, and querying. Furthermore, the Hadoop based programming framework for big data issues will be introduced along with any governance and policy issues. Corequisite: FE 513

Full Description

The course provides a practical introduction to SQL databases and Hadoop cluster systems. Students will receive hands-on instruction about setting up and working with databases. Most of the software will be introduced using case studies or demonstrations, followed by a lecture of related fundamental knowledge. The course covers SQL, NoSQL and database management systems. The course will cover accessing databases using API.

This course deals with financial technology underlying activities of markets, institutions and participants. The overriding purpose is to develop end-to-end business decision-making data analytics tools along with enterprise-level systems thinking. Statistical learning algorithms will be connected to financial objects identification and authentication along with the appropriate databases to create enterprise level financial services analytics systems.

Effective visualization of complex data allows for useful insights, more effective communication, and making decisions. This course investigates methods for visualizing financial datasets from a variety of perspectives in order to best identify the right tool for a given task. Students will use a number of tools to refine their data and create visualizations, including: R and associated visualization libraries, Ruby on Rails visualization tools, ManyEyes, HTML5 & CSS 3, D3.js and related javascript libraries, Google Chart Tools, Google Refine, and image-editing programs.

This course introduces the stochastic calculus to students of finance and financial engineering. The course deals with Markov chains, Poisson processes, random walks, Brownian motion, asset prices as processes, limits of stochastic sequences, Ito sums and integral, fundamental models in modern finance, price dynamics and elementary examples of stochastic differential equations.

This course provides the mathematical foundation for understanding modern financial theory. It includes topics such as basic probability, random variables, discrete continuous distributions, random processes, Brownian motion, and an introduction to Ito’s calculus. Applications to financial instruments are discussed throughout the course.

This course deals with risk management concepts in financial systems. Topics include identifying sources of risk in financial systems, classification of events, probability of undesirable events, risk and uncertainty, risk in games and gambling, risk and insurance, hedging and the use of derivatives, the use of Bayesian analysis to process incomplete information, portfolio beta and diversification, active management of risk/return profile of financial enterprises, propagation of risk, and risk metrics.

This course provides computational tools used in industry by the modern financial analyst. The current financial models and algorithms are further studied and numerically analyzed using regression and time series analysis, decision methods, and simulation techniques. The results are applied to forecasting involving asset pricing, hedging, portfolio and risk assessment, some portfolio and risk management models, investment strategies, and other relevant financial problems. Emphasis will be placed on using modern software. Foundational: FE 543 or FE 610

This course introduces the modern portfolio theory and optimal portfolio selection using optimization techniques such as linear programming. Topics include contingent investment decisions, deferral options, combination options and mergers and acquisitions. The course introduces various concepts of financial risk measures.

This course deals with basic financial derivatives theory, arbitrage, hedging, and risk. The theory discusses Ito’s lemma, the diffusion equation and parabolic partial differential equations, and the Black-Scholes model and formulae. The course includes applications of asset price random walks, the log-normal distribution, and estimating volatility from historic data. Numerical techniques, such as finite difference and binomial methods, are used to value options for practical examples.

IT organizations must be able to leverage new technologies. This course focuses on how organizations can effectively and efficiently assess trends and emerging technologies in data and knowledge management, information networks, and analyzing and developing application systems. Students will learn how to help their organizations define, select, and adopt new information technologies.

This course focuses on the role of Information Technology (IT) in reengineering and enhancing key business processes. The implications for organizational structures and processes, as the result of increased opportunities to deploy information and streamline business systems, are covered.

This course leads students through the identification, analysis, definition, and deployment of service opportunities within public and private organizations. Each of these phases is analyzed in detail to encompass the principal activities, methods, tools and techniques applied in the respective phase. Students will learn how to identify appropriate supporting techniques and information technologies for the different phases of the service life cycle, assess the role of technology, and gauge the organizational impact of service-focused operations. The objective of the course is to enable students to identify, implement and evaluate innovative service offerings in their organization.

This course focuses on the issues surrounding the design of an overall Information Technology architecture. The traditional approach in organizations is to segment the problem into four areas: network, hardware, data, and applications. Instead, this course concentrates on the interdependencies among these architectures. In addition, this course will utilize management research on organizational integration and coordination. The student will learn how to design in the large, make appropriate choices about architecture in relationship to overall organization goals, understand the different mechanisms for coordination available, and create a process for establishing and maintaining an ongoing enterprise architecture.

This course deals with the basic problems of managing a project, defined as a temporary organization built for the purpose of achieving a specific objective. Both operational and conceptual issues will be considered. Operational issues include definition, planning, implementation, control, and evaluation of the project. Conceptual issues include project management vs. hierarchical management, matrix organization, project authority, motivation, and morale. Cases will be used to illustrate problems in project management and how to resolve them.

This course provides a theoretical perspective on project management for a better understanding of project implementation in modern organizations. The course is based on the premise that success in project leadership depends on a proper managerial style and attitude, and not on specific tools for planning and controlling. The course focuses on developing the manager’s conceptual thinking and on building “the project manager’s mind.” The course helps managers see the entire project landscape and the long-term issues that are critical to project success. It will also address the organizational aspects of initiating and running the program.

Formalized procedures, tools, and techniques used in conceptual and detailed planning of the project. Development of work breakdown structure as the foundation for project cost and project duration. Application of project data in monitoring the project progress and in formulating remedial actions in response to unexpected occurrences.

This course focuses on key leadership skills for addressing the complex challenges posed by program management, highly-matrixed environments and cross-national collaborations Its purpose is to enhance individuals’ abilities to develop others, strategically integrate efforts across groups, and drive change. The concepts presented are theory and research driven so that participants can deepen their conceptual understanding. At the same time, the course calls upon learners to address real-life challenges they face as program and or director-level leaders. Each session presents effective techniques and uses experiential exercises or assignments to provide plenty of practice. The course also requires participants to further transfer learning to their workplaces through focused development planning and coaching support.

This course addresses environmental management and its role in sustainability from multiple perspectives, including but not limited to that of a natural scientist, an engineer, a marketing manager, an economist, an environmental lawyer, and a policy maker. The course also introduces students to some of the many tools used by environmental managers, such as life cycle analysis, environmental audit, etc. Students will learn from the course instructor and invited subject matter experts, who will explain in a non-technical manner that is intended for adequate comprehension by students from diverse fields of study on how their respective disciplines contribute to proper management of our environment, thereby making our world more sustainable.

This course will focus on best practices and emerging trends in sustainable business management. Topics will include corporate social responsibility, sustainable business theories, green business models, value chain management, green marketing, triple bottom line reporting, benefit-cost analysis and sustainability metrics and reporting. Students will explore the relationship between business management and sustainability goals for a number of industrial sectors. The course will include case studies as a tool for assessing strategies, identifying opportunities for improvements and recommending future actions. Students will be introduced to commonly used sustainability reporting frameworks and will use them to evaluate objective-setting and progress towards green goals.

A survey of legal and regulatory approaches to environmental protection. Topics include: environmental ethics, National Environmental Policy Act, State and Federal environmental agencies; and the Clean Water Act, Safe Drinking Water Act, Superfund, Resource Recovery and Conservation Act, Right-to-Know, Environmental Cleanup Responsibility Act, and wetlands protection.

This course addresses issues of sustainable development at the local, regional and global scales. Topics include understanding of the definitions, history, current status and future outlook of sustainable development. Population dynamics, wealth distribution, principles of economic growth, social dimensions of sustainable growth (poverty, food security, health, education, social inclusion), biodiversity and ecosystem dynamics, climate change. Sustainable development stakeholders and their roles and responsibilities including individuals, advocacy groups, local, regional and country-level governing bodies, NGOs and corporations. Legal, policy and regulatory aspects of sustainable development. A systems view of sustainability and sustainable development including the concepts of global boundaries and resiliency.