Finance and Risk Engineering (FRE-GY)

This summer bootcamp online experience for the incoming MS Financial Engineering cohort prepares students for coursework in Financial Engineering and for summer internship interviews.

This summer bootcamp online experience for the incoming MS Financial Engineering cohort prepares students for coursework in Financial Engineering and for summer internship interviews.

This summer bootcamp experience for the incoming MS Financial Engineering cohort prepares students for coursework in Financial Engineering and for summer internship interviews. | Prerequisite: Matriculation into a graduate program sponsored by the Department of Finance & Risk Engineering, or permission of the department. Corequisites: FRE-GY 5040

This summer bootcamp experience for the incoming MS Financial Engineering cohort prepares students for coursework in Financial Engineering and for summer internship interviews. | Prerequisite: Matriculation into a graduate program sponsored by the Department of Finance & Risk Engineering, or permission of the department. Corequisites: FRE-GY 5030

This course tracks the requirement for the self-paced, self-taught Bloomberg certification to be completed through a Bloomberg terminal. | Prerequisite: Graduate Financial Risk Engineering students only

The Master of Science in Financial Engineering program offers four types of Capstone experiences to its graduate students: theses, projects, special topics, and internships. This Capstone Assessment will serve as a centralized measure for the various types of Capstone experiences to identify whether students have successfully completed this experience and garner feedback about graduating students' skills and professional readiness. Note: course should be completed during final semester of studies. | Prerequisites: FRE-GY 9973 or FRE-GY 7021 (taken two times for a total of 3 credits) or FRE-GY 7043 or two special topics courses of 1.5 credits each, with a capstone papers submitted to the faculty.

This course provides a solid understanding of the creation and interpretation of modern financial statements. Topics include the reasons for financial statements, U.S. accounting principles and how they differ abroad, quality of financial information, financial ratios and their uses, cash-flow analysis, measurement of corporate performance. The course will also cover various methods of forecasting statements and a discussion of valuation. | Prerequisite: Graduate Standing or permission of FRE department.

This course provides a rigorous introduction to the principles and application of the theory of financial economics. Following a review of foundational theories of markets and competition, this course covers the following areas: certainty and perfect capital markets, the institutional setting of financial economics, risk and contingent claims theory, and capital market imperfections and the limits to arbitrage that these impose on financial systems. | Prerequisite: Graduate Standing

This course explains in detail various models and methods for pricing and hedging derivatives including: European, American, exotic options, swaps, and convertible bonds. Presentation is done using equity, interest rate, and volatility derivative products. A short introduction to computational methods necessary for pricing derivatives is provided. | Prerequisites: Matriculation into MS Financial Engineering or permission of the department.

This course focuses on quantitative methods and financial modeling. Probability theory, stochastic processes and optimization are studied and applied to a broad variety of financial problems and their derivatives. Topics include probability spaces; conditional probability; densities; distributions; density estimators; multivariate probability; moment-generating functions; random walks; Markov processes; Poisson processes; and the Brownian-motion process. | Prerequisite: Students are expected to know calculus and elementary probability and Graduate Standing

Topics include a review of probability and statistical inference and linear regression models. The focus of the course is time series analysis with special attention to the modeling of financial stock prices and returns. Volatility modeling and estimation will be also addressed through the analysis of intra-day trading data. | Prerequisite: FRE-GY 6083 and a working knowledge of statistics. Matriculation into MS Financial Engineering or permission of the department.

This course introduces financial engineers to robust risk-based valuation methods in discrete and continuous time. This includes four major applications: cash flows, traded derivative contracts, nontraded and embedded derivatives, and corporate assets & liabilities. - “Cash flows” refers to risk-free and risky payments or expenditures. - “Traded derivatives” include a high level treatment of forward contracts and the most commonly traded option contracts. - “Nontraded and embedded derivatives” refer to contingent cash flows created in the normal processes of contracting and asset management - “Corporate assets” refer to claims to cash flows owned and managed by corporations - “Corporate liabilities” refers to corporate-issued securities or other payment obligations incurred by corporations. | Prerequisite: Graduate Standing

This course introduces the techniques and problems of Financial Risk Management and Asset Pricing. It emphasizes risk finance and attitudes; Value at Risk; risk measurement principles; valuation and expected utility and their relevance in the valuation and the pricing of financial investments; insurance; management of derivatives; and risk management. Throughout, risk-management application problems are explored., The course introduces and focuses on the fundamental principles of the Arrow-Debreu state preference theory used to price derivatives and other assets in complete markets. Risk neutral-Binomial models in option pricing; essential elements of Ito calculus; and the Black-Scholes model for pricing options are introduced and applied to practical financial decision making and risk management problems. Prerequisite: Graduate Standing

This course focuses on issues involved in processing financial transactions—from order execution to final settlement of transactions—and operational risk in general. The course examines the procedures and market conventions for processing, verifying, and confirming completed transactions; resolving conflicts; decisions involved in developing clearing operations or purchasing clearing services; the role played by clearing houses; and numerous issues associated with cross-border transactions. The course also examines the effects of transaction processing, liquidity management, organizational structure, and personnel and compliance on the nature of operational risk. Qualitative and quantitative measures of operational risk are discussed. | Prerequisite: FRE-GY 6153 and Graduate Standing

The course discusses advanced topics in hedging exposures, with emphasis on adaptation of the mathematics to the real world. Examines applications in quantitative finance. Methods in the hedging of cash flows and liabilities for corporations and for option traders are covered. A synthesis is made of both theory and historical hedges traded. | Prerequisite: Graduate Financial Risk Engineering students only

Financial Institutions spend billions per year to exploit the latest development in information technology. This course introduces a framework with which to understand and leverage information technology. The technology components covered include telecommunications, groupware, imaging and document processing, artificial intelligence, networks, protocols, risk, and object-oriented analysis and design. the course also covers the entire technological-planning process specifically for financial institutions. | Prerequisite: Graduate Standing

This course complements the Foundations of Financial Technology by treating in-depth advanced topics in this rapidly changing field. Students prepare and present case studies applying the concepts covered in class. | Prerequisites: FRE-GY 6153.

This course provides the mathematical foundations of Option Pricing models. The techniques covered include arithmetic and geometric Brownian motion, first passage time, the reflection principle, the stochastic Ito integral, Ito differential Calculus, change of probability measure, martingales, Stochastic Differential Equations and Partial Differential Equations. Some of the pricing models considered are the European, Barrier, Asian and American options. These problems are either solved analytically by the martingale approach or numerically, by applying approximation and simulation methods. Since the same techniques allow the treatment of more complex financial products, examples of credit derivatives will be also presented. This course is a requirement in the Computational Finance Track | Prerequisite: FRE-GY 6083

Advanced numerical techniques for the solution of ordinary, partial and stochastic differential equations are presented. These techniques are analyzed both mathematically and using computer aided software that allows for the solution and the handling of such problems. In addition, the course introduces techniques for Monte Carlo simulation techniques and their use to deal with theoretically complex financial products in a tractable and practical manner. Both self-writing of software as well as using outstanding computer programs routinely used in financial and insurance industries will be used. | Prerequisite: FRE-GY 6083 and Graduate Standing

This course provides students with the analytical and financial modeling skills needed to value firms ranging from early-stage startups to mature giants. Students will use the material they learn to build and present a comprehensive valuation model for a mature company and will also present their valuations of a range of startups to their venture backers and management teams. There are no prerequisites other than graduate standing (the course will cover the basics of accounting and valuation), but students must be prepared to spend some time outside of class hours to interact with entrepreneurs and venture capitalists, both in-person at Tandon and in other countries over Zoom. | Prerequisites: Graduate Standing.

Financial econometrics has matured into a necessary and essential part of financial engineering that provides opportunities to deal with real and practical problems in finance. For example, techniques such as ARCH and GARCH and their subsequent development are used to estimate the volatility of underlying financial processes; the analysis of intra-day trading data that requires particular models and techniques; memory-based and fractal stochastic processes to study complex markets behaviors and copulas applied routinely to model- and estimate-dependent risks. These financial and risk problems require the application of advanced financial-econometric techniques, which the course provides from both theoretical and empirical-applied viewpoints. Selected cases provide a real-world sense of financial engineering when it is faced with financial-market reality and complexity. | Prerequisite: FRE-GY 6083 and Graduate Standing

This is an introduction to financial strategy for MS Financial Engineering students. The course focuses on the role of financial engineers and financial officers in developing and sustaining competitive advantage through the use of financial engineering analyses. | Prerequisites: Matriculation into a graduate program sponsored by the Department of Finance & Risk Engineering, or permission of the Department & FRE-GY 6023 and FRE-GY 6103.

This course examines the theories and empirical evidence related to mergers and acquisitions and other corporate transactions and reorganizations. The course looks at friendly mergers, hostile takeovers (including takeover and anti-takeover tactics), leveraged buyouts and bankruptcy. Throughout, the course examines the motives behind these transactions and reorganizations. | Prerequisites: FRE-GY 6103 and Graduate Standing

This course examines the body of analytical tools and measures that constitute modern fixed-income markets. The valuation of interest-rate sensitive cash flows is the unifying theme. Major topics include theories of term structure, institutional aspects of fixed-income markets and analytical techniques for managing interest-rate risk. Bond refunding, defeasance, corporate bonds, forwards, futures, options and interest-rate swaps are discussed. The course gives an overview of the major classes of fixed-income securities and the markets in which they trade. Among the major classes of fixed-income instruments discussed are Treasury and agency securities, mortgage-backed securities (including CMOs and Strips), asset-backed securities, municipals, floating and inverse floating rate securities. | Prerequisite: FRE-GY 6023, FRE-GY 6083, FRE-GY 6103 and Graduate Standing

This course provides a deep understanding of credit instruments from a qualitative and quantitative point of view. Students learn how to price credit derivatives and hedge credit risk. Both the structural and intensity models approaches are presented. Applications to a number of structured products are considered. | Prerequisites: FRE-GY 6411 and Graduate Standing

The level of economic and financial globalization combined with the growth of the multinational firms and virtual firms with no boundaries may have altered the future of finance and its risk engineering. The purpose of this course is to focus attention on the essential elements that both large financial firms and institutions are confronting worldwide, the challenges of national and international financial investments, currencies speculations and investments, regulation as well as managing risks in a strategic and macroeconomic environment. In such an environment, financial markets are multi-polar, geographically distributed with national entities pursuing their own economic and political agenda. | Prerequisites: FRE-GY 6411 and FRE-GY 6511 and matriculation into a graduate program sponsored by the Department of Finance & Risk Engineering, or permission of the Department

This course focuses on the quantitative foundations of portfolio management . It teaches the fundamental mathematical models such as the Markowitz, CAPM, and the Merton investment-consumption models, and discusses the issues related to the implementation of these models in practice to different types of portfolios. Finally, it also introduces some common portfolio construction and rebalancing techniques. | Prerequisites: Matriculation into a graduate program sponsored by the Department of Finance & Risk Engineering, or permission of the Department & FRE-GY 6083

This course covers a wide range theoretical and practical issues that arise in the management of equity and fixed income portfolios, including the classical (Markowitz) foundations of mean-variance optimization, the use of constraints, risk budgeting, robust (outlier-resistant) optimization, tail risk aware optimization, the estimation of expected returns, and the measurement and monitoring of portfolio performance using ideas from statistical process control. It will also require the use of Bloomberg’s PORT optimization tool to optimize, as well as to simulate the risk and return of, large portfolios. | Prerequisite: FRE-GY 6083, FRE-GY 6103 and Matriculation into a graduate program sponsored by the Department of Finance & Risk Engineering, or permission of Department.

This course covers quantitative methods of measurement and management of market risk as well as regulatory aspects of market risk management including both the current framework of Basel 2, 2.5, and 3 and the future methodology of FRTB. As the final project students produce a fully developed risk management system that includes risk calculations (sensitivities, VaR, Stressed VaR, Stress Analysis) on individual position and portfolio levels. | Co-requisite: FRE-GY 6711 and Graduate Standing.

This course is a research/case effort and can be handled in different ways at the discretion of the faculty supervisor. The course may involve a series of cases that are dissected and analyzed. It may involve teaming students with industry personnel for proprietary or non-proprietary research projects. Or it may involve thesis-type research. Generally, students work under faculty supervision, but the course is intended to be largely self-directed within guidelines established by the supervising faculty member. A significant written research component is required. Prerequisites: This course should be taken during the student’s final semester. | Prerequisites vary depending on the student’s track and the nature of the chosen project.

This course teaches students to use financial software tools commonly employed in industry. Examples include: @Risk, Yieldbook, Excel, R, and C++. | Prerequisites: Graduate Standing

The course introduces programming applications in financial modelling. Topics include variables, data types, input/output, plotting, selection statements, loop statements, functions, and classes, and implementation for Black-Scholes option pricing partial differential equation, Monte Carlo simulation, numerical methods for solving partial differential equations, and option pricing by Fourier transform.

This course introduces the free programming language R and its many applications to finance including risk management, portfolio construction, strategy development and testing, and trading and execution. Topics covered include financial time series analysis, advanced risk tools, applied econometrics, portfolio management, and derivatives valuation. Students will be required to write some code in R every week. | Prerequisites: Matriculation into a graduate program sponsored by the Department of Finance & Risk Engineering, or permission of the Department & FRE-GY 6123 and FRE-GY 6083

This course covers programming applications to financial engineering, including C++ and Java and the various common development environments for them. Topics include structured and object-oriented programming in C++ with applications to binomial options pricing, multi-threaded programming in Java with applets and graphical interfaces with applications to risk measurement tools, data-based manipulation and programming in SQL and standard database access libraries with applications to historical financial data series retrieval and management, and other advanced programming concepts important for financial engineering such as numerical techniques, trading systems, and large-scale software design. | Matriculation into a graduate program sponsored by the Department of Finance & Risk Engineering, or permission of the Department.

Current topics of particular importance in finance and risk engineering are analyzed and discussed. Selected topics are emphasized and provide focus for further study. Examples might include infrastructure and projects finance, international and global finance, economics and finance in developing countries, global finance in a global world, international investment strategies, finance and taxes, among others.

Current topics of particular importance in finance and risk engineering are analyzed and discussed. Selected topics are emphasized and provide focus for further study. Examples might include infrastructure and projects finance, international and global finance, economics and finance in developing countries, global finance in a global world, international investment strategies, finance and taxes, among others. | Prerequisites: advanced standing and instructor’s permission.

Prerequisite: Graduate Standing

Current topics of particular importance in finance and risk engineering are analyzed and discussed. Selected topics are emphasized and provide focus for further study. Examples might include infrastructure and projects finance, international and global finance, economics and finance in developing countries, global finance in a global world, international investment strategies, finance and taxes, among others. | Prerequisites: advanced standing and instructor’s permission.

Current topics of particular importance in finance and risk engineering are analyzed and discussed. Selected topics will be emphasized and provide focus for further study. Examples might include urban finance engineering, environmental finance, infrastructure and projects finance, real estate finance, insurance finance and derivatives, macro hedge funds management, among others. Prerequisites: advanced standing and instructor’s permission and Graduate Standing

Current topics of particular importance in finance and risk engineering are analyzed and discussed. Selected topics will be emphasized and provide focus for further study. Examples might include urban finance engineering, environmental finance, infrastructure and projects finance, real estate finance, insurance finance and derivatives, macro hedge funds management, among others. Prerequisites: advanced standing and instructor’s permission and Graduate Standing

Current topics of particular importance in finance and risk engineering are analyzed and discussed. Selected topics are emphasized and provide focus for further study. Examples might include infrastructure and projects finance, international and global finance, economics and finance in developing countries, global finance in a global world, international investment strategies, finance and taxes, among others. Prerequisites: advanced standing and instructor’s permission and Graduate Standing

This course provides a solid understanding of the creation and interpretation of modern financial statements. Topics include the reasons for financial statements, U.S. accounting principles and how they differ abroad, quality of financial information, financial ratios and their uses, cash-flow analysis, measurement of corporate performance. The course will also cover various methods of forecasting statements and a discussion of valuation. | Prerequisite: Graduate Standing or permission of FRE department.

In this course, the Career Development Office helps the student secure an internship. Students work under faculty supervision. However, the course is intended to be largely self-directed within the guidelines established by the supervising faculty member. A paper based on the internship work is required. | Prerequisites: This course should be taken after the student has successfully completed two Semesters and earned at least 18 credits. Prerequisites vary depending on the student’s track, the nature of the internship and Graduate Standing.

In this course, the Career Development Office helps the student secure an internship. Students work under faculty supervision. However, the course is intended to be largely self-directed within the guidelines established by the supervising faculty member. A paper based on the internship work is required. | Prerequisites: This course should be taken after the student has successfully completed two Semesters and earned at least 18 credits. Prerequisites vary depending on the student’s track, the nature of the internship and Graduate Standing.

In this project course, students work with faculty on proprietary or non-proprietary research projects. Generally, students work under faculty supervision. However, the course is intended to be largely self-directed within the guidelines established by the supervising faculty member. A significant written research component is required. | Prerequisites: This course should be taken after the student has successfully completed two Semesters and has earned at least 18 credits. Prerequisites vary depending on the student’s track, the nature of the project to be undertaken, and Graduate Standing.

Statistical arbitrage refers to strategies that combine many relatively independent positive expected value trades so that profit, while not guaranteed, becomes very likely. This course prepares students to research and practice in this area by providing the tools and techniques to generate and evaluate individual trading strategies, combine them into a coherent portfolio, manage the resulting risks, and monitor for excess deviations from expected performance. It introduces theoretical concepts such as cointegration, risk capital allocation, proper backtesting, and factor analysis, as well as practical considerations such as data mining, automated systems, and trade execution. Programming languages such as R, Python, or C++ will be used to present applications to data at low, intermediate and high frequency. | Prerequisites: Matriculation into a graduate program sponsored by the Department of Finance & Risk Engineering, or permission of the Department & FRE-GY 6123 and FRE-GY 6083

The goal of this course is to understand the technology behind financial forensics and regulatory systems. These include innovative database techniques ("dataveillance"), artificial intelligence, data mining, and non-parametric outlier methods used by the Secuities Exchange Commission (SEC), the Financial Industry Regulatory Authority (FINRA), as well as the FBI, and other federal and state agencies. Student teams will prepare and present projects or case studies applying hte concepts covered in class. | Prerequisite: FRE-GY 6153 and Graduate Standing

This course focuses on portfolio construction and rebalancing strategies such as momentum, value, and size strategies, among others. The course emphasizes backtesting and risk factor analysis as well as optimization to reduce tracking error. It will also address how a quantitative investment approach can help both individual and institutional investors make sound long-term investment decisions. | Prerequisite: FRE-GY 6123 and Graduate Standing

Algorithmic trading refers to the utilization of special computer programs in an order management system that restructure an order into a sequence of sub-orders based on the dimensions of submission time, price, size, and side. The goal of this course is to survey several algorithmic strategies used by financial institutions and to understand their implementation in the context of order management systems and standard financial protocols (such as FIX and FIXatdl). Student teams will prepare and present projects or case studies applying the concepts covered in class. | Prerequisites: FRE-GY 6153 and Graduate Standing

The fast-growing field of news analytics requires large databases, fast computation, and robust statistics. This course introduces the tools and techniques of analyzing news, how to quantify textual items based on, for example, positive or negative sentiment, relevance to each stock, and the amount of novelty in the content. Applications to trading strategies are discussed, including both absolute and relative return strategies, and risk management strategies. Students will be exposed to leading software in this cutting-edge space. | Prerequisites: FRE-GY 6153 and FRE-GY 7221 and Graduate Standing

This is an on-line quantitative course especially geared toward Master of Science in Financial Engineering students. The course covers the statistical tools needed to model and estimate the joint dynamics of markets. Included are: - topics in multivariate statistics that are relevant for risk management and portfolio management - machine learning models as generalizations of linear factor models, omnipresent across finance - the connection between the estimation/calibration of machine learning models and classical and Bayesian econometrics - backtesting and model/estimation risk in the context of decision theory - distributional stress-testing for risk management and portfolio/business construction for portfolio management. The final exam may be administered on-line or in-person. | Prerequisite: Matriculation into MS Financial Engineering or permission of FRE department

This course covers the theory of Machine Learning and its fundamental applications in the field of Financial Engineering. Supervised, unsupervised, and reinforcement learning paradigms are discussed. | Prerequisites: Matriculation into MS Financial Engineering or permission of the FRE department

Current topics of particular importance in finance and risk engineering are analyzed and discussed. Selected topics are emphasized and provide focus for further study. Examples might include Financial Economics, Macroeconomics and Finance, the Bond market, the securities markets, Derivatives markets, Contract Theory, Credit and Counterparty Risks, Banking Finance and others. | Prerequisites: Graduate standing and instructor’s permission

The course analyzes and discusses current topics of particular importance in finance and risk engineering. Selected topics are emphasized and provide focus for further study. Examples can include Behavioral Finance, Personal Finance, Investment Theories and Alternative Finance, Corporate and Financial Responsibility, Financial Ethics, Hedge Funds Investment Strategies and their Management and macro hedge funds management, among others. | Prerequisites: Graduate standing and instructor’s permission.

Current topics of particular importance in Actuarial Science are analyzed and discussed. Course topics may include for example: Pension Funds management, Actuarial Science and Social Security, Life Insurance, Insurance and Financial Products design and management. | Prerequisite: Advanced standing and instructor’s permission.

Current and selected topics of particular importance in finance and risk engineering are analyzed and discussed. Selected topics are emphasized and provide a focus for further study. Topics include Credit Risk and Credit Derivatives, Quantitative Methods in Rare Events, Energy, Oil and Water Finance as well as advanced topics in financial econometrics and computational finance. | Prerequisites: Graduate standing and instructor’s permission.

Current and selected topics of particular importance in Actuarial Science and in the insurance- finance convergence are analyzed and discussed. Course topics may include Risk Engineering and the Insurance Business, Principles of Insurance Management in a Dynamic and Global Setting, Finance-insurance convergence. | Prerequisite: Advanced standing and instructor’s permission.

Current topics of particular importance in finance and risk engineering are analyzed and discussed. Selected topics are emphasized and provide a focus for further study. Examples can include urban finance engineering, environmental finance, infrastructure and projects finance, real-estate finance, insurance finance and derivatives, and macro hedge funds management. | Prerequisites: Graduate standing and instructor’s permission.

Current topics of particular importance in financial information services and technology are analyzed and discussed. Selected topics are emphasized and provide focus for further study. Examples might include, natural language processing, sentiment analysis, alternative data, advanced deep learning techniques, and others. |Prerequisites: Graduate Standing and instructor's permission.

This course provides a comprehensive introduction to the mathematical foundations of stochastic systems and stochastic controls in discrete time. The course also explores the applications of stochastic controls in the theoretical developments of modern machine learning, including reinforcement learning, generative diffusion models, deep neural network training, and fine-tuning large language models. | Prerequisites: PhD standing or Permission from FRE Department. Co-requisites: (Recommended but not required): ECE-GY 6253 or ECE-GY 6233 (or similar).

Current topics of particular importance in asset pricing are analyzed and discussed. Selected topics are emphasized and provide focus for further study. Examples might include, financial modeling, financial statement analysis, portfolio optimization with dynamic programming, market microstructure, and others. |Prerequisites: Graduate Standing and instructor's permission.

Current topics of particular importance in financial engineering are analyzed and discussed. Selected topics are emphasized and provide focus for further study. Examples might include machine learning with big data, fixed income securities, quantitative investing strategies, and others. |Prerequisites: Graduate Standing and instructor's permission.

Current topics of particular importance in risk management are analyzed and discussed. Selected topics are emphasized and provide focus for further study. Examples might include climate change risk, event driven finance, mathematics of machine learning, Markov chains, and others. |Prerequisites: Graduate Standing and instructor's permission.

In this research course, students undertake proprietary or non-proprietary research and write a thesis-type research paper. Generally, students work under faculty supervision. However, the course is intended to be largely self-directed within guidelines established by the supervising faculty member. | Prerequisites: Graduate Standing. This course should be taken during the student’s final semester. Prerequisites vary depending on the student’s track and the nature of the thesis project.