GLOBAL CAPITAL MARKETS

An introduction to capital markets and investments providing an overview of financial markets and tools for asset valuation. Topics covered include the pricing of fixed-income securities (treasury markets, interest rate swaps futures, etc.), discussions on topics in credit, foreign exchange, sovereign ad securitized markets—private equity and hedge funds, etc.

• M 6 p.m.-8:30 p.m.
• Instructor: Siddhartha Ghosh Dastidar
  CULPA: 2 Info
• 3 points

TOPICS IN QUANTATIVE FINANCE

FINANCIAL ENG. FOR ESG FINANCE

ESG (Environmental, Social and Corporate Governance) Finance is a rapidly growing area of Investment Management – and Finance more broadly – that has received a lot of attention in the past several years from the investor community, financial regulatory agencies, and the general public alike. This course provides an introduction to ESG Finance from a financial engineer’s perspective. This course also discusses proliferation of newly available data sources and the associated quantitative techniques necessary to process those. A major component of this course is a discussion of Climate Risk, an area of particular focus due to its increasing general importance. The course includes an overview of both recent research and the evolving regulatory landscape in the climate risk space. An in-depth discussion of financial impact assessment of various climate risk-driven scenarios (climate risk stress testing) concludes the course.

• T 7:10 p.m.-9:40 p.m.
• Instructor: Cyril Shmatov
  Info
• 1.5 points

TOPICS IN QUANTATIVE FINANCE

TERM STRUCTURES& CREDIT MODELS

In this course, we will cover the basics of mathematical modeling of interest rates and credit derivatives. In the first part, we will cover basic interest rate derivatives, the Heath-Jarrow-Morton (HJM) 
framework, classic short rate models (for both interest rates and default intensities), and the numerical techniques used in practice for their calibration. In the second part, we will cover the basics 
of single-name derivatives modeling, and we will discuss pricing simple credit derivatives. We will also discuss correlation products and the most common techniques used for their pricing. In the third part, we will discuss some recent research papers addressing the use of adjoint algorithmic differentiation for the calculation of risk for interest rate and credit derivatives.

• W 5:40 p.m.-8:10 p.m.
• Instructor: Luca Capriotti
  Info
• 3 points

TOPICS IN QUANTITATIVE FINANCE

ALTERNATIVE INVESTMENTS

The search for better performance has led investors to explore Alternative Investments that are outside the traditional categories of exchange traded equities, Treasury Bonds, and other
investment-grade fixed income products. The field of Alternative Investments covers a wide range of products such as convertible bonds, Preferred Shares, Hedge Funds, Venture Capital, and
Cryptocurrencies. There is a growing need in the market for students with knowledge of these products and the practical and theoretical know how of valuing and risk managing these investments given that each product has it own nuances and anomalies. This course presents and studies some major Alternative Investment products and ways to evaluate and risk manage them.

• R 1:10 p.m.-3:40 p.m.
• Instructor: Khosrow Dehnad
  CULPA: 2 Info
• 1.5 points

FOR EXCH/RELATD DERIVATVS INST

Foreign exchange market and its related derivative instruments—the latter being forward contracts, futures, options, and exotic options. What is unusual about foreign exchange is that although it can rightfully claim to be the largest of all financial markets, it remains an area where very few have any meaningful experience. Virtually everyone has traded stocks, bonds, and mutual funds. Comparatively few individuals have ever traded foreign exchange. In part that is because foreign exchange is an interbank market. Ironically the foreign exchange markets may be the best place to trade derivatives and to invent new derivatives—given the massive two-way flow of trading that goes through bank dealing rooms virtually 24 hours a day. And most of that is transacted at razor-thin margins, at least comparatively speaking, a fact that makes the foreign exchange market an ideal platform for derivatives. The emphasis is on familiarizing the student with the nature of the foreign exchange market and those factors that make it special among financial markets, enabling the student to gain a deeper understanding of the related market for derivatives on foreign exchange.

• R 4:10 p.m.-6:40 p.m.
• Instructor: David Derosa
  CULPA: 4 h-index: 9 Info
• 1.5 points

STRUCTURED&HYBRID PRODUCTS

Prerequisite(s): IEOR E4700. Conceptual and practical understanding of structured and hybrid products from the standpoint of relevant risk factors, design goals and characteristics, pricing, hedging, and risk management. Detailed analysis of the underlying cash-flows, embedded derivative instruments, and various structural features of these transactions, both from the investor and issuer perspectives, and analysis of the impact of the prevailing market conditions and parameters on their pricing and risk characteristics. Numerical methods for valuing and managing risk of structured/hybrid products and their embedded derivatives and their application to equity, interest rates, commodities and currencies, inflation, and credit-related products. Conceptual and mathematical principles underlying these techniques, and practical issues that arise in their implementations in the Microsoft Excel/VBA and other programming environments. Special contractual provisions encountered in structured and hybrid transactions, and incorporation of yield curves, volatility smile, and other features of the underlying processes into pricing and implementation framework for these products.

• R 7:10 p.m.-9:40 p.m.
• Instructor: Alireza Javaheri
  Info
• 3 points

Programming for Financial Engineering

Covers C++ programming language, applications, and features for financial engineering, and quantitative finance applications. Note: restricted to IEOR MS FE students only.

• W 7:10 p.m.-9:40 p.m.
• Instructor: Sebastien Donadio
  Info
• 3 points

Deep Learning for OR and FE

Selected topics of interest in area of quantitative finance. Some topics include energy derivatives, experimental finance, foreign exchange and related derivative instruments, inflation derivatives, hedge fund management, modeling equity derivatives in Java, mortgage-backed securities, numerical solutions of partial differential equations, quantitative portfolio management, risk management, trade and technology in financial markets. Note: open to IEOR students only.

• Instructor: Ali Hirsa
  h-index: 8 Info
• 3 points

Applied Financial Risk Management

Applied Financial Risk Mg

Introduces risk management principles, practical implementation and applications, standard market, liquidity, and credit risk measurement techniques, and their drawbacks and limitations. Note: restricted to IEOR students only.

• TR 2:40 p.m.-3:55 p.m.
• Instructor: Allan M Malz
  CULPA: 1 Info
• 3 points

Financial Engineering Practitioners Semi

FE Seminar Series

Degree requirement for all MSFE first-year students. Topics in Financial Engineering. Past seminar topics include Evolving Financial Intermediation, Measuring and Using Trading Algorithms Effectively, Path-Dependent Volatility, Artificial Intelligence and Data Science in modern financial decision making, Risk-Based Performance Attribution, and Financial Machine Learning. Meets select Monday evenings.

• M 7 p.m.-9 p.m.
• 0 points

MSFE Quantitative and Computational Boot

MSFE Quant/Comp Bootcamp

Primer on quantitative and mathematical concepts. Required of all incoming MSFE students.

• 0 points

MASTERS RESEARCH OR PROJECT

Prerequisite(s): Approval by a faculty member who agrees to supervise the work. Independent work involving experiments, computer programming, analytical investigation, or engineering design.

• Instructor: Anish Agarwal
  Info
• Instructor: Shipra Agrawal
  h-index: 24 Info
• Instructor: Eric Balkanski
  h-index: 13 Info
• Instructor: Daniel Bienstock
  h-index: 38 Info
• Instructor: Agostino Capponi
  h-index: 19 Info
• Instructor: Rachel Cummings
  h-index: 16 Info
• Instructor: Antonius B Dieker
  CULPA: 10 h-index: 19 Info
• Instructor: Adam N Elmachtoub
  CULPA: 1 h-index: 13 Info
• Instructor: Yuri Faenza
  h-index: 11 Info
• Instructor: Vineet Goyal
  h-index: 21 Info
• Instructor: Ali Hirsa
  h-index: 8 Info
• Instructor: Anran Hu
  Info
• Instructor: Garud Iyengar
  CULPA: 6 h-index: 30 Info
• Instructor: Hardeep Johar
  Info
• Instructor: Cedric Josz
  CULPA: 2 h-index: 13 Info
• Instructor: Soulaymane Kachani
  CULPA: 12 Info
• Instructor: Yaren Kaya
  Info
• Instructor: Christian Kroer
  h-index: 16 Info
• Instructor: Daniel Lacker
  CULPA: 4 h-index: 13 Info
• Instructor: Henry Lam
  h-index: 17 Info
• Instructor: Fabrizio Lecci
  Info
• Instructor: Tianyi Lin
  Info
• Instructor: Uday Menon
  Info
• Instructor: Bento Natura
  Info
• Instructor: Jay Sethuraman
  CULPA: 10 Info
• Instructor: Karl Sigman
  CULPA: 15 Info
• Instructor: Clifford Stein
  CULPA: 31 Wikipedia h-index: 53 Info
• Instructor: Wenpin Tang
  h-index: 6 Info
• 1-3 points

MASTERS RESEARCH OR PROJECT

Prerequisite(s): Approval by a faculty member who agrees to supervise the work. Independent work involving experiments, computer programming, analytical investigation, or engineering design.

• Instructor: Wenpin Tang
  h-index: 6 Info
• Instructor: Kaizheng Wang
  CULPA: 1 h-index: 8 Info
• Instructor: Lily Xu
  Info
• Instructor: David D Yao
  CULPA: 5 Info
• Instructor: Yi Zhang
  CULPA: 2 Info
• Instructor: Xunyu Zhou
  h-index: 54 Info
• Instructor: Winsor Yang
  Info
• Instructor: Eric Stratman
  Info
• 1-3 points

FIELDWORK

Only for IEOR graduate students who need relevant work experience as part of their program of study. Final reports required. May not be taken for pass/fail credit or audited.

• 1-2 points

FIELDWORK

Only for IEOR graduate students who need relevant work experience as part of their program of study. Final reports required. May not be taken for pass/fail credit or audited.

• 1-2 points

FIELDWORK

Only for IEOR graduate students who need relevant work experience as part of their program of study. Final reports required. May not be taken for pass/fail credit or audited.

• 1-2 points

OPTIMIZATION I

Theory and geometry of linear programming. The simplex method. Duality theory, sensitivity analysis, column generation and decomposition. Interior point methods. Introduction to nonlinear optimization: convexity, optimality conditions, steepest descent, and Newton’s method, active set, and barrier methods.

• TR 10:10 a.m.-11:25 a.m.
• Instructor: Vineet Goyal
  h-index: 21 Info
• 4.5 points

Machine Learning and High-Dimensional Da

Mchn lrning&Hgh-dmntnl da

Discusses recent advances in fields of machine learning: kernel methods, neural networks (various generative adversarial net architectures), and reinforcement learning (with applications in robotics). Quasi Monte Carlo methods in the context of approximating RBF kernels via orthogonal transforms (instances of the structured technique). Will discuss techniques such as TD(0), TD(λ), LSTDQ, LSPI, DQN.

• M 7:10 p.m.-9:40 p.m.
• Instructor: Krzysztof M Choromanski
  Info
• 3 points

STOCHASTIC MODELING I

Advanced treatment of stochastic modeling in the context of queueing, reliability, manufacturing, insurance risk, financial engineering and other engineering applications. Review of elements of probability theory; exponential distribution; renewal theory; Wald’s equation; Poisson processes. Introduction to both discrete and continuous-time Markov chains; introduction to Brownian motion.

• TR 2:40 p.m.-3:55 p.m.
• Instructor: Karl Sigman
  CULPA: 15 Info
• 4.5 points

OPTIMIZATION & SIMULATION BOOTCAMP

• Instructor: Michael Miller
  CULPA: 18 h-index: 14 Info
• 0 points

ADVANCED TOPICS IN IEOR

Diffusion Models AI & RL

Selected topics in IEOR. Content varies from year to year. May be repeated for credit.

• M 2:40 p.m.-5:10 p.m.
• Instructor: Xunyu Zhou
  h-index: 54 Info
• 3 points

ADVANCED TOPICS IN IEOR

Agentic AI & Data Economy

Selected topics in IEOR. Content varies from year to year. May be repeated for credit.

• MW 1:10 p.m.-2:25 p.m.
• Instructor: Agostino Capponi
  h-index: 19 Info
• 3 points

ADVANCED TOPICS IN IEOR

Algo Predictions

Selected topics in IEOR. Content varies from year to year. May be repeated for credit.

• TR 11:40 a.m.-12:55 p.m.
• Instructor: Eric Balkanski
  h-index: 13 Info
• 3 points

ADVANCED TOPICS IN IEOR

Algorithmic GameTheory OR

Selected topics in IEOR. Content varies from year to year. May be repeated for credit.

• MW 10:10 a.m.-11:25 a.m.
• Instructor: Christian Kroer
  h-index: 16 Info
• 3 points

ADVANCED TOPICS IN IEOR

Foundations of Data Privacy

Selected topics in IEOR. Content varies from year to year. May be repeated for credit.

• T 2:40 p.m.-5:10 p.m.
• Instructor: Rachel Cummings
  h-index: 16 Info
• 3 points

ADVANCED TOPICS IN IEOR

Queues & Stoch Netwks

Selected topics in IEOR. Content varies from year to year. May be repeated for credit.

• W 2:40 p.m.-5:10 p.m.
• Instructor: David D Yao
  CULPA: 5 Info
• 3 points

RESEARCH

Before registering, the student must submit an outline of the proposed work for approval by the supervisor and the chair of the Department. Advanced study in a specialized field under the supervision of a member of the department staff. May be repeated for credit.

• Instructor: Anish Agarwal
  Info
• Instructor: Shipra Agrawal
  h-index: 24 Info
• Instructor: Eric Balkanski
  h-index: 13 Info
• Instructor: Daniel Bienstock
  h-index: 38 Info
• Instructor: Agostino Capponi
  h-index: 19 Info
• Instructor: Rachel Cummings
  h-index: 16 Info
• Instructor: Antonius B Dieker
  CULPA: 10 h-index: 19 Info
• Instructor: Adam N Elmachtoub
  CULPA: 1 h-index: 13 Info
• Instructor: Yuri Faenza
  h-index: 11 Info
• Instructor: Vineet Goyal
  h-index: 21 Info
• Instructor: Ali Hirsa
  h-index: 8 Info
• Instructor: Anran Hu
  Info
• Instructor: Garud Iyengar
  CULPA: 6 h-index: 30 Info
• Instructor: Hardeep Johar
  Info
• Instructor: Cedric Josz
  CULPA: 2 h-index: 13 Info
• Instructor: Soulaymane Kachani
  CULPA: 12 Info
• Instructor: Yaren Kaya
  Info
• Instructor: Christian Kroer
  h-index: 16 Info
• Instructor: Daniel Lacker
  CULPA: 4 h-index: 13 Info
• Instructor: Henry Lam
  h-index: 17 Info
• Instructor: Fabrizio Lecci
  Info
• Instructor: Tianyi Lin
  Info
• Instructor: Uday Menon
  Info
• Instructor: Bento Natura
  Info
• Instructor: Jay Sethuraman
  CULPA: 10 Info
• Instructor: Karl Sigman
  CULPA: 15 Info
• Instructor: Clifford Stein
  CULPA: 31 Wikipedia h-index: 53 Info
• Instructor: Wenpin Tang
  h-index: 6 Info
• 1-6 points

RESEARCH

Before registering, the student must submit an outline of the proposed work for approval by the supervisor and the chair of the Department. Advanced study in a specialized field under the supervision of a member of the department staff. May be repeated for credit.

• Instructor: Wenpin Tang
  h-index: 6 Info
• Instructor: Kaizheng Wang
  CULPA: 1 h-index: 8 Info
• Instructor: Lily Xu
  Info
• Instructor: David D Yao
  CULPA: 5 Info
• Instructor: Yi Zhang
  CULPA: 2 Info
• Instructor: Xunyu Zhou
  h-index: 54 Info
• Instructor: Winsor Yang
  Info
• Instructor: Eric Stratman
  Info
• 1-6 points