We offer a range of elective courses which may change each year. Below is a sampling of electives that we have recently offered.

Fall Electives

Asset Backed Security Markets

MFE 230M (2 units)

This empirical course will apply the latest tools of economics and finance to provide a detailed understanding of the structure and operation of the securitized bond markets in the U.S., including what can go wrong. As one of the major innovations in U.S. capital markets, there is robust demand from a wide variety of employers for 230M graduates who intimately understand the complexities of securitization and can work with the massive datasets required thereby. Discussing 230M class projects in interviews provides an opportunity to showcase that skillset to potential employers. We will extend the study of fixed-income securities and credit risk with advanced topics on securitized lending, mortgages, and mortgage-backed securities, applying these lessons to many other asset-backed securities including asset-backed commercial paper, auto loans, credit card receivables, crowdsourced lending, equipment, third-world debt, repo, commercial leases, and energy derivatives. Of necessity, problem sets will involve developing Big Data skills to handle the massive individual-loan datasets underlying many asset-backed securities, as well as Monte Carlo simulation and option-based pricing techniques. We will consider the basic mechanics of structuring ABS deals, including how to value, trade, rate, and stress-test such securities, as well as the risk management techniques employed in both the pooling and slicing (tranching) phases of the securitization process. Finally, we consider a proposal to use medical securitization to cure cancer.

Decentralized Finance

This course covers an overview of DeFi, Blockchain Technology, Smart Contracts, Decentralized Lending, as well as other topics at the intersection of the DeFi and traditional finance ecosystems. 

Equity Markets

MFE 230G (1 unit) 

The course cover active equity portfolio management including the more general quantitative theory of active management. We will view active management as an optimization problem trading off expected returns against risk and the cost of trading. Modules will cover forecasting returns, risk, and cost. We will also cover how to research active strategies and the analytics that support the enterprise. We will discuss various categories of active equity strategies and provide an introduction to current approaches.

Financial Practice Seminars

MFE students are encouraged to attend weekly discussions held by finance practitioners. In the first term speakers discuss jobs available to graduates of the MFE and the skills needed to contribute to a firm's mission. In the second term, speakers provide insights into the way the financial world is changing: new products and needs; evolving data and information systems; and similar topics.

High Frequency Finance

MFE 230X (2 units)

This course covers topics in high frequency finance and discusses recent developments in market microstructure, electronic trading and data modeling. The course is aimed at students who are considering careers in financial engineering or quantitative trading at institutions involved in automated securities trading on electronic platforms.

Independent Study

MFE293 (1 - 3 units) 

The Independent Study course is your opportunity to do research in an area of interest to you, in which there are no existing courses.

Our students work directly with financial institutions, hedge funds, Fintech firms, etc., on (unpaid) projects for which they receive academic credit.

Deep Learning and Applications Part 1

MFE230T Part 1 (1 unit) 

Topics include supervised, unsupervised, and reinforcement learning industry tools to develop machine learning systems. We will look at Trees, Multilayer perceptron, ANN, DNN, CNN, NN for time series data, Transformers, Bert and GPT3, among other areas.

Deep Learning and Applications Part 2

MFE230T (1 unit) 

The course is on deep/machine learning with applications in finance.  The course aims to provide students with a thorough understanding how deep/machine learning models can or cannot be applied in financial engineering contexts. One of the main goals of this class is to teach students experimental methods to evaluate published models in a critical way. The class therefore aims to prepare students for a real-life situation faced by many quantitative finance researchers in industry. In addition, students will be exposed to an array of data sources, both standard and alternative in nature.

Currency Markets

The course is dedicated to currency markets: market organization, determination of spot and forward rates, and links to international finance more broadly. Topics include: FX arrangements and capital controls, Different approaches to exchange rate determination/forecasting, Conventional and unconventional monetary policy and exchange rate, among other areas.

Winter Electives

Behavioral Finance

MFE 230S (2 units)

This course covers elements of behavioral decision theory and its implication in financial markets. Focus is on the psychological processes by which people make judgments and decisions, and the heuristics and biases associated with these decisions.

Dynamic Asset Management

MFE 230K (2 units) 

Covers the strategies for achieving various investment objectives for portfolios/ instruments (equity, fixed income, currency, mortgages, non-traded assets) and applications (investment funds, pension funds, insurance companies, bank investment portfolios).

Financial Innovation with Data Science Applications

MFE 230J (2 units)

The objective of the course is to explore modern financial innovation through the lens of data science, and through a combination of lectures, cases, guest speakers, and applied data science projects. By the end of the course, the students will better understand the most significant financial innovations today and the critical role quantitative research can play in determining success.