Everything about our program prepares you to make an impact on the job from day one, starting with the curriculum.

We carefully craft your course of study to integrate the mathematical, statistical, and computer science methods you learn with the theoretical frameworks and institutional settings in which they are applied. All of the classes, starting with the pre-program coursework, build upon the previous ones to provide a solid foundation that reinforces what you have already learned. 

The Berkeley Haas MFE curriculum is as dynamic as the finance industry itself. Faculty members contribute to, and share, pioneering research. A committee of leading industry practitioners advises the program director on current trends and future needs. 

Degree Requirements

MFE students must successfully complete 28 units of coursework (1 unit = 15 class hours), including the Applied Finance Project, plus an internship or industry/independent study project. The 10- to 12-week internship/industry project or independent study project is a required condition for graduation.


March 16 – 19, 2020

The program kicks off with an informative and social orientation. During this week-long introduction to the program, you'll get to know other new students and gain a sense of what the classroom experience will hold. The orientation features team-building exercises, lectures, and workshops on special topics, including a thorough overview of the job market and career resources.

Spring Term

March 23 – May 15, 2020 (8 weeks)

Investments and Derivatives

MFE 230A (2 units) - Nicolae Garleânu

This course covers the basic theories of asset pricing. It begins with the standard discounted cash flow analysis and generalizes this approach to develop the No Arbitrage Pricing technique for security valuation. Applications including fixed income securities, derivatives and contingent claims will be considered. The course will then examine the basic principles of optimal portfolio theory and consider special models of equilibrium asset pricing, including the Capital Asset Pricing Model and related Factor Models. Applications to equity pricing and portfolio performance evaluation will be explored. Programming and analytical exercises will be assigned.

Empirical Methods in Finance

MFE 230E (3 units) - Martin Lettau

This course reviews probability and statistical techniques commonly used in quantitative finance. It includes a review of normal, log-normal, and CEV distributions. This course covers estimation and non-parametric techniques commonly used in finance (MLE, GMM, GARCH) and introduces students to financial databases and to estimation application software for exercises in estimating volatilities and correlations and their stability.

Stochastic Calculus with Asset Pricing Applications

MFE 230Q (2 units) - Dmitry Livdan

This course introduces the concepts and tools of stochastic calculus as required for effective pricing of complex financial derivatives in continuous time. The course stresses the practical applications of stochastic differential equations, Ito integrals, and measure transformations as required in advanced financial engineering practice and for the understanding of asset pricing theory. The material discussed in this course is used extensively in the some of the more advanced classes.

Positioning Yourself for Opportunities in the Financial World

MFE 230T (1 unit) - Linda Kreitzman

This course is exclusively designed for the Master of Financial Engineering (MFE) students or those interested in preparing for a career in finance. The goal of the course is to ensure your success as an MFE and beyond.

Financial Institutions Seminar

Individuals from financial services firms will describe the work of financial engineers in their firms and the kinds of skills and personal attributes they are seeking for this work.

Summer Term

June 1 – July 24, 2020

Derivatives: Quantitative Methods

MFE 230D (2 units) - Eric Reiner

This course emphasizes the pricing of derivatives in continuous time, from the formulation of the pricing problem to the implementation of computational and numerical solution techniques. The course consists of three parts. In the first part, asset pricing theory is used to set up the pricing problem for a wide range of instruments with features such as early exercise, jumps, and path dependencies. The second part focuses on simulation methods for pricing both European and early exercise derivatives. The third part shows how to effectively use advanced finite difference techniques for solving a wide array of pricing problems.

Fixed Income Markets

MFE 230I (3 units) - Richard Stanton

This course provides a quantitative approach to fixed income securities and bond portfolio management. The focus is on fixed income security markets, pricing and uses for portfolio management or for hedging interest rate risk. The course covers bond mathematics, term structure measurement and theory, immunization techniques and the modern theory of bond pricing, including the pricing of credit-risky bonds. It also covers derivative instruments (futures, swaps, options, exotic instruments). There will be extensive use of application and programming exercises.

Financial Data Science

MFE 230P (2 units) - Laurent El Ghaoui

This course proposes a guided tour through optimization models arising in practical Finance. These problems include ones that are traditionally associated with optimization, including asset and liability management, asset pricing, and portfolio optimization. We also describe optimization models arising in model calibration, prediction and estimation, and risk analysis. The course includes some recent approaches to the analysis of other kinds of financial data, such as text (financial news) data.

Positioning Yourself for Opportunities in the Financial World

MFE 230T (1 unit) - Linda Kreitzman

Further preparation of the students for placement in internship and full time positions is done throughout the seminar, both for finance and data science positions.  

Financial Institutions Seminar Series

The 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.

Fall Term

August 10 – October 2, 2020 (8 weeks)


Financial Risk Measurement and Management

MFE 230H (2 units) - Amir Kermani

This course examines financial risk measurement and management, including market risk, credit risk, liquidity risk, settlement risk, model risk, volatility risk, kurtosis risk and other types of financial risks. It includes risk measurement techniques for different types of contracts and portfolios (equity, fixed income, currency) such a duration, portfolio Beta, factor sensitivities, Value at Risk™, dynamic portfolio distribution analysis and extreme value analysis. It also includes risk management techniques for different types of problems such as trading desk risk management, total portfolio market exposure limits, counterpart credit exposure limits, and funding liquidity exposure limits.

Choose 5 units of electives*:

International Equity & Currency Markets

MFE 230G (2 units) - Ron Kahn and Richard Lyons

This course reviews various aspects of equity and currency markets and provides models of and historical evidence on the average returns and volatility of returns on equities, on the trade-to-trade equity price behavior, on trading volume and patterns, and on primary financial risks. The determination of spot and forward exchange rate and the volatility, volume, high frequency dynamics, and dealer behavior in currency markets are considered. Practical considerations involved in the implementation of various strategies are considered.

Asset Backed Security Markets

MFE 230M (2 units) - Nancy Wallace

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.

Independent Study

MFE293 (1 - 3 units) - Choose an advisor

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

High Frequency Finance

MFE 230X (2 units) - Terry Hendershott and Dmitry Livdan

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.


       More Electives: Topics in Financial Engineering (2020-2021)
        Offerings can change from year to year.

Introduction to Deep Learning

MFE230T (1 unit) – Gert Lanckreit

Topics include Supervised, Unsupervised, and Reinforcement learning Industry Tools to Develop Machine Learning Systems. Data Collection and Processing (APIs, web scraping, and Hadoop, MapReduce, Spark) Multilayer Perceptron (Deep Neural Nets, Training Deep Neural Nets, Convolutional, Neural Networks, Recurring Neural Networks, Word2Vec). The course will end with a session on solving practical problems with deep learning.

Deep Learning for Financial Time-Series

MFE230T (1 unit) - Laurent El Ghaoui

Topics include time-series models and challenges; Markov chains, stochastic processes, spectral representation, long memory Processes “shallow models”: ARMA, filter banks, SVR/SVM, random forests and Probabilistic graphical networks; deep models: RNNs and CNNs for sequential modeling, attention networks deep learning frameworks, basic models and causal loss functions for financial time-series prediction. Distributed representations of discrete entities and applications in Natural Language Processing data and model fusion strategies, irregular time series low cost modeling strategies (model compression, cascades and low rank modeling).


Internship Period

October 12, 2020 – January 8, 2021

The Internship/Special Topics in Finance project is a required condition for graduation. The internship or approved, on-site project takes place from mid-October to mid-January. 

Because of the school's reputation and close ties to the best firms, Haas has an exceptional record of helping students secure internships, consistently placing 100% of students each year.

Winter Term

January 11 – March 5, 2021 (8 weeks)


Applied Finance Project

MFE 230O (3 units) - Eric Reiner

This is an applied project exploring an unresolved finance problem that is met in practice and involves the development or use of a quantitative financial technique. Participation requires prior approval of the supervising faculty member

Choose 4-6 units electives*:

Dynamic Asset Management

MFE 230K (2 units) - Kevin Coldiron

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).

Behavioral Finance

MFE 230S (2 units) -Greg LaBlanc

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.

Independent Study (by exception only)

MFE293 (1 - 3 units) - Choose an advisor

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

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.

Financial Innovation with Data Science Applications

MFE 230J (2 units) – Ananth Madhavan and Christine Parlour

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.

*Please note that not all electives will be offered every year. This schedule is tentative and will be updated every term.

Pedro Zonari, MFE 18

Pedro Zonari

MFE 18

New York, New York

“There is no fat in the Berkeley MFE program. Every course and hands-on learning experience is calibrated to expand your knowledge. The group assignments reflect the real world and are intended to make your learning fast and efficient. The condensed one-year format meant I was out in the workforce that much faster.”