MFE Academics

Learn from Leaders in the Field

The UCLA Anderson MFE curriculum merges theory and principle with up-to-the-minute business practice. While MFE programs are available at many universities, UCLA Anderson is one of the few top-tier business schools worldwide to offer the MFE degree. Our dynamic curriculum, taught by a world-renowned finance faculty, merges technical and theory-based pedagogy with practical immersion through a summer internship and a corporate-sponsored Applied Finance Project.

Course Schedule


Earn 72 units through coursework and the hands-on Applied Finance Project.
During the summer quarter, MFE students work on a required Internship.

Fall Winter Spring Summer Fall
September – December January – March April – June June – August September - December
Financial Accounting
Stochastic Calculus
Career Development Series
Trading, Market Frictions and FinTech
Derivative Markets
Empirical Methods in Finance
Fixed Income Markets
Career Development 

Financial Risk Management
Computational Methods in Finance
Special Topics in FE
(choose 2 out of 3)
- Data Analytics and Machine Learning
- Quantitative Asset Management
- Balancing Purpose and Profit: Environmental, Social, and Governance (ESG) For Managers and Investors
- Other Select MBA Electives

Summer Internship Applied Finance Project
Fieldwork/Research in Financial Engineering
Special Topics in FE
(choose 3 out of 4)
- Credit Markets
- Statistical Arbitrage
- Behavioral Finance
- Introduction to the Finance of Blockchain and Cryptocurrency
-Select MBA Electives

Please note: Our courses are taught in Python or R

How The Instruction at UCLA Anderson is Different


As part of the Capital Analysis and Stress Testing team in Goldman Sachs, I work with different divisions of the firm to ensure they have adequate capital to withstand market turmoil in the annual Federal Reserve stress test. The MFE program equipped me with a diverse skill set through their classes such as Financial Risk Management, Fixed Income, Accounting and Derivatives which gave me the necessary range of skills to understand different functionalities of the Firm. In addition, their focus in the development of soft skills helped me improve my communication and presentations skills which are an integral part of my career.

— Meghana Rao (MFE ‘18)
Controller in Goldman Sachs
New York City

A Unique MFE Offering 

The MFE Program is proud to offer Communicating with Impact, workshops within our required Career Development Series, which will make all the difference in your career. Learn the art of persuasion and effective articulation of technical concepts and executions, so that your work can be efficiently conveyed to decision-makers. You will find that your choices of words are dependent not only on the content, but on context and delivery — it’s not just what you say, but how and to whom you say it.

Course Descriptions

Investments (Fall)

Professor: Mikhail Chernov

This course covers the essentials of asset pricing and portfolio choice, standard discounted cash flow approaches and no-arbitrage framework for valuing financial securities. It introduces basic paradigms of asset pricing, such as the capital asset pricing model (CAPM), arbitrage pricing theory (APT) and the Fama-French three-factor model. Students learn the development and illustration of dynamic portfolio selection and optimization approaches.

Financial Accounting (Fall)

Professor: Alex Dill

This is an introduction to the concepts of financial accounting and their underlying assumptions, including an examination of the uses and limitations of financial statements. Procedural aspects of accounting are discussed in order to enhance understanding of the content of financial statements. The course emphasizes using accounting information in the evaluation of business performance and risk. The use of accounting information in research studies is also examined.

Econometrics (Fall)

Professor: Dan Yavorsky

This course covers the theory and in-depth application of linear regression. Topics include simple linear regression, multiple regression, prediction in a multiple-regression model, residual diagnostics, detection of outliers and violations of stochastic assumptions.

Stochastic Calculus (Fall)

Professor: Stavros Panageas

This course covers the economic, statistical and mathematical foundations of derivatives markets. It presents the basic discrete-time and continuous-time paradigms used in derivatives finance, including an introduction to stochastic processes, stochastic differential equations, Ito's Lemma and key elements of stochastic calculus. The economic foundations of the Black–Scholes no-arbitrage paradigm are covered, as are the Girsanov theorem and changes of measure, the representation of linear functionals, equivalent martingale measures, risk-neutral valuation, fundamental partial differential equation representations of derivatives prices, market prices of risk and Feynman–Kac representations of solutions to derivatives prices. The role of market completeness and its implications for the hedging and replication of derivatives is covered in depth.

Trading, Market Frictions and FinTech (Winter)

Professor: Jinyuan Zhang

This course examines processes and mechanisms by which securities' prices are formed. This price formation process emphasizes the most important function of the secondary market---information transmission. Detailed topics including exchange design rules, market designs, asymmetric information, liquidity provision and pricing, high-frequency trading, market crashes, and short-selling.

Derivative Markets (Winter)

Professor: Eric Reiner 

Derivatives are both exchange-traded and over-the-counter securities. The derivatives markets are the world's largest and most liquid. This course focuses on the organization and role of put and call option markets, futures and forward markets, as well as their interrelations. The emphasis is on arbitrage relations, valuation and hedging with derivatives. The course also covers the implementation of derivatives trading strategies, the perspective of corporate securities as derivatives, the functions of derivatives in securities markets and recent innovations in derivatives markets.

Empirical Methods in Finance (Winter)

Professor: Lars Lochstoer

This course covers the probability and statistical techniques commonly used in quantitative finance. Students use estimation application software in exercises to estimate volatility, correlations and stability.

Fixed Income Markets (Winter)

Professor: Francis Longstaff

This course provides a quantitative approach to fixed-income securities and bond portfolio management, with a focus on fixed-income security markets. The course covers the pricing of bonds and fixed-income derivatives, the measurement and hedging of interest rate risk, dynamic models of interest rates and the management of fixed-income portfolio risk.

Financial Risk Measurement and Management (Spring)

Professor: Valentin Haddad

This course examines financial risk measurement and management, including market risk, liquidity risk, settlement risk, model risk, volatility risk and kurtosis risk.

Computational Methods in Finance (Spring)

Professor: Levon Goukasian

This course covers the quantitative and computational tools used in finance. It introduces numerical techniques such as the implementation of binomial and trinomial option pricing, lattice algorithms for computing derivative prices and hedge ratios, simulation-based algorithms for pricing American options and the numerical solution of the partial differential equations that appear in financial engineering.

Data Analytics and Machine Learning (Elective - Spring)

Professor: Lars Lochstoer

Study of data science, oriented toward decision making and predictive analytics. Topics include predictive and prescriptive models, panel regressions, text analysis, model validation and selection, models for discrete outcomes, and machine learning. Uses industry-leading Python statistical environment. Examples and homework focus on finance applications including return and earnings prediction, default prediction and lending markets, portfolio choice, and trading models.

Quantitative Asset Management (Elective - Spring)

Professor: Bernard Herskovic

This course emphasizes the application of state-of-the-art quantitative techniques to asset management problems. The course covers asset-pricing models in depth, portfolio optimization and construction and dynamic strategies such as pairs trading, long-term and short-term momentum trades and strategies that address behavioral finance anomalies. The course also discusses major forms of asset-management structures, such as mutual funds, hedge funds, ETFs and special investment vehicles, and examines some of the primary types of trading strategies used by these organizations.

Applied Finance Project (Fall)

Professor: Eric Reiner

Every MFE student is required to complete an Applied Finance Project (AFP) that explores a quantitative finance problem. The AFP enables candidates to apply the knowledge and tools they developed through MFE coursework by working directly with clients.

Credit Markets (Elective - Fall)

Visiting Professor: Patrick Augustin

This course provides an introduction to the building and implementation of credit models for use by financial institutions and quantitative investors. The course covers the basics of corporate debt securities and provides an in-depth introduction to the credit derivatives markets. Structured credit products such as cash and synthetic collateralized debt obligations (CDOs) are discussed.

Statistical Arbitrage (Elective - Fall)

Professor: Valentin Haddad

Study of quantitative equity market-neutral strategies. At one end of spectrum are high-capacity strategies with multi-year time horizons. At other end are low-capacity strategies with milli-second time horizons. Students place themselves squarely in middle of this trade-off, enabling them to study both slow and fast signals. This is sweet spot where one can have sufficiently high Sharpe ratio to be rewarded on one's own merit rather than on one's verbal ability to explain away bad performance; and one can escape from technologically intensive rat race to have fastest computer co-located closest to stock exchange. Rather than give students list of alphas that are supposed to work, study gives them toolkit necessary to develop their own sources of alpha. Statistical arbitrage is less of formula than ongoing process: one fixes airplane as one is flying it.

Behavioral Finance (Elective - Fall)

Professor: Avanidhar Subrahmanyam

Introduction and explanation of evidence of anomalous return behavior found in stock markets. Presentation of details on how "quant" firms apply evidence to manage equity portfolios, and seek to explain trading activity in equity markets. Exploration of some evidence that contradicts standard risk-return paradigm. Introduction of some psychological biases that researchers suspect are inherent to investors. Some results from psychology literature employed to explain irrationalities encountered in financial markets. Discussion of what stock trading strategies to avoid and what strategies to adopt. Latest evidence on why individual investors trade, and how individual and institutional investors form their portfolios.

Introduction to the Finance of Blockchain and Cryptocurrency (Elective - Fall)

Professor: Ben Tsai

This course will introduce students to the financial concepts in the cryptocurrency industry.  Basic topics covered include historical performance, valuation, regulatory concerns, and infrastructure of the crypto market.  It will then move to derivatives, centralized and decentralized financing (DeFi), and staking.  Finally, the course will discuss asset and wealth management in the blockchain/cryptocurrency space, including asset tokenization.

Career Development Series (Fall and Winter)

Career development programming supplies students with necessary career-management skills and tools to effectively identify, compete, and secure professional opportunities.

Special Topics in Financial Engineering (Electives)

Choose five of eight courses offered, two during Spring term and three during the last Fall term. Special topics courses consist of an in-depth examination of problems or issues in an area of current concern in financial engineering.