The Asset Management curriculum is still under development, but it will cover a range of topics, including investment theory, investment practices, and trading and portfolio execution. Courses will be taught (and often co-taught) by Yale SOM’s full-time finance faculty, leaders from the Yale Investments Office, and guest lecturers from firms such as AQR and Bridgewater.
Principal and Head of Global Stock Selection, AQR Capital Management
In our industry, we are constantly looking for bright people who have rigorous quantitative training plus an understanding of how theories and conceptual tools can be applied to markets. The Yale finance faculty are at the forefront of research in asset valuation and market dynamics, and they maintain close relationships with investors, providing students of the Yale Master’s in Asset Management with exceptional instruction on both sides of that equation. By co-teaching many classes with practitioners, they strengthen the bridge between theory and practice—an ideal environment in which to start a career in asset management.
The following are sample course descriptions being developed for the Asset Management program. Details may change before program launch in fall 2021.
Asset Management First Principles
This course will cover the basic first principles of asset management from leaders in the field from both academia and practice. Topics covered will be the principle lessons of diversification, risk-return tradeoff, the usefulness of models and data, long-term versus short-term performance evaluation, asset allocation, investment horizon, fiduciary responsibility, and the societal impact of asset management. This course will set the stage broadly for the variety of topics and issues that will be covered throughout the program.
Asset Pricing Theory
This course provides the theoretical background and economics underlying asset pricing theory used to describe the levels and dynamics of asset prices in markets. The course will cover the classic CAPM as well as multifactor models motivated from several theories. Conditional asset pricing models and macroeconomic models will also be discussed.
This course derives the empirical models and methods for testing asset pricing theory and analyzing financial security price data. The course is primarily empirically focused with heavy data applications. Students will replicate studies and design their own tests of theories and apply them to the data. The second part of the semester focuses on the latest techniques for applying big data and machine learning to problems in asset management.
This course delves into quantitative factor investing, the basic building blocks of quantitative models of investing. We will explore the scientific evidence and theory behind factor investing and examine its applications including index funds, smart beta, quantitative hedge fund models, and performance evaluation. The course is primarily empirically focused with heavy data applications.
The field of behavioral finance tries to make sense of investor behavior, financial markets, and corporate finance using models that make psychologically realistic assumptions about the way people think, e.g., that allow for less than fully rational thinking. In this course, we cover both the classic contributions to the field and also the most recent research developments.
Financial markets provide investors with a rich set of opportunities to hedge and speculate on a multitude of risks, offering significant potential benefits to asset managers, individual investors, and firms exposed to such risks. In this course, we develop the framework needed to understand the financial instruments investors can use to trade many macroeconomic and financial risks.
This course introduces students to the context and practice of portfolio management. Students will have a chance to put into practice the quantitative and qualitative financial theories and tools. Teams build portfolios through the development of a value proposition, an assessment of client needs and constraints, a research plan, a trading and execution strategy, a risk analysis, client communication and performance attribution.
Hedge Fund Strategies
The class describes some of the main strategies used by hedge funds and proprietary traders and provides a methodology to analyze them. In class and through exercises and projects, the strategies are illustrated using real data, and students learn to use “backtesting” to evaluate a strategy. The class also covers institutional issues related to liquidity, margin requirements, risk management, and performance measurement. The class is highly quantitative.
Asset Management Colloquium
Four to five talks per semester by leaders in the field of asset management. Potential topics: real assets, crypto currencies, short-selling, venture capital, discretionary macro, data technology, risk management, and client relations.