Phd class: Empirical Asset Pricing

Empirical Asset Pricing

This course is intended for Ph.D. students in Finance. It focuses on selected topics in empirical asset pricing. We will start from the notion and tests of Market Efficiency, including recent developments in Machine Learning. Then, we discuss the theory behind the tests of Asset Pricing models, starting from CAPM. We will examine the main failures of this model (size effect, value premium, momentum, low volatility, profitability, other anomalies). Next, we will consider some of the developments in cross sectional asset pricing (conditional models, multi-factor models). In the second part of the course, we will focus on explanations for the persistence of anomalies. In particular, we will discuss the literature on the limits of arbitrage and slow moving capital. We will also discuss the role of institutional investors in distorting asset prices.

The econometric tools that will encounter include: Linear Regression, Maximum Likelihood, Generalized Method of Moments, simple Machine Learning approaches. Since the focus of the class is on applications, the discussion of the econometric tools will be informal.

The grading is based on a final exam and on class presentations.