This course builds on Asset Pricing I. The course focuses on empirical asset pricing. We cover reduced-form factor models, including equity factor models and term-structure models, as a parsimonious representation of the stochastic discount factor, and methods to estimate and test these models. We examine models of subjective belief formation of investors as explanations for the empirically observed risk premium variation, as well as asset demand system approaches to identify and estimate asset pricing models. We further explore machine-learning approaches to empirical asset pricing, leveraging them to enhance conventional prediction, estimation, and inference with respect to expected returns, risk premia, factor-mimicking portfolios, the stochastic discount factor and optimal portfolios, alphas, and models of the risk-return trade-off, while also addressing their limitations and criticisms by highlighting when, where, and why algorithms may fail.
