ABSTRACT
Asset pricing anomalies are the foundations of factor investing. This chapter presents simple ideas and concepts: basic factor models and common empirical facts time-varying nature of returns and risk premia. It provides the reader with lists of articles that go much deeper to stimulate and satisfy curiosity. The chapter intends to give a broad overview and covers the essential themes so that the reader is guided towards the relevant references. It reviews and mentions articles published essentially in the first family of journals. Broadly speaking, the rationale behind factor investing is that the financial performance of firms depends on factors, whether they be latent and unobservable, or related to intrinsic characteristics. The chapter highlights the need of replicability of factor premia and echo the recent editorial by Harvey. It appears undeniable that the intersection between the two fields of asset pricing and machine learning offers a rich variety of applications.
