We survey the nascent literature on machine learning in the study of financial markets. We
highlight the best examples of what this line of research has to offer and recommend …

This chapter surveys recent econometric methodologies for inference in large dimensional
conditional factor models in finance. Changes in the business cycle and asset …

Complexity in Factor Pricing Models Page 1 Complexity in Factor Pricing Models Antoine
Didisheim Shikun (Barry) Ke Bryan Kelly Semyon Malamud Uni. Melbourne Yale Yale EPFL AFA …

This paper develops a method informed by data and models to recover information about
investor beliefs. Our approach uses information embedded in forward-looking asset prices in …

We propose a generalized aggregation approach for model averaging. The entropy-based
optimal criterion is a natural choice for aggregating information from many “globally” …

We derive a universal thermodynamic uncertainty relation (TUR) that applies to an arbitrary
observable in a general Markovian system. The generality of our result allows us to make …

Applied researchers using structural models under rational expectations (RE) often confront
empirical evidence of misspecification. In this paper we consider a generic dynamic model …

This article is motivated by the need to bridge some gap between modern asset pricing
theory and recent developments in econometric methodology. While asset pricing theory …

This paper performs an out-of-sample comparison of linear factor asset pricing models from
an economic perspective under predictability. I assess the economic value added of several …

We propose a regularized generalized method of moments (RegGMM) approach to
estimating time‐varying coefficient models via a ridge fusion penalty with a high …