We survey recent methodological contributions in asset pricing using factor models and
machine learning. We organize these results based on their primary objectives: estimating …

Recent studies document strong empirical support for multifactor models that aim to explain
the cross-sectional variation in corporate bond expected excess returns. We revisit these …

ABSTRACT A Bayesian asset pricing test is derived that is easily computed in closed form
from the standard F‐statistic. Given a set of candidate traded factors, we develop a related …

Failing to account for transaction costs materially impacts inferences drawn when evaluating
asset pricing models, biasing tests in favor of those employing high‐cost factors. Ignoring …

This study examines the predictability of cryptocurrency returns based on investors' risk
premia. Prior studies that have examined the predictability of cryptocurrencies using various …

Non-standard errors capture variation due to differences in research design choices. We
document large variation in design choices in the context of asset pricing factor models and …

We decompose corporate bond and equity index returns into duration-matched government
bond returns and the excess returns over this duration-matched counterfactual, which we …

When expected returns are linear in asset characteristics, the stochastic discount factor
(SDF) that prices individual stocks can be represented as a factor model with GLS cross …

I compare commonly employed factor models across 50 non-US developed and emerging
market countries by ranking them based on their maximum Sharpe ratios. Consistent with …

We compare major factor models and find that the Stambaugh and Yuan (2016) 4-factor
model is the overall winner in the time-series domain. The Hou, Xue, and Zhang (2015) q …