TY - JOUR
T1 - Winners from Winners
T2 - A Tale of Risk Factors
AU - Chib, Siddhartha
AU - Zhao, Lingxiao
AU - Zhou, Guofu
N1 - Publisher Copyright:
Copyright: © 2023 INFORMS.
PY - 2024/1
Y1 - 2024/1
N2 - Starting from twelve distinct factors from the recent literature, plus twelve principal components (PCs) of anomalies unexplained by the initial factors, a Bayesian comparison of approximately seventeen million models in terms of marginal likelihoods and posterior model probabilities shows that {Mkt, MOM, IA, ROE, MGMT, PERF, PEAD, FIN}, plus the nonconsecutive principal components, {PC1, PC5, PC7} are the best supported risk factors. Pricing tests and annualized out-of-sample Sharpe ratios for tangency portfolios suggest that this asset pricing model should be used for computing expected returns, assessing investment strategies and building portfolios.
AB - Starting from twelve distinct factors from the recent literature, plus twelve principal components (PCs) of anomalies unexplained by the initial factors, a Bayesian comparison of approximately seventeen million models in terms of marginal likelihoods and posterior model probabilities shows that {Mkt, MOM, IA, ROE, MGMT, PERF, PEAD, FIN}, plus the nonconsecutive principal components, {PC1, PC5, PC7} are the best supported risk factors. Pricing tests and annualized out-of-sample Sharpe ratios for tangency portfolios suggest that this asset pricing model should be used for computing expected returns, assessing investment strategies and building portfolios.
KW - Bayesian model comparison
KW - anomaly
KW - factor models
KW - portfolio analysis
KW - stochastic discount factor
UR - https://www.scopus.com/pages/publications/85182882192
U2 - 10.1287/mnsc.2022.4668
DO - 10.1287/mnsc.2022.4668
M3 - Article
AN - SCOPUS:85182882192
SN - 0025-1909
VL - 70
SP - 396
EP - 414
JO - Management Science
JF - Management Science
IS - 1
ER -