TY - JOUR
T1 - An Empirical Assessment of Characteristics and Optimal Portfolios
AU - Lamoureux, Christopher G.
AU - Zhang, Huacheng
N1 - Publisher Copyright:
© The Author(s) 2024. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved.
PY - 2024/9/1
Y1 - 2024/9/1
N2 - We implement a dynamically regularized, bootstrapped two-stage out-of-sample parametric portfolio policy to evaluate characteristics’ efficacy in the conditional stock return-generating process in the metric of expected power utility. Traditional characteristics, such as momentum and size afforded large utility gains before 1999. These opportunities have since vanished. Overfitting—imprecision in weight estimation—is correlated with the optimal portfolio’s variance. Therefore, it is not a problem for power utility investors with coefficients of relative aversion greater than four. For more risk-tolerant investors, we successfully reduce estimation error by increasing the curvature of the loss function relative to the investor’s utility function.
AB - We implement a dynamically regularized, bootstrapped two-stage out-of-sample parametric portfolio policy to evaluate characteristics’ efficacy in the conditional stock return-generating process in the metric of expected power utility. Traditional characteristics, such as momentum and size afforded large utility gains before 1999. These opportunities have since vanished. Overfitting—imprecision in weight estimation—is correlated with the optimal portfolio’s variance. Therefore, it is not a problem for power utility investors with coefficients of relative aversion greater than four. For more risk-tolerant investors, we successfully reduce estimation error by increasing the curvature of the loss function relative to the investor’s utility function.
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U2 - 10.1093/rapstu/raae006
DO - 10.1093/rapstu/raae006
M3 - Article
AN - SCOPUS:85200818583
SN - 2045-9920
VL - 14
SP - 450
EP - 480
JO - Review of Asset Pricing Studies
JF - Review of Asset Pricing Studies
IS - 3
ER -