Wei Liu
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Wei Liu has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- James W. Kolari
Texas A&M University
14 shared publications - Seppo Pynnönen
University of Vaasa
13 shared publications - Huiling Liao
Applied Mathematics, Illinois Institute of Technology, Chicago, IL 60616, USA
1 shared publication - Jianhua Z. Huang
The Chinese University of Hong Kong, Shenzhen
1 shared publication
Latest Publications
- Open Access
- 1 July 2025
- Published by MDPI AG in Journal of Risk and Financial Management
- Vol. 18 (7) , 362
A Quantum Leap in Asset Pricing: Explaining Anomalous Returns
This paper investigates the ability of asset pricing models to explain the cross-section of average stock returns of anomaly portfolios. A large sample of 286 anomaly portfolios are employed. We perform out-of-sample cross-sectional regression tests of both prominent asset pricing models and a relatively new model dubbed the ZCAPM. Empirical tests strongly support the lesser known ZCAPM but not other multifactor models. Further analyses of out-of-sample mispricing errors of the models reveal that the ZCAPM provides much more accurate pricing of anomaly portfolios than other models. We conclude that anomalies are anomalous to popular multifactor models but not the ZCAPM. By implication, the efficient market hypothesis is supported.
- 1 July 2025
- Published by MDPI AG in Journal of Risk and Financial Management
- Vol. 18 (7) , 362
Open AccessA Quantum Leap in Asset Pricing: Explaining Anomalous Returns
This paper investigates the ability of asset pricing models to explain the cross-section of average stock returns of anomaly portfolios. A large sample of 286 anomaly portfolios are employed. We perform out-of-sample cross-sectional regression tests of both prominent asset pricing models and a relatively new model dubbed the ZCAPM. Empirical tests strongly support the lesser known ZCAPM but not other multifactor models. Further analyses of out-of-sample mispricing errors of the models reveal that the ZCAPM provides much more accurate pricing of anomaly portfolios than other models. We conclude that anomalies are anomalous to popular multifactor models but not the ZCAPM. By implication, the efficient market hypothesis is supported.
- 1 January 2023
- Published by Springer Nature
- p. 225-234
Mutual Fund Portfolios
- 1 January 2023
- Published by Springer Nature
- p. 43-55
Multifactor Asset Pricing Models
- 1 January 2023
- Published by Springer Nature
- p. 237-247
The Future of Investment Practice, Artificial Intelligence, and Machine Learning
- 1 January 2023
- Published by Springer Nature
- p. 237-247
The Future of Investment Practice, Artificial Intelligence, and Machine Learning
- 1 January 2023
- Published by Springer Nature
- p. 191-206
Long Only Efficient Portfolios
- 1 January 2023
- Published by Springer Nature
- p. 207-223
The Beta-Zeta Risk Architecture of the Mean-Variance Parabola
- 1 January 2023
- Published by Springer Nature
- p. 207-223
The Beta-Zeta Risk Architecture of the Mean-Variance Parabola
- 1 January 2023
- Published by Springer Nature
- p. 59-69
A New Asset Pricing Model: The ZCAPM
- 1 January 2023
- Published by Springer Nature
- p. 123-148
Building the Global Minimum Variance Portfolio G
- 1 January 2023
- Published by Springer Nature
- p. 123-148
Building the Global Minimum Variance Portfolio G