Publication Type
Journal Article
Version
submittedVersion
Publication Date
1-2020
Abstract
For conditional time-varying factor models with high dimensional assets, this article proposes a high dimensional alpha (HDA) test to assess whether there exist abnormal returns on securities (or portfolios) over the theoretical expected returns. To employ this test effectively, a constant coefficient test is also introduced. It examines the validity of constant alphas and factor loadings. Simulation studies and an empirical example are presented to illustrate the finite sample performance and the usefulness of the proposed tests. Using the HDA test, the empirical example demonstrates that the FF three-factor model (Fama and French, 1993) is better than CAPM (Sharpe, 1964) in explaining the mean-variance efficiency of both the Chinese and US stock markets. Furthermore, our results suggest that the US stock market is more efficient in terms of mean-variance efficiency than the Chinese stock market.
Keywords
Conditional alpha test, High dimensional data, Mean-variance efficiency, Spline estimator, Time-varying coefficient
Discipline
Econometrics
Research Areas
Econometrics
Publication
Journal of Business and Economic Statistics
Volume
38
Issue
1
First Page
214
Last Page
227
ISSN
0735-0015
Identifier
10.1080/07350015.2018.1482758
Publisher
Taylor & Francis
Citation
MA, Shujie; LAN, Wei; SU, Liangjun; and TSAI, Chih-Ling.
Testing alphas in conditional time-varying factor models with high dimensional assets. (2020). Journal of Business and Economic Statistics. 38, (1), 214-227.
Available at: https://ink.library.smu.edu.sg/soe_research/2177
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1080/07350015.2018.1482758
Comments
SMU Economics and Statistics Working Paper Series 09-2018