Abstract
The asset pricing literature emphasizes factor models that minimize pricing errors but overlooks unselected candidate factors that could enhance the performance of test assets. This paper proposes a framework for factor model selection and testing by (i) selecting the optimal model that spans the joint efficient frontier of test assets and all candidate factors, and (ii) testing pricing performance on both test assets and unselected candidate factors. Our framework updates a baseline model (e.g., CAPM) sequentially by adding or removing factors based on asset pricing tests. Ensuring model selection consistency, our framework utilizes the asset pricing duality: minimizing cross-sectionally unexplained pricing errors aligns with maximizing the Sharpe ratio of the selected factor model. Empirical evidence shows that workhorse factor models fail asset pricing tests, whereas our proposed 8-factor model is not rejected and exhibits robust out-of-sample performance.
| Original language | English |
|---|---|
| Publisher | Social Science Research Network (SSRN) |
| Number of pages | 48 |
| DOIs | |
| Publication status | Online published - 30 Jul 2023 |
Bibliographical note
Research Unit(s) information for this publication is provided by the author(s) concerned.Research Keywords
- anomalies
- factor efficiency
- stepwise selection
- GRS test
- model comparison
- Sharpe ratio