New Evidence on Conditional Factor Models
Journal article, Peer reviewed
Submitted version
Permanent lenke
http://hdl.handle.net/11250/2607759Utgivelsesdato
2018Metadata
Vis full innførselSamlinger
- Publikasjoner fra CRIStin - BI [1030]
- Scientific articles [2189]
Sammendrag
We estimate conditional multifactor models over a large cross section of stock returns matching 25 CAPM anomalies. Using conditioning information associated with different instruments improves the performance of the Hou, Xue, and Zhang (HXZ) (2015) and Fama and French (FF) (2015), (2016) models. The largest increase in performance holds for momentum, investment, and intangibles-based anomalies. Yet, there are significant differences in the performance of scaled models: HXZ clearly dominates FF in explaining momentum and profitability anomalies, while the converse holds for value–growth anomalies. Thus, the asset pricing implications of alternative investment and profitability factors (in a conditional setting) differ in a nontrivial way.