A 2026 study by Neil Saini tests the durability of five classical stock market factor premiums after 2010. Using data from the Ken French Data Library spanning 1963–2024, the analysis applies the Harvey-Liu-Zhu multiple testing correction framework. Findings show significant decay for most factors, with only the market premium remaining significant after accounting for transaction costs.
Use Cases
- Testing factor durability based on out-of-sample verification from 2010 onward.
- Evaluating statistical significance of factor premiums based on the Harvey-Liu-Zhu correction framework.
- Assessing the impact of transaction costs on factor profitability based on a 15 basis point assumption.
- Investigating data snooping bias in published financial anomalies based on factor return decay.
Strengths
- Analysis is pre-registered and reproducible, with code available on GitHub.
- Uses a long time series of factor returns from 1963 to 2024.
- Applies a rigorous multiple testing correction framework (t ≥ 3.0).
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment.
Provenance
- Source
- Ken French Data Library
- Collection Method
- Analysis of published factor returns.
- Time Range
- 1963–2024
- Freshness
- Last updated 2026-07-20 03:10:24; freshness should be verified.
- Geography
- null