Open Source Cross-Sectional Asset Pricing
Federal Reserve Board of Governors · University of Cologne
Abstract
We provide data and code that successfully reproduces nearly all cross-sectional stock return predictors. Our 319 characteristics draw from previous meta-studies, but we differ by comparing our t-stats to the original papers’ results. For the 161 characteristics that were clearly significant in the original papers, 98% of our long-short portfolios find t-stats above 1.96. For the 44 characteristics that had mixed evidence, our reproductions find t-stats of 2 on average. A regression of reproduced t-stats on original long-short t-stats finds a slope of 0.88 and an R2 of 82%. Mean returns are monotonic in predictive signals at the characteristic level. The remaining 114 characteristics were insignificant in…
Citation impact
- FWCI
- 83.88
- Percentile
- 100%
- References
- 0
Authors
2Topics & keywords
- Business
- Open source
- Consumption-based capital asset pricing model
- Asset (computer security)
- Finance
- Capital asset pricing model
- Computer science
- Computer security