R&D Alpha Factor Analysis
A comprehensive research platform examining the relationship between R&D investment intensity and long-term shareholder returns for S&P 500 companies over 25+ years of data.
Key Research Findings
Platform Features
Built with academic rigor for practitioners. All methodology is documented, code is open source, and results are reproducible.
Rolling Window Analysis
5, 10, and 20-year rolling windows with Fama-French July-June return convention
Statistical Tests
ANOVA, Welch t-tests, HAC corrections, effect sizes (eta-squared, Cohen's d)
Factor Spanning Tests
Regression against Fama-French factors to test R&D premium independence
Transaction Cost Model
Realistic implementation costs with turnover, spreads, and market impact
Investable ETF
Live portfolio construction with sector-neutral weighting and backtest
Publication Snapshots
Frozen research results for reproducibility and audit trail
Research Methodology
The platform implements academic-grade methodology for analyzing the R&D factor premium. Companies are sorted into quintiles by R&D intensity (R&D expense / revenue), and portfolio returns are calculated using the Fama-French July-June convention to avoid look-ahead bias.
Statistical inference uses HAC-adjusted standard errors (Newey-West) to account for overlapping window autocorrelation. Effect sizes are reported alongside p-values to demonstrate economic significance.
All results are from a publication-ready snapshot system that ensures reproducibility and provides a frozen baseline for audit.
Explore the research platform
Access the full interactive analysis, methodology documentation, and investable strategy construction.