01 / Overview
Objective
Apply the Treynor–Black framework to five S&P 100 equities and test whether security-specific alpha can improve the risk-adjusted profile of a market portfolio.
02 / Methodology
Analytical approach
- 01
Collect 60 months of returns for five S&P 100 equities and the market.
- 02
Estimate CAPM and Fama–French three-factor regressions.
- 03
Separate systematic exposure from residual alpha and idiosyncratic risk.
- 04
Weight the active sleeve by alpha relative to residual variance.
- 05
Combine the active and passive portfolios and evaluate beta and Sharpe ratio.
03 / Evidence
Key inputs and outputs
04 / Findings
What the analysis showed
- The optimized portfolio maintained below-market beta at 0.93.
- Alpha weighting improved the portfolio’s risk-adjusted profile to a 0.74 Sharpe ratio.
- Factor regressions provided a disciplined separation of market exposure from security-selection signals.
05 / Conclusion
Investment conclusion
The model demonstrates a systematic bridge between security analysis and portfolio construction: active weights are earned through residual alpha and constrained by idiosyncratic risk rather than conviction alone.
06 / Limitations
Boundaries of the work
- The five-name universe is small and sensitive to the estimation window.
- Historical factor relationships may not persist out of sample.
- Transaction costs, turnover, and estimation error are not fully modeled.
- This project is not yet documented in the public GitHub repository.
07 / Tools & skills