Optimization of the Dow Jones industrial average using the Treynor-Black model with appraisal weighting
DOI:
https://doi.org/10.18381/eq.v23i2.7400Abstract
Objective: To evaluate whether historical performance a]g allows the dynamic weighting of the Dow Jones Industrial Average components to be optimized using the Treynor–Black model and to improve performance as related to the index.Methodology: For the assets that compose the DJIA in each period, α is estimated using CAPM and multifactor models to construct an active portfolio weighted by the appraisal ratio (a/idiosyncratic variance), applying trailing rolling windows and no leverage. The paper also adds a chronological 80%-20% temporal validation and a progressive Jensen alpha estimated with a 252-day rolling window.Results: The CAPM-based model achieves an average annual return close to 13.8% compared to 7.8% for the index, with an approximate 66.9% probability of outperforming it and a superior risk-return relationship. The 80%-20% temporary validation preserves the advantage out of sample: in the OOS block, the portfolio records a mean return of 13.7% versus 10.3% for the DJIA and an average progressive Jensen alpha of 0.0470.Limitations: The results depend on the stability of a, changes in market regimes, sensitivity in the estimation of specific risk, and implementation costs that are not modeled in the validation exercise.Originality: It integrates performance-based allocation (appraisal), preserving temporary comparability with the DJIA.Conclusions: Appraisal-based weighting improves relative performance when the signals are statistically robust.Downloads
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