Introduces cap-axis integral diagnostic revealing zero-alpha violations on cap-rank subspaces in factor models using 1967-2024 CRSP data.
Which Portfolios? The Construction Dependence of Factor Model Performance
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
abstract
Factor-model performance depends not only on the model but also on how test assets are constructed. We form characteristic-unsorted random portfolios from a broad CRSP universe and vary stock selection, initial weighting, holding, and rebalancing. Rankings shift materially: buy-and-hold favors FF5 and FF6, whereas daily constant-weighting favors FF3, the most stable model across designs. Although q5 attains the highest maximum Sharpe ratio in factor-spanning tests, it leaves comparatively large and construction-sensitive pricing errors on random portfolios. These results reflect construction-specific weighting of each model's pricing-error vector. Test-asset construction, including dynamic weight management, is therefore a design choice in model evaluation.
fields
q-fin.GN 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Decomposing the market into body and tail reveals q5 produces systematic offsetting leg alphas at daily frequency despite strongest spanning, a pattern removed by random splits and attenuated monthly.
citing papers explorer
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A Cap-Axis Integral Diagnostic of Factor Models
Introduces cap-axis integral diagnostic revealing zero-alpha violations on cap-rank subspaces in factor models using 1967-2024 CRSP data.
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Anatomy of the Market: A Body-Tail Test of Factor Models
Decomposing the market into body and tail reveals q5 produces systematic offsetting leg alphas at daily frequency despite strongest spanning, a pattern removed by random splits and attenuated monthly.