Finding 4693Emerging EvidenceValidation V0
This paper uniquely highlights the overlooked impact of prediction target transformationsuch as raw, standardized, or rank-based returnson machine learning accuracy and portfolio performance. Its systematic, cross-market empirical analysis challenges the fields focus on feature engineering, offering compelling evidence that target engineering is crucial and underexplored in quantitative finance and trading.
75%Confidence
1Evidence objects
v1Version
DraftStatus
Evidence trail
Supporting75% linkage confidence
This paper uniquely highlights the overlooked impact of prediction target transformationsuch as raw, standardized, or rank-based returnson machine learning accuracy and portfolio performance. Its systematic, cross-market empirical analysis challenges the fields focus on feature engineering, offering compelling evidence that target engineering is crucial and underexplored in quantitative finance and trading.
key_findings bullet 4 · key_findings
Inspect source: Getting the Target Right in Return Prediction →This Finding was extracted from the configured corpus. It is versioned, traceable, and may evolve through editorial review or new corpus evidence.