Wasserstein Distance-Based Feature Engineering for Enhancing Forecasting and Asset Allocation Insights

Abstract This study evaluates the Wasserstein distance — a metric rooted in optimal transport theory — as a distribution-aware feature input to financial price forecasting and as a dissimilarity input to the Hierarchical Risk Parity (HRP) portfolio construction framework. Using thirty financial asse...

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Xehetasun bibliografikoak

Egile nagusia:	Insu Choi
Formatua:	Artigo
Hizkuntza:	Inglês
Argitaratua:	Springer 2026-05-01
Saila:	International Journal of Computational Intelligence Systems
Gaiak:	Wasserstein distance Price forecasting Asset allocation Hierarchical risk parity Decision tree Explainable artificial intelligence
Sarrera elektronikoa:	https://doi.org/10.1007/s44196-026-01382-0
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