Pınar Kaya Soylu

A multi-stage machine learning approach to portfolio selection and weight optimization for pairs trading

A multi-stage machine learning framework for portfolio selection and weight optimization in high-frequency crypto-asset pairs trading that decomposes the allocation problem into economically meaningful stages and allows each decision layer to be modeled according to its own statistical structure is proposed.