Real problems are formulated into tractable mathematical models, which allow for an analysis of various approaches.Attention is focused on solutions.Provides a unified treatment of the models discussed , presents a critique of the existing results, and points out potential research directions.

We examine how allowing portfolio weights to depend on individual stocks' measurable characteristics, in the spirit of Brandt, Santa-Clara, and Valkanov (2009), shapes the return distribution of optimal out-of-sample portfolios for investors with varying levels of risk aversion. All investors...

This study provides a comprehensive review of machine learning (ML) applications in the fields of business and finance. First, it introduces the most commonly used ML techniques and explores their diverse applications in marketing, stock analysis, demand forecasting, and energy marketing. In...