In this book, the authors present the main concepts, theoretical backgrounds, and the very recent innovative applications of asset allocation in finance that are necessary for an understanding of the current academic research and practices. The main aim of this book is to be an up-to-date resource for academic researchers, students, and practitioners in finance. Recent developments in technology have enabled complex and high-capacity computations that one could have hardly imagined before, resulting in a revolutionary effect on the finance industry as well as on asset allocation practices. The content of this book covers both the traditional theory building up the foundations of asset allocation as well as the very recently proposed asset allocation strategies consisting of the applications of non-parametric rank-based approaches and machine learning algorithms. This leads the audience from the theory and discussions of the past to today's innovative ideas, their applications, challenges, and prospects. The intended audience for this book is researchers, undergraduate and graduate students in the field of economics and finance. Moreover, the book will also be useful to practitioners working in the finance industry, such as financial analysts, consultants, investment officers, portfolio managers and other finance professionals who are making investment recommendations and/or actively investing.
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