Applying Particle Swarm Optimization: New Solutions and Cases for Optimized Portfolios

This book provides an in-depth explanation of particle swarm optimization (PSO) and its application to portfolio optimization problems. It demonstrates how to implement Markowitz's portfolio optimization approach using PSO and expands on the Markowitz model to improve the solution-finding process. It is a valuable resource for researchers, teachers, engineers, managers, and practitioners interested in applying PSO to portfolio optimization.

Format: Hardback
Length: 351 pages
Publication date: 14 May 2021
Publisher: Springer Nature Switzerland AG

This comprehensive book delves into the theoretical framework of particle swarm optimization (PSO) and its application to portfolio optimization problems. The overarching objective of portfolio optimization is to identify a solution that maximizes expected returns while managing various levels of risk. According to H. Markowitz's portfolio selection theory, as new assets are incorporated into an investment portfolio, the overall risk decreases, contingent upon the correlations between asset returns. At the same time, the expected return on the portfolio represents the weighted average of the expected returns for each asset.

The book offers a detailed explanation of PSO, showcasing its implementation in the context of Markowitz's portfolio optimization approach. Furthermore, it extends the Markowitz model and explores the use of various algorithms to enhance the solution-finding process. In essence, this book serves as a valuable resource for researchers, educators, engineers, managers, and practitioners seeking to employ the PSO technique in portfolio optimization.

Weight: 711g
Dimension: 235 x 155 (mm)
ISBN-13: 9783030702809
Edition number: 1st ed. 2021