Metaheuristic Approaches to Portfolio Optimization

Metaheuristic Approaches to Portfolio Optimization

Jhuma Ray (RCC Institute of Information Technology, India), Anirban Mukherjee (RCC Institute of Information Technology, India), Sadhan Kumar Dey (RCC Institute of Information Technology, India) and Goran Klepac (RCC Institute of Information Technology, India)
Projected Release Date: March, 2019|Copyright: © 2019 |Pages: 300
ISBN13: 9781522581031|ISBN10: 1522581030|EISBN13: 9781522581048|DOI: 10.4018/978-1-5225-8103-1

Description

Control of an impartial balance between risks and returns has become important for investors, and having a combination of financial instruments within a portfolio is an advantage. Portfolio management has thus become very important for reaching a resolution in high-risk investment opportunities and addressing the risk-reward tradeoff by maximizing returns and minimizing risks within a given investment period for a variety of assets.

Metaheuristic Approaches to Portfolio Optimization is an essential reference source that examines the proper selection of financial instruments in a financial portfolio management scenario in terms of metaheuristic approaches. It also explores common measures used for the evaluation of risks/returns of portfolios in real-life situations. Featuring research on topics such as closed-end funds, asset allocation, and risk-return paradigm, this book is ideally designed for investors, financial professionals, money managers, accountants, students, professionals, and researchers.

Topics Covered

The many academic areas covered in this publication include, but are not limited to:

  • Active Portfolio Management
  • Asset Allocation
  • Black-Litterman Model
  • Closed-End Funds
  • Evolutionary Computation
  • Machine Learning
  • Open-End Funds
  • Risk-Return Paradigm
  • Simulated Annealing
  • Trade Volume

Table of Contents and List of Contributors

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