Algorithms for Solving Financial Portfolio Design Problems: Emerging Research and Opportunities

Algorithms for Solving Financial Portfolio Design Problems: Emerging Research and Opportunities

Fatima Zohra Lebbah (Ecole Supérieure en Génie Electrique et Energétique (ESG2E), Oran, Algeria & Laboratoire de Recherche en Informatique de Sidi Bel-Abbès (LabRI-SBA), Equipe de Computational Intelligence and Soft Computing (CISCO), Ecole Supérieure en Informatique de Sidi Bel-Abbès, Algeria)
Release Date: December, 2019|Copyright: © 2020 |Pages: 198|DOI: 10.4018/978-1-7998-1882-3
ISBN13: 9781799818823|ISBN10: 1799818829|EISBN13: 9781799818830|ISBN13 Softcover: 9781799818854

Description

In the current scope of economics, the management of client portfolios has become a considerable problem within financial institutions due to the amount of risk that goes into assigning assets. Various algorithmic models exist for solving these portfolio challenges; however, considerable research is lacking that further explains these design problems and provides applicable solutions to these imperative issues.

Algorithms for Solving Financial Portfolio Design Problems: Emerging Research and Opportunities is a pivotal reference source that provides vital research on the application of various programming models within the financial engineering field. While highlighting topics such as landscape analysis, breaking symmetries, and linear programming, this publication analyzes the quadratic constraints of current portfolios and provides algorithmic solutions to maximizing the full value of these financial sets. This book is ideally designed for financial strategists, engineers, programmers, mathematicians, banking professionals, researchers, academicians, and students seeking current research on recent mathematical advances within financial engineering.

Topics Covered

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

  • Breaking Symmetries
  • Financial Risks
  • Global Search
  • Greedy Algorithms
  • Landscape Analysis
  • Linear Programming
  • Local Search
  • Matricial Models
  • Neighborhood Function
  • Programming Performance

Table of Contents and List of Contributors

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