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Fuzzy Portfolio Optimization

Advances in Hybrid Multi-criteria Methodologies

  • Pankaj Gupta
  • Mukesh Kumar Mehlawat
  • Masahiro Inuiguchi
  • Suresh Chandra

Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 316)

Table of contents

  1. Front Matter
    Pages 1-15
  2. Pankaj Gupta, Mukesh Kumar Mehlawat, Masahiro Inuiguchi, Suresh Chandra
    Pages 1-31
  3. Pankaj Gupta, Mukesh Kumar Mehlawat, Masahiro Inuiguchi, Suresh Chandra
    Pages 33-59
  4. Pankaj Gupta, Mukesh Kumar Mehlawat, Masahiro Inuiguchi, Suresh Chandra
    Pages 61-80
  5. Pankaj Gupta, Mukesh Kumar Mehlawat, Masahiro Inuiguchi, Suresh Chandra
    Pages 81-125
  6. Pankaj Gupta, Mukesh Kumar Mehlawat, Masahiro Inuiguchi, Suresh Chandra
    Pages 127-160
  7. Pankaj Gupta, Mukesh Kumar Mehlawat, Masahiro Inuiguchi, Suresh Chandra
    Pages 161-186
  8. Pankaj Gupta, Mukesh Kumar Mehlawat, Masahiro Inuiguchi, Suresh Chandra
    Pages 187-222
  9. Pankaj Gupta, Mukesh Kumar Mehlawat, Masahiro Inuiguchi, Suresh Chandra
    Pages 223-253
  10. Pankaj Gupta, Mukesh Kumar Mehlawat, Masahiro Inuiguchi, Suresh Chandra
    Pages 255-281
  11. Pankaj Gupta, Mukesh Kumar Mehlawat, Masahiro Inuiguchi, Suresh Chandra
    Pages 283-309
  12. Back Matter
    Pages 311-319

About this book

Introduction

This monograph presents a comprehensive study of portfolio optimization, an important area of quantitative finance. Considering that the information available in financial markets is incomplete and that the markets are affected by vagueness and ambiguity, the monograph deals with fuzzy portfolio optimization models. At first, the book makes the reader familiar with basic concepts, including the classical mean–variance portfolio analysis. Then, it introduces advanced optimization techniques and applies them for the development of various multi-criteria portfolio optimization models in an uncertain environment. The models are developed considering both the financial and non-financial criteria of investment decision making, and the inputs from the investment experts. The utility of these models in practice is then demonstrated using numerical illustrations based on real-world data, which were collected from one of the premier stock exchanges in India. The book addresses both academics and professionals pursuing advanced research and/or engaged in practical issues in the rapidly evolving field of portfolio optimization.

 

Keywords

Fuzzy decision theory Fuzzy returns Mean-variance model Membership functions for return and risk Multi-criteria portfolio selection model Possibilistic portfolio selection problem RCGA for optimization SVM optimization Subjective preference of the investor Uncertain variable

Authors and affiliations

  • Pankaj Gupta
    • 1
  • Mukesh Kumar Mehlawat
    • 2
  • Masahiro Inuiguchi
    • 3
  • Suresh Chandra
    • 4
  1. 1.Department of Operational Research Faculty of Mathematical SciencesUniversity of DelhiDelhiIndia
  2. 2.Department of Operational Research, Faculty of Mathematical SciencesUniversity of DelhiDelhiIndia
  3. 3.Department of Systems Innovation, Division of Mathematical Science for Social SystemsOsaka University,Graduate School of Engineering ScienceOsakaJapan
  4. 4.Department of MathematicsIndian Institute of TechnologyNew DelhiIndia

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-642-54652-5
  • Copyright Information Springer-Verlag Berlin Heidelberg 2014
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-642-54651-8
  • Online ISBN 978-3-642-54652-5
  • Series Print ISSN 1434-9922
  • Series Online ISSN 1860-0808
  • Buy this book on publisher's site