Multi Objective Linear Programming In Portfolio Selection
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Multi Objective Linear Programming In Portfolio Selection
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Author : Gayatri Biswal
language : en
Publisher:
Release Date : 2017
Multi Objective Linear Programming In Portfolio Selection written by Gayatri Biswal and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with categories.
Portfolio theory originally proposed by Markowitz is based on the assumption that the utility of an investor is a function of two factors, viz., mean and variance (or standard deviation) of return. However, the single index model of Sharpe is a statistical representation of return generating process that expresses return on stock in the form of a regression equation. Literature review on investment portfolio management shows that Sharpe's coefficient is the most commonly used performance measure in the determination of optimal portfolio. Sharpe's model is a linear programming model of the problem considering as the measure of risk. The present paper, building on the above model, proposes a multi-objective linear programming portfolio selection model that ensures a nondominated solution on the efficient frontier based on the outputs of the single index model. Taking Dow Jones Industrial Average (DJIA) as the market index and considering monthly indices along with the monthly prices of 28 securities for the period from March 1999 to March 2015, this model solves a practical portfolio selection problem in a multi-objective framework. The proposed model also shows its superiority over Sharpe's single index model.
Multi Objective Portfolio Selection Model With Diversification By Neutrosophic Optimization Technique
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Author : Sahidul Islam
language : en
Publisher: Infinite Study
Release Date :
Multi Objective Portfolio Selection Model With Diversification By Neutrosophic Optimization Technique written by Sahidul Islam and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with Mathematics categories.
In this paper, we first consider a multi-objective Portfolio Selection model and then we add another entropy objective function and next we generalized the model. We solve the problems using Neutrosophic optimization technique. The models are illustrated with numerical examples.
Portfolio Selection Using Multi Objective Optimisation
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Author : Saurabh Agarwal
language : en
Publisher: Springer
Release Date : 2017-08-21
Portfolio Selection Using Multi Objective Optimisation written by Saurabh Agarwal and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-08-21 with Business & Economics categories.
This book explores the risk-return paradox in portfolio selection by incorporating multi-objective criteria. Empirical research is presented on the development of alternate portfolio models and their relative performance in the risk/return framework to provide solutions to multi-objective optimization. Next to outlining techniques for undertaking individual investor’s profiling and portfolio programming, it also offers a new and practical approach for multi-objective portfolio optimization. This book will be of interest to Foreign Institutional Investors (FIIs), Mutual Funds, investors, and researchers and students in the field.
Multi Objective Programming And Goal Programming
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Author : Tetsuzo Tanino
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-11-11
Multi Objective Programming And Goal Programming written by Tetsuzo Tanino and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-11 with Mathematics categories.
This volume constitutes the proceedings of the Fifth International Conference on Multi-Objective Programming and Goal Programming: Theory & Appli cations (MOPGP'02) held in Nara, Japan on June 4-7, 2002. Eighty-two people from 16 countries attended the conference and 78 papers (including 9 plenary talks) were presented. MOPGP is an international conference within which researchers and prac titioners can meet and learn from each other about the recent development in multi-objective programming and goal programming. The participants are from different disciplines such as Optimization, Operations Research, Math ematical Programming and Multi-Criteria Decision Aid, whose common in terest is in multi-objective analysis. The first MOPGP Conference was held at Portsmouth, United Kingdom, in 1994. The subsequent conferenes were held at Torremolinos, Spain in 1996, at Quebec City, Canada in 1998, and at Katowice, Poland in 2000. The fifth conference was held at Nara, which was the capital of Japan for more than seventy years in the eighth century. During this Nara period the basis of Japanese society, or culture established itself. Nara is a beautiful place and has a number of historic monuments in the World Heritage List. The members of the International Committee of MOPGP'02 were Dylan Jones, Pekka Korhonen, Carlos Romero, Ralph Steuer and Mehrdad Tamiz.
New Developments In Multiple Objective And Goal Programming
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Author : Dylan Jones
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-03-17
New Developments In Multiple Objective And Goal Programming written by Dylan Jones and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-03-17 with Mathematics categories.
This volume shows the state-of-the-art in both theoretical development and application of multiple objective and goal programming. Applications from the fields of supply chain management, financial portfolio selection, financial risk management, insurance, medical imaging, sustainability, nurse scheduling, project management, water resource management, and the interface with data envelopment analysis give a good reflection of current usage. A pleasing variety of techniques are used including models with fuzzy, group-decision, stochastic, interactive, and binary aspects. Additionally, two papers from the upcoming area of multi-objective evolutionary algorithms are included. The book is based on the papers of the 8th International Conference on Multi-Objective and Goal Programming (MOPGP08) which was held in Portsmouth, UK, in September 2008.
A Hybrid Multi Objective Optimization Approach For Portfolio Selection Problem
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Author : Osman Pala
language : en
Publisher:
Release Date : 2017
A Hybrid Multi Objective Optimization Approach For Portfolio Selection Problem written by Osman Pala and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with categories.
Portfolio selection problem is a major subject in finance where investors deal with selecting satisfying portfolio which is composed of a vast number of risky assets, under some restricting criteria that are defined by themselves. Asset prices can be effected from different events, such as political crisis, financial turmoil and technological improvements. Due to uncertainty nature of these events, it is difficult to forecast future prices of assets. However, Markowitz's Modern Portfolio Theory, which is mainly focused on portfolio risk, introduced a new idea for asset diversification in portfolio optimization. According to this approach, an investor can reduce portfolio risk simply by holding combinations of assets that are not perfectly positively correlated and also efficient portfolio can only be obtained by focusing portfolio return and risk together. In this paper, a two stage multi objective portfolio selection model is proposed for obtaining best portfolio. In the first stage, Pareto efficient portfolios are obtained by genetic algorithm with using mean and variance of assets. Then in the second stage a multi criteria decision method is applied for ranking Pareto-optimum portfolios that are obtained in previous stage. Effectiveness of criteria, such as entropy measures and higher moments are taken into consideration and also performance ratios are examined in evaluating Pareto efficient portfolios and their rankings. An illustrated example is given and results of proposed model are discussed in experimental section.
Multiobjective Programming And Goal Programming
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Author : Vincent Barichard
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-01-30
Multiobjective Programming And Goal Programming written by Vincent Barichard and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-01-30 with Business & Economics categories.
This book gives the reader an insight into the state of the art in the field of multiobjective (linear, nonlinear and combinatorial) programming, goal programming and multiobjective metaheuristics. The 26 papers describe all relevant trends in this fields of research . They cover a wide range of topics ranging from theoretical investigations to algorithms, dealing with uncertainty, and applications to real world problems such as engineering design, water distribution systems and portfolio selection. The book is based on the papers of the seventh international conference on multiple objective programming and goal programming (MOPGP06).
Fuzzy Portfolio Optimization
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Author : Pankaj Gupta
language : en
Publisher: Springer
Release Date : 2014-03-17
Fuzzy Portfolio Optimization written by Pankaj Gupta and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-03-17 with Technology & Engineering categories.
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.
Linear And Mixed Integer Programming For Portfolio Optimization
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Author : Renata Mansini
language : en
Publisher: Springer
Release Date : 2015-06-10
Linear And Mixed Integer Programming For Portfolio Optimization written by Renata Mansini and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-10 with Business & Economics categories.
This book presents solutions to the general problem of single period portfolio optimization. It introduces different linear models, arising from different performance measures, and the mixed integer linear models resulting from the introduction of real features. Other linear models, such as models for portfolio rebalancing and index tracking, are also covered. The book discusses computational issues and provides a theoretical framework, including the concepts of risk-averse preferences, stochastic dominance and coherent risk measures. The material is presented in a style that requires no background in finance or in portfolio optimization; some experience in linear and mixed integer models, however, is required. The book is thoroughly didactic, supplementing the concepts with comments and illustrative examples.
Operations Research Optimization With Matlab Multiobjective Quadratic And Mixed Programming
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Author : Perez C.
language : en
Publisher:
Release Date : 2017-08-16
Operations Research Optimization With Matlab Multiobjective Quadratic And Mixed Programming written by Perez C. and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-08-16 with categories.
The generalization of optimization theory and techniques to other formulations comprises a large area of applied mathematics. Optimization includes finding "best available" values of some objective function given a defined domain (or input), including a variety of different types of objective functions and different types of domains.Adding more than one objective to an optimization problem adds complexity. For example, to optimize a structural design, one would desire a design that is both light and rigid. When two objectives conflict, a trade-off must be created. There may be one lightest design, one stiffest design, and an infinite number of designs that are some compromise of weight and rigidity. The set of trade-off designs that cannot be improved upon according to one criterion without hurting another criterion is known as the Pareto set. The curve created plotting weight against stiffness of the best designs is known as the Pareto frontier.A design is judged to be "Pareto optimal" (equivalently, "Pareto efficient" or in the Pareto set) if it is not dominated by any other design: If it is worse than another design in some respects and no better in any respect, then it is dominated and is not Pareto optimal. The choice among "Pareto optimal" solutions to determine the "favorite solution" is delegated to the decision maker. In other words, defining the problem as multi-objective optimization signals that some information is missing: desirable objectives are given but combinations of them are not rated relative to each other. In some cases, the missing information can be derived by interactive sessions with the decision maker.Multi-objective optimization problems have been generalized further into vector optimization problems where the (partial) ordering is no longer given by the Pareto ordering.Optimization problems are often multi-modal; that is, they possess multiple good solutions. They could all be globally good or there could be a mix of globally good and locally good solutions. Obtaining all (or at least some of) the multiple solutions is the goal of a multi-modal optimizer.Classical optimization techniques due to their iterative approach do not perform satisfactorily when they are used to obtain multiple solutions, since it is not guaranteed that different solutions will be obtained even with different starting points in multiple runs of the algorithm. Evolutionary algorithms, however, are a very popular approach to obtain multiple solutions in a multi-modal optimization task.This book develops the following topics:* "Multiobjective Optimization Algorithms" * "Using fminimax with a Simulink Model" * "Signal Processing Using fgoalattain" * "Generate and Plot a Pareto Front" * "Linear Programming Algorithms" * "Maximize Long-Term Investments Using Linear Programming" * "Mixed-Integer Linear Programming Algorithms" * "Tuning Integer Linear Programming" * "Mixed-Integer Linear Programming Basics" * "Optimal Dispatch of Power Generators" * "Mixed-Integer Quadratic Programming Portfolio Optimization" * "Quadratic Programming Algorithms"* "Quadratic Minimization with Bound Constraints" * "Quadratic Minimization with Dense, Structured Hessian"* "Large Sparse Quadratic Program with Interior Point Algorithm" * "Least-Squares (Model Fitting) Algorithms" * "lsqnonlin with a Simulink Model" * "Nonlinear Least Squares With and Without Jacobian" * "Linear Least Squares with Bound Constraints" * "Optimization App with the lsqlin Solver" * "Maximize Long-Term Investments Using Linear Programming" * "Jacobian Multiply Function with Linear Least Squares" * "Nonlinear Curve Fitting with lsqcurvefit" * "Fit a Model to Complex-Valued Data" * "Systems of Equations" * "Nonlinear Equations with Analytic Jacobian" * "Nonlinear Equations with Jacobian" * "Nonlinear Equations with Jacobian Sparsity Pattern"* "Nonlinear Systems with Constraints" * "Parallel Computing for Optimization"