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Metaheuristics For Portfolio Optimization


Metaheuristics For Portfolio Optimization
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Metaheuristics For Portfolio Optimization


Metaheuristics For Portfolio Optimization
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Author : G. A. Vijayalakshmi Pai
language : en
Publisher: John Wiley & Sons
Release Date : 2017-12-27

Metaheuristics For Portfolio Optimization written by G. A. Vijayalakshmi Pai and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-27 with Computers categories.


The book is a monograph in the cross disciplinary area of Computational Intelligence in Finance and elucidates a collection of practical and strategic Portfolio Optimization models in Finance, that employ Metaheuristics for their effective solutions and demonstrates the results using MATLAB implementations, over live portfolios invested across global stock universes. The book has been structured in such a way that, even novices in finance or metaheuristics should be able to comprehend and work on the hybrid models discussed in the book.



Metaheuristic Approaches To Portfolio Optimization


Metaheuristic Approaches To Portfolio Optimization
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Author : Ray, Jhuma
language : en
Publisher: IGI Global
Release Date : 2019-06-22

Metaheuristic Approaches To Portfolio Optimization written by Ray, Jhuma and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-22 with Business & Economics categories.


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.



Metaheuristic Optimization Nature Inspired Algorithms Swarm And Computational Intelligence Theory And Applications


Metaheuristic Optimization Nature Inspired Algorithms Swarm And Computational Intelligence Theory And Applications
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Author : Modestus O. Okwu
language : en
Publisher: Springer Nature
Release Date : 2020-11-13

Metaheuristic Optimization Nature Inspired Algorithms Swarm And Computational Intelligence Theory And Applications written by Modestus O. Okwu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-13 with Technology & Engineering categories.


This book exemplifies how algorithms are developed by mimicking nature. Classical techniques for solving day-to-day problems is time-consuming and cannot address complex problems. Metaheuristic algorithms are nature-inspired optimization techniques for solving real-life complex problems. This book emphasizes the social behaviour of insects, animals and other natural entities, in terms of converging power and benefits. Major nature-inspired algorithms discussed in this book include the bee colony algorithm, ant colony algorithm, grey wolf optimization algorithm, whale optimization algorithm, firefly algorithm, bat algorithm, ant lion optimization algorithm, grasshopper optimization algorithm, butterfly optimization algorithm and others. The algorithms have been arranged in chapters to help readers gain better insight into nature-inspired systems and swarm intelligence. All the MATLAB codes have been provided in the appendices of the book to enable readers practice how to solve examples included in all sections. This book is for experts in Engineering and Applied Sciences, Natural and Formal Sciences, Economics, Humanities and Social Sciences.



Algorithm Portfolios


Algorithm Portfolios
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Author : Dimitris Souravlias
language : en
Publisher: Springer Nature
Release Date : 2021-03-24

Algorithm Portfolios written by Dimitris Souravlias and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-24 with Business & Economics categories.


This book covers algorithm portfolios, multi-method schemes that harness optimization algorithms into a joint framework to solve optimization problems. It is expected to be a primary reference point for researchers and doctoral students in relevant domains that seek a quick exposure to the field. The presentation focuses primarily on the applicability of the methods and the non-expert reader will find this book useful for starting designing and implementing algorithm portfolios. The book familiarizes the reader with algorithm portfolios through current advances, applications, and open problems. Fundamental issues in building effective and efficient algorithm portfolios such as selection of constituent algorithms, allocation of computational resources, interaction between algorithms and parallelism vs. sequential implementations are discussed. Several new applications are analyzed and insights on the underlying algorithmic designs are provided. Future directions, new challenges, and open problems in the design of algorithm portfolios and applications are explored to further motivate research in this field.



Advances In Swarm Intelligence


Advances In Swarm Intelligence
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Author : Ying Tan
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-06

Advances In Swarm Intelligence written by Ying Tan 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 2010-06 with Computers categories.


The LNCS series reports state-of-the-art results in computer science research, development, and education, at a high level and in both printed and electronic form. Enjoying tight cooperation with the R&D community, with numerous individuals, as well as with prestigious organizations and societies, LNCS has grown into the most comprehensive computer science research forum available. The scope of LNCS, including its subseries LNAI and LNBI, spans the whole range of computer science and information technology including interdisciplinary topics in a variety of application fields. The type of material published traditionally includes More recently, several color-cover sublines have been added featuring, beyond a collection of papers, various added-value components; these sublines include In paallel to the printed book, each new volume is published electronically in LNCS Online.



Search And Optimization By Metaheuristics


Search And Optimization By Metaheuristics
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Author : Ke-Lin Du
language : en
Publisher: Birkhäuser
Release Date : 2016-07-20

Search And Optimization By Metaheuristics written by Ke-Lin Du and has been published by Birkhäuser this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-20 with Computers categories.


This textbook provides a comprehensive introduction to nature-inspired metaheuristic methods for search and optimization, including the latest trends in evolutionary algorithms and other forms of natural computing. Over 100 different types of these methods are discussed in detail. The authors emphasize non-standard optimization problems and utilize a natural approach to the topic, moving from basic notions to more complex ones. An introductory chapter covers the necessary biological and mathematical backgrounds for understanding the main material. Subsequent chapters then explore almost all of the major metaheuristics for search and optimization created based on natural phenomena, including simulated annealing, recurrent neural networks, genetic algorithms and genetic programming, differential evolution, memetic algorithms, particle swarm optimization, artificial immune systems, ant colony optimization, tabu search and scatter search, bee and bacteria foraging algorithms, harmony search, biomolecular computing, quantum computing, and many others. General topics on dynamic, multimodal, constrained, and multiobjective optimizations are also described. Each chapter includes detailed flowcharts that illustrate specific algorithms and exercises that reinforce important topics. Introduced in the appendix are some benchmarks for the evaluation of metaheuristics. Search and Optimization by Metaheuristics is intended primarily as a textbook for graduate and advanced undergraduate students specializing in engineering and computer science. It will also serve as a valuable resource for scientists and researchers working in these areas, as well as those who are interested in search and optimization methods.



An Introduction To Metaheuristics For Optimization


An Introduction To Metaheuristics For Optimization
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Author : Bastien Chopard
language : en
Publisher: Springer
Release Date : 2018-11-02

An Introduction To Metaheuristics For Optimization written by Bastien Chopard and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-02 with Computers categories.


The authors stress the relative simplicity, efficiency, flexibility of use, and suitability of various approaches used to solve difficult optimization problems. The authors are experienced, interdisciplinary lecturers and researchers and in their explanations they demonstrate many shared foundational concepts among the key methodologies. This textbook is a suitable introduction for undergraduate and graduate students, researchers, and professionals in computer science, engineering, and logistics.



Metaheuristics For Dynamic Optimization


Metaheuristics For Dynamic Optimization
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Author : Enrique Alba
language : en
Publisher: Springer
Release Date : 2012-08-11

Metaheuristics For Dynamic Optimization written by Enrique Alba and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-08-11 with Technology & Engineering categories.


This book is an updated effort in summarizing the trending topics and new hot research lines in solving dynamic problems using metaheuristics. An analysis of the present state in solving complex problems quickly draws a clear picture: problems that change in time, having noise and uncertainties in their definition are becoming very important. The tools to face these problems are still to be built, since existing techniques are either slow or inefficient in tracking the many global optima that those problems are presenting to the solver technique. Thus, this book is devoted to include several of the most important advances in solving dynamic problems. Metaheuristics are the more popular tools to this end, and then we can find in the book how to best use genetic algorithms, particle swarm, ant colonies, immune systems, variable neighborhood search, and many other bioinspired techniques. Also, neural network solutions are considered in this book. Both, theory and practice have been addressed in the chapters of the book. Mathematical background and methodological tools in solving this new class of problems and applications are included. From the applications point of view, not just academic benchmarks are dealt with, but also real world applications in logistics and bioinformatics are discussed here. The book then covers theory and practice, as well as discrete versus continuous dynamic optimization, in the aim of creating a fresh and comprehensive volume. This book is targeted to either beginners and experienced practitioners in dynamic optimization, since we took care of devising the chapters in a way that a wide audience could profit from its contents. We hope to offer a single source for up-to-date information in dynamic optimization, an inspiring and attractive new research domain that appeared in these last years and is here to stay.



Metaheuristics And Optimization In Computer And Electrical Engineering


Metaheuristics And Optimization In Computer And Electrical Engineering
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Author : Navid Razmjooy
language : en
Publisher: Springer Nature
Release Date : 2020-11-16

Metaheuristics And Optimization In Computer And Electrical Engineering written by Navid Razmjooy and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-16 with Technology & Engineering categories.


The use of artificial intelligence, especially in the field of optimization is increasing day by day. The purpose of this book is to explore the possibility of using different kinds of optimization algorithms to advance and enhance the tools used for computer and electrical engineering purposes.



Linear And Mixed Integer Programming For 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.