A Heuristic Approach To Portfolio Optimization
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Author |
: Dietmar G. Maringer |
Publisher |
: Springer Science & Business Media |
Total Pages |
: 238 |
Release |
: 2006-07-02 |
ISBN-10 |
: 9780387258539 |
ISBN-13 |
: 0387258531 |
Rating |
: 4/5 (39 Downloads) |
Synopsis Portfolio Management with Heuristic Optimization by : Dietmar G. Maringer
Portfolio Management with Heuristic Optimization consist of two parts. The first part (Foundations) deals with the foundations of portfolio optimization, its assumptions, approaches and the limitations when "traditional" optimization techniques are to be applied. In addition, the basic concepts of several heuristic optimization techniques are presented along with examples of how to implement them for financial optimization problems. The second part (Applications and Contributions) consists of five chapters, covering different problems in financial optimization: the effects of (linear, proportional and combined) transaction costs together with integer constraints and limitations on the initital endowment to be invested; the diversification in small portfolios; the effect of cardinality constraints on the Markowitz efficient line; the effects (and hidden risks) of Value-at-Risk when used the relevant risk constraint; the problem factor selection for the Arbitrage Pricing Theory.
Author |
: Ray, Jhuma |
Publisher |
: IGI Global |
Total Pages |
: 281 |
Release |
: 2019-06-22 |
ISBN-10 |
: 9781522581048 |
ISBN-13 |
: 1522581049 |
Rating |
: 4/5 (48 Downloads) |
Synopsis Metaheuristic Approaches to Portfolio Optimization by : Ray, Jhuma
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.
Author |
: Ying Tan |
Publisher |
: Springer Science & Business Media |
Total Pages |
: 771 |
Release |
: 2010-06 |
ISBN-10 |
: 9783642134944 |
ISBN-13 |
: 3642134947 |
Rating |
: 4/5 (44 Downloads) |
Synopsis Advances in Swarm Intelligence by : Ying Tan
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.
Author |
: Erricos John Kontoghiorghes |
Publisher |
: Springer Science & Business Media |
Total Pages |
: 626 |
Release |
: 2013-11-11 |
ISBN-10 |
: 9781475736137 |
ISBN-13 |
: 1475736134 |
Rating |
: 4/5 (37 Downloads) |
Synopsis Computational Methods in Decision-Making, Economics and Finance by : Erricos John Kontoghiorghes
Computing has become essential for the modeling, analysis, and optimization of systems. This book is devoted to algorithms, computational analysis, and decision models. The chapters are organized in two parts: optimization models of decisions and models of pricing and equilibria.
Author |
: Renata Mansini |
Publisher |
: Springer |
Total Pages |
: 131 |
Release |
: 2015-06-10 |
ISBN-10 |
: 9783319184821 |
ISBN-13 |
: 3319184822 |
Rating |
: 4/5 (21 Downloads) |
Synopsis Linear and Mixed Integer Programming for Portfolio Optimization by : Renata Mansini
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.
Author |
: Manfred Gilli |
Publisher |
: |
Total Pages |
: 18 |
Release |
: 2000 |
ISBN-10 |
: OCLC:248515717 |
ISBN-13 |
: |
Rating |
: 4/5 (17 Downloads) |
Synopsis A Heuristic Approach to Portfolio Optimization by : Manfred Gilli
Author |
: G. A. Vijayalakshmi Pai |
Publisher |
: John Wiley & Sons |
Total Pages |
: 322 |
Release |
: 2017-12-27 |
ISBN-10 |
: 9781119482789 |
ISBN-13 |
: 111948278X |
Rating |
: 4/5 (89 Downloads) |
Synopsis Metaheuristics for Portfolio Optimization by : G. A. Vijayalakshmi Pai
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.
Author |
: Richard O. Michaud |
Publisher |
: Oxford University Press |
Total Pages |
: 207 |
Release |
: 2008-03-03 |
ISBN-10 |
: 9780199887194 |
ISBN-13 |
: 0199887195 |
Rating |
: 4/5 (94 Downloads) |
Synopsis Efficient Asset Management by : Richard O. Michaud
In spite of theoretical benefits, Markowitz mean-variance (MV) optimized portfolios often fail to meet practical investment goals of marketability, usability, and performance, prompting many investors to seek simpler alternatives. Financial experts Richard and Robert Michaud demonstrate that the limitations of MV optimization are not the result of conceptual flaws in Markowitz theory but unrealistic representation of investment information. What is missing is a realistic treatment of estimation error in the optimization and rebalancing process. The text provides a non-technical review of classical Markowitz optimization and traditional objections. The authors demonstrate that in practice the single most important limitation of MV optimization is oversensitivity to estimation error. Portfolio optimization requires a modern statistical perspective. Efficient Asset Management, Second Edition uses Monte Carlo resampling to address information uncertainty and define Resampled Efficiency (RE) technology. RE optimized portfolios represent a new definition of portfolio optimality that is more investment intuitive, robust, and provably investment effective. RE rebalancing provides the first rigorous portfolio trading, monitoring, and asset importance rules, avoiding widespread ad hoc methods in current practice. The Second Edition resolves several open issues and misunderstandings that have emerged since the original edition. The new edition includes new proofs of effectiveness, substantial revisions of statistical estimation, extensive discussion of long-short optimization, and new tools for dealing with estimation error in applications and enhancing computational efficiency. RE optimization is shown to be a Bayesian-based generalization and enhancement of Markowitz's solution. RE technology corrects many current practices that may adversely impact the investment value of trillions of dollars under current asset management. RE optimization technology may also be useful in other financial optimizations and more generally in multivariate estimation contexts of information uncertainty with Bayesian linear constraints. Michaud and Michaud's new book includes numerous additional proposals to enhance investment value including Stein and Bayesian methods for improved input estimation, the use of portfolio priors, and an economic perspective for asset-liability optimization. Applications include investment policy, asset allocation, and equity portfolio optimization. A simple global asset allocation problem illustrates portfolio optimization techniques. A final chapter includes practical advice for avoiding simple portfolio design errors. With its important implications for investment practice, Efficient Asset Management 's highly intuitive yet rigorous approach to defining optimal portfolios will appeal to investment management executives, consultants, brokers, and anyone seeking to stay abreast of current investment technology. Through practical examples and illustrations, Michaud and Michaud update the practice of optimization for modern investment management.
Author |
: Information Resources Management Association |
Publisher |
: |
Total Pages |
: |
Release |
: 2020-12-05 |
ISBN-10 |
: 1799880486 |
ISBN-13 |
: 9781799880486 |
Rating |
: 4/5 (86 Downloads) |
Synopsis Research Anthology on Multi-industry Uses of Genetic Programming and Algorithms by : Information Resources Management Association
"This book of research chapters explores the technology, uses, and implementation of genetic programming and algorithms across multiple industries creating a fundamental understanding of this technology, and how genetic programming and algorithms are implemented in fields such as healthcare, engineering, social sciences, computer science and more"--
Author |
: Burcu Adıgüzel Mercangöz |
Publisher |
: Springer Nature |
Total Pages |
: 355 |
Release |
: 2021-05-13 |
ISBN-10 |
: 9783030702816 |
ISBN-13 |
: 3030702812 |
Rating |
: 4/5 (16 Downloads) |
Synopsis Applying Particle Swarm Optimization by : Burcu Adıgüzel Mercangöz
This book explains the theoretical structure of particle swarm optimization (PSO) and focuses on the application of PSO to portfolio optimization problems. The general goal of portfolio optimization is to find a solution that provides the highest expected return at each level of portfolio risk. According to H. Markowitz’s portfolio selection theory, as new assets are added to an investment portfolio, the total risk of the portfolio’s decreases depending on the correlations of asset returns, while the expected return on the portfolio represents the weighted average of the expected returns for each asset. The book explains PSO in detail and demonstrates how to implement Markowitz’s portfolio optimization approach using PSO. In addition, it expands on the Markowitz model and seeks to improve the solution-finding process with the aid of various algorithms. In short, the book provides researchers, teachers, engineers, managers and practitioners with many tools they need to apply the PSO technique to portfolio optimization.