Download or read book Portfolio Risk Optimization by Fuzzy Approaches written by Thanh Thi Nguyen and published by . This book was released on 2013 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to the complexity and uncertainty in real world portfolio management, investors might be reluctant and sometimes unable to provide precise judgements regarding stock performance. In this context, analysts have long advocated use of fuzzy mathematics so that uncertainties and lack of precision can be acknowledged. This research therefore explores the applications of fuzzy sets in particular, or fuzzy logic in general for representing vague and imprecise financial data for portfolio risk optimization. Asset returns are uncertain and changeable over time so we model asset returns as fuzzy random variables and propose portfolio optimization models. Using fuzzy random variables, we introduce a new concept of financial risk, and the fuzzy Sharpe ratio contributing an important advancement in portfolio selection in the fuzzy environment. Two solution methods using a fuzzy approach and a genetic algorithm are applied to the proposed models. The proposed approach exhibits advantages over the so-called standard mean-variance optimization (MVO), throughout experimental results. The non-Gaussian distribution of asset returns has long been recognized, and the conventional MVO has been criticized as inadequate. Hence utilizing higher moments than variance, i.e. skewness, kurtosis soon emerged in portfolio selection. This research investigates the importance of higher moments in portfolio optimization through deploying fuzzy approaches. Marginal impacts of stocks on portfolio return and higher moment risks, are modelled by fuzzy numbers. The fuzzy models are constructed to optimize not only portfolio return and normal variance risk but also the portfolio higher moment risks. From the stock marginal impact modelling, two fuzzy approaches are used to derive optimal portfolio allocations. The first approach applies the constrained fuzzy analytic hierarchy process, whereas the second approach uses the fuzzy linear programming method. The efficiency of both approaches shows advantages of the proposed fuzzy models in portfolio selection. Going beyond the normal variance and higher moment risks, investors also should take into account downside risk measures. The downside risks are inspired by the principle of safety first in portfolio selection. The principle states that an investor would prefer the investment with the smallest probability of going below the target return. A fuzzy integrated framework is proposed accounting for portfolio return and six risk criteria including normal risk (volatility), asymmetric risk (skewness), "fat-tail" risk (kurtosis) and downside risks, i.e. semi-variance, modified Value-at-Risk, and modified Expected Shortfall. Fuzzy goals of portfolio's return and risks are constructed by bootstrapping, and kernel smoothing density estimate. A preselection process dealing with large datasets is also adopted to eliminate low diversification potential stocks before running the optimization model. Various investors' risk preference schemes are implemented with both national and international experimental datasets. Results reported demonstrate the advantages of the proposed fuzzy framework compared to a conventional higher moment portfolio optimization model. The conclusion is that fuzzy modelling is efficient and competent in various portfolio selection formulations when uncertainty and vagueness are deemed present. When appropriately utilized, fuzzy approaches can bring superior investment outcomes compared to conventional non-fuzzy models prevalent in the literature.

Download or read book Fuzzy Portfolio Optimization written by Pankaj Gupta and published by Springer. This book was released on 2014-03-17 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Fuzzy Portfolio Optimization written by Yong Fang and published by Springer Science & Business Media. This book was released on 2008-09-20 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most of the existing portfolio selection models are based on the probability theory. Though they often deal with the uncertainty via probabilistic - proaches, we have to mention that the probabilistic approaches only partly capture the reality. Some other techniques have also been applied to handle the uncertainty of the ?nancial markets, for instance, the fuzzy set theory [Zadeh (1965)]. In reality, many events with fuzziness are characterized by probabilistic approaches, although they are not random events. The fuzzy set theory has been widely used to solve many practical problems, including ?nancial risk management. By using fuzzy mathematical approaches, quan- tative analysis, qualitative analysis, the experts’ knowledge and the investors’ subjective opinions can be better integrated into a portfolio selection model. The contents of this book mainly comprise of the authors’ research results for fuzzy portfolio selection problems in recent years. In addition, in the book, the authors will also introduce some other important progress in the ?eld of fuzzy portfolio optimization. Some fundamental issues and problems of po- folioselectionhavebeenstudiedsystematicallyandextensivelybytheauthors to apply fuzzy systems theory and optimization methods. A new framework for investment analysis is presented in this book. A series of portfolio sel- tion models are given and some of them might be more e?cient for practical applications. Some application examples are given to illustrate these models by using real data from the Chinese securities markets.

Download or read book Fuzzy Portfolio Optimization for Power Generation Assets written by Barbara Glensk and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fuzzy sets theory is proposed as an alternative to the probabilistic approach for assessing portfolios of power plants, in order to capture the complex reality of decision-making processes. This paper presents different fuzzy portfolio selection models, where the rate of returns as well as the investor's aspiration levels of portfolio return and risk are regarded as fuzzy variables. Furthermore, portfolio risk is defined as a downside risk, which is why a semi-mean-absolute deviation portfolio selection model is introduced. Finally, as an illustration, the models presented are applied to a selection of power generation mixes. The efficient portfolio results show that the fuzzy portfolio selection models with different definitions of membership functions as well as the semi-mean-absolute deviation model perform better than the standard mean-variance approach. Moreover, introducing membership functions for the description of investors' aspiration levels for the expected return and risk shows how the knowledge of experts, and investors' subjective opinions, can be better integrated in the decision-making process than with probabilistic approaches.

Download or read book Optimization of Financial Asset Neutrosophic Portfolios written by Marcel-Ioan Boloș and published by Infinite Study. This book was released on with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this paper was to model, with the help of neutrosophic fuzzy numbers, the optimal financial asset portfolios, offering additional information to those investing in the capital market. The optimal neutrosophic portfolios are those categories of portfolios consisting of two or more financial assets, modeled using neutrosophic triangular numbers, that allow for the determination of financial performance indicators, respectively the neutrosophic average, the neutrosophic risk, for each financial asset, and the neutrosophic covariance as well as the determination of the portfolio return, respectively of the portfolio risk.

Download or read book Uncertain Portfolio Optimization written by Zhongfeng Qin and published by Springer. This book was released on 2016-09-16 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a new modeling approach for portfolio optimization problems involving a lack of sufficient historical data. The content mainly reflects the author’s extensive work on uncertainty portfolio optimization in recent years. Considering security returns as different variables, the book presents a series of portfolio optimization models in the framework of credibility theory, uncertainty theory and chance theory, respectively. As such, it offers readers a comprehensive and up-to-date guide to uncertain portfolio optimization models.

Download or read book Progress in Intelligent Decision Science written by Tofigh Allahviranloo and published by Springer Nature. This book was released on 2021-01-29 with total page 992 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains the topics of artificial intelligence and deep learning that do have much application in real-life problems. The concept of uncertainty has long been used in applied science, especially decision making and a logical decision must be made in the field of uncertainty or in the real-life environment that is formed and combined with vague concepts and data. The chapters of this book are connected to the new concepts and aspects of decision making with uncertainty. Besides, other chapters are involved with the concept of data mining and decision making under uncertain computations.

Download or read book Fuzzy Approach Model to Portfolio Risk Response Strategies written by Yaser Rahimi and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Risk management and control of project risks have been the intrinsic characteristics of high-rise building projects in a changing built environment. In this research, a novel bi-objective model for the best mixture of projects is proposed. The first objective focuses on maximizing profits and efficiency of risk responses, and the second objective aims at minimizing project direct cost including machinery, human, and material costs to implement proper risk responses over a planning horizon under uncertainty. In this model, risks of the projects are controlled by time, quality, and cost constraints, and the most optimum risk response strategies (RRSs) are selected to eliminate or reduce the impacts of the risks. Thus, the combination of optimum projects with the best RRSs can be selected for an organizational portfolio model. Finally, to assess the solution method and the proposed model, the empirical result and sensitivity analysis are carried out. Ten large-scale high-rise building projects and their associated risks are evaluated as cases in this study.

Download or read book Robust Value at risk Optimization Approach for Portfolio Management written by Maksim Oks and published by . This book was released on 2002 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Portfolio Management with Heuristic Optimization written by Dietmar G. Maringer and published by Springer Science & Business Media. This book was released on 2006-07-02 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Fuzzy Optimization written by Weldon A. Lodwick and published by Springer. This book was released on 2010-07-23 with total page 535 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimization is an extremely important area in science and technology which provides powerful and useful tools and techniques for the formulation and solution of a multitude of problems in which we wish, or need, to to find a best possible option or solution. The volume is divided into a coupe of parts which present various aspects of fuzzy optimization, some related more general issues, and applications.

Download or read book Intelligent and Fuzzy Systems written by Cengiz Kahraman and published by Springer Nature. This book was released on with total page 812 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Financial Risk Modelling and Portfolio Optimization with R written by Bernhard Pfaff and published by John Wiley & Sons. This book was released on 2012-11-05 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces the latest techniques advocated for measuring financial market risk and portfolio optimization, and provides a plethora of R code examples that enable the reader to replicate the results featured throughout the book. Financial Risk Modelling and Portfolio Optimization with R: Demonstrates techniques in modelling financial risks and applying portfolio optimization techniques as well as recent advances in the field. Introduces stylized facts, loss function and risk measures, conditional and unconditional modelling of risk; extreme value theory, generalized hyperbolic distribution, volatility modelling and concepts for capturing dependencies. Explores portfolio risk concepts and optimization with risk constraints. Enables the reader to replicate the results in the book using R code. Is accompanied by a supporting website featuring examples and case studies in R. Graduate and postgraduate students in finance, economics, risk management as well as practitioners in finance and portfolio optimization will find this book beneficial. It also serves well as an accompanying text in computer-lab classes and is therefore suitable for self-study.

Download or read book Portfolio Optimization Using Neuro Fuzzy System in Indian Stock Market written by M. Gunasekaran and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper describes a portfolio optimization system by using Neuro-Fuzzy framework in order to manage stock portfolio. It is great importance to stock investors and applied researchers. The proposed portfolio optimization approach Neuro-Fuzzy System reasoning in order to make a more yields from the stock portfolio, and hence maximize return and minimize risk of a stock portfolio through diversification and right investment allocation to the particular stock under uncertainty. To evaluate the performance of forecasting and optimization system, BSE Sensex index of India considered as benchmarks in this study to measure efficient forecasting models. The results show that the proposed Neuro-Fuzzy system produces much higher accuracy when compared to other portfolio models.

Download or read book Portfolio Decision Analysis written by Ahti Salo and published by Springer Science & Business Media. This book was released on 2011-08-12 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt: Portfolio Decision Analysis: Improved Methods for Resource Allocation provides an extensive, up-to-date coverage of decision analytic methods which help firms and public organizations allocate resources to 'lumpy' investment opportunities while explicitly recognizing relevant financial and non-financial evaluation criteria and the presence of alternative investment opportunities. In particular, it discusses the evolution of these methods, presents new methodological advances and illustrates their use across several application domains. The book offers a many-faceted treatment of portfolio decision analysis (PDA). Among other things, it (i) synthesizes the state-of-play in PDA, (ii) describes novel methodologies, (iii) fosters the deployment of these methodologies, and (iv) contributes to the strengthening of research on PDA. Portfolio problems are widely regarded as the single most important application context of decision analysis, and, with its extensive and unique coverage of these problems, this book is a much-needed addition to the literature. The book also presents innovative treatments of new methodological approaches and their uses in applications. The intended audience consists of practitioners and researchers who wish to gain a good understanding of portfolio decision analysis and insights into how PDA methods can be leveraged in different application contexts. The book can also be employed in courses at the post-graduate level.

Download or read book Advanced Stochastic Models Risk Assessment and Portfolio Optimization written by Svetlozar T. Rachev and published by Wiley. This book was released on 2008-02-25 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This groundbreaking book extends traditional approaches of risk measurement and portfolio optimization by combining distributional models with risk or performance measures into one framework. Throughout these pages, the expert authors explain the fundamentals of probability metrics, outline new approaches to portfolio optimization, and discuss a variety of essential risk measures. Using numerous examples, they illustrate a range of applications to optimal portfolio choice and risk theory, as well as applications to the area of computational finance that may be useful to financial engineers.

Download or read book Novel Six Sigma DMAIC Approaches to Project Risk Assessment and Management written by Bubevski, Vojo and published by IGI Global. This book was released on 2024-05-01 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: In today's fast-paced business environment, project managers face the daunting challenge of managing risk effectively amid uncertainty. Traditional project management methodologies often lag, leading to missed deadlines, cost overruns, and subpar outcomes. A comprehensive risk management framework is necessary for organizations to be protected from fate's whims, hindering their ability to achieve strategic objectives. The DMAIC Stochastic Method is a groundbreaking approach that combines Six Sigma principles with stochastic modeling to revolutionize project risk management. Novel Six Sigma DMAIC Approaches to Project Risk Assessment and Management is a guidebook for implementing the DMAIC Stochastic Method in project management. This innovative methodology provides a systematic way of identifying, assessing, and mitigating risks, ensuring that projects stay on track and deliver the desired results. By integrating deterministic and stochastic models, the DMAIC Stochastic Method offers a more holistic view of risk, enabling managers to make informed decisions and proactively address potential issues.