Advanced Stochastic Models, Risk Assessment, and Portfolio Optimization

Advanced Stochastic Models, Risk Assessment, and Portfolio Optimization
Title Advanced Stochastic Models, Risk Assessment, and Portfolio Optimization PDF eBook
Author Svetlozar T. Rachev
Publisher Wiley
Pages 0
Release 2008-02-25
Genre Business & Economics
ISBN 9780470053164

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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.

Portfolio Optimization and Performance Analysis

Portfolio Optimization and Performance Analysis
Title Portfolio Optimization and Performance Analysis PDF eBook
Author Jean-Luc Prigent
Publisher CRC Press
Pages 451
Release 2007-05-07
Genre Business & Economics
ISBN 142001093X

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In answer to the intense development of new financial products and the increasing complexity of portfolio management theory, Portfolio Optimization and Performance Analysis offers a solid grounding in modern portfolio theory. The book presents both standard and novel results on the axiomatics of the individual choice in an uncertain framework, cont

The Kelly Capital Growth Investment Criterion

The Kelly Capital Growth Investment Criterion
Title The Kelly Capital Growth Investment Criterion PDF eBook
Author Leonard C. MacLean
Publisher World Scientific
Pages 883
Release 2011
Genre Business & Economics
ISBN 9814293490

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This volume provides the definitive treatment of fortune's formula or the Kelly capital growth criterion as it is often called. The strategy is to maximize long run wealth of the investor by maximizing the period by period expected utility of wealth with a logarithmic utility function. Mathematical theorems show that only the log utility function maximizes asymptotic long run wealth and minimizes the expected time to arbitrary large goals. In general, the strategy is risky in the short term but as the number of bets increase, the Kelly bettor's wealth tends to be much larger than those with essentially different strategies. So most of the time, the Kelly bettor will have much more wealth than these other bettors but the Kelly strategy can lead to considerable losses a small percent of the time. There are ways to reduce this risk at the cost of lower expected final wealth using fractional Kelly strategies that blend the Kelly suggested wager with cash. The various classic reprinted papers and the new ones written specifically for this volume cover various aspects of the theory and practice of dynamic investing. Good and bad properties are discussed, as are fixed-mix and volatility induced growth strategies. The relationships with utility theory and the use of these ideas by great investors are featured.

Linear and Mixed Integer Programming for Portfolio Optimization

Linear and Mixed Integer Programming for Portfolio Optimization
Title Linear and Mixed Integer Programming for Portfolio Optimization PDF eBook
Author Renata Mansini
Publisher Springer
Pages 131
Release 2015-06-10
Genre Business & Economics
ISBN 3319184822

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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.

Efficient Asset Management

Efficient Asset Management
Title Efficient Asset Management PDF eBook
Author Richard O. Michaud
Publisher Oxford University Press
Pages 207
Release 2008-03-03
Genre Business & Economics
ISBN 0199887195

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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.

Performance Evaluation and Attribution of Security Portfolios

Performance Evaluation and Attribution of Security Portfolios
Title Performance Evaluation and Attribution of Security Portfolios PDF eBook
Author Bernd R. Fischer
Publisher Academic Press
Pages 725
Release 2012-12-31
Genre Business & Economics
ISBN 0080926525

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Just how successful is that investment? Measuring portfolio performance requires evaluation (measuring portfolio results against benchmarks) and attribution (determining individual results of the portfolio's parts), In this book, a professor and an asset manager show readers how to use theories, applications, and real data to understand these tools. Unlike others, Fischer and Wermers teach readers how to pick the theories and applications that fit their specific needs. With material inspired by the recent financial crisis, Fischer and Wermers bring new clarity to defining investment success. - Gives readers the theories and the empirical tools to handle their own data - Features practice problems formerly from the CFA Program curriculum.

Robust Portfolio Optimization and Management

Robust Portfolio Optimization and Management
Title Robust Portfolio Optimization and Management PDF eBook
Author Frank J. Fabozzi
Publisher John Wiley & Sons
Pages 513
Release 2007-04-27
Genre Business & Economics
ISBN 0470164891

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Praise for Robust Portfolio Optimization and Management "In the half century since Harry Markowitz introduced his elegant theory for selecting portfolios, investors and scholars have extended and refined its application to a wide range of real-world problems, culminating in the contents of this masterful book. Fabozzi, Kolm, Pachamanova, and Focardi deserve high praise for producing a technically rigorous yet remarkably accessible guide to the latest advances in portfolio construction." --Mark Kritzman, President and CEO, Windham Capital Management, LLC "The topic of robust optimization (RO) has become 'hot' over the past several years, especially in real-world financial applications. This interest has been sparked, in part, by practitioners who implemented classical portfolio models for asset allocation without considering estimation and model robustness a part of their overall allocation methodology, and experienced poor performance. Anyone interested in these developments ought to own a copy of this book. The authors cover the recent developments of the RO area in an intuitive, easy-to-read manner, provide numerous examples, and discuss practical considerations. I highly recommend this book to finance professionals and students alike." --John M. Mulvey, Professor of Operations Research and Financial Engineering, Princeton University