Download or read book Portfolio Management Using Black Litterman written by Henning Padberg and published by GRIN Verlag. This book was released on 2008-01-24 with total page 24 pages. Available in PDF, EPUB and Kindle. Book excerpt: Seminar paper from the year 2007 in the subject Business economics - Banking, Stock Exchanges, Insurance, Accounting, grade: 1,3, University of Münster (Finance Center Münster), course: Betriebliche Finanzierung (Finance Seminar), language: English, abstract: The Black-Litterman optimization model is based on the idea of efficient markets and the capital asset pricing model (CAPM). The BL model enhances standard mean-variance optimization by implementing market views into the optimization process (probability theory). Investors obtain sophisticated and reasonable asset allocations. Portfolio management usually comprises asset allocation decisions with the goal of creating diversified portfolios. Managers can consult quantitative models to support their decision-making process. Fischer Black and Robert Litterman (1992) developed the Black-Litterman (BL) optimization model. It is based on the idea of efficient markets, the capital asset pricing model of Sharpe (1964) and Lintner (1965), as well as the established mean-variance optimization (MVO) developed by Markowitz (1952), and conditional probability theory dating back to Bayes (1763). Starting point of the BL model is the assumption that equilibrium markets and market cap. weights provide the investor with Implied Returns. The BL model uses a mixed estimation technique to incorporate investors’ Views into return forecasts. It is possible to implement relative and absolute opinions regarding expected returns of assets with different levels of confidence. These Views enable an adjustment of equilibrium Implied Returns, which forms a new expectation of BL Revised Implied Returns. As a result of optimization with BL input data, the investor gets new optimal portfolio weights. The motivation of Black and Litterman (1992) to develop a new portfolio optimization tool was a lack of acceptance of the Markowitz algorithm within professional asset managers. There aim was to shape a model which can overcome the weaknesses of MVO and which combines a quantitative and qualitative approach. Consequently, the BL model tackles the weakest point of MVO, its sensitivity to the return forecasts and allows taking active Views. This paper is structured in the following sections: First, it shows the basic principles on which the BL model is founded. Then, it illustrates the model by means of its assumptions, the general approach, and the math involved. Finally, it evaluates the model in a critical review, provides an overview of applicable extensions, and addresses the issues of practicability and behavioral finance.

Download or read book Multi Asset Portfolio Optimization and Out of Sample Performance written by Wolfgang Bessler and published by . This book was released on 2014 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Black-Litterman model aims to enhance asset allocation decisions by overcoming the problems of mean-variance portfolio optimization. We propose a sample based version of the Black-Litterman model and implement it on a multi-asset portfolio consisting of global stocks, bonds, and commodity indices, covering the period from January 1993 to December 2011. We test its out-of-sample performance relative to other asset allocation models and find that Black-Litterman optimized portfolios significantly outperform naïve-diversified portfolios (1/N-rule and strategic weights), and consistently perform better than mean-variance, Bayes-Stein, and minimum-variance strategies in terms of out-of-sample Sharpe ratios, even after controlling for different levels of risk aversion, investment constraints, and transaction costs. The BL model generates portfolios with lower risk, less extreme asset allocations, and higher diversification across asset classes. Sensitivity analyses indicate that these advantages are due to more stable mixed return estimates that incorporate the reliability of return predictions, smaller estimation errors, and lower turnover.

Download or read book Deconstructing Black Litterman written by Richard O. Michaud and published by . This book was released on 2015 with total page 21 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Markowitz (1952, 1959) mean-variance (MV) efficient frontier has been the theoretical standard for defining portfolio optimality for more than a half century. However, MV optimized portfolios are highly susceptible to estimation error and difficult to manage in practice (Jobson and Korkie 1980, 1981; Michaud 1989). The Black and Litterman (BL) (1992) proposal to solve MV optimization limitations produces a single maximum Sharpe ratio (MSR) optimal portfolio on the unconstrained MV efficient frontier based on an assumed MSR optimal benchmark portfolio and active views. The BL portfolio is often uninvestable in applications due to large leveraged or short allocations. BL use an input tuning process for computing acceptable sign constrained solutions. We compare constrained BL to MV and Michaud (1998) optimization for a simple data set. We show that constrained BL is identical to Markowitz and that Michaud portfolios are better diversified under identical inputs and optimality criteria. The attractiveness of the BL procedure is due to convenience rather than effective asset management and not recommendable relative to alternatives.

Download or read book Efficient Asset Management written by Richard O. Michaud and published by Oxford University Press. This book was released on 2008-03-03 with total page 207 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Perspectives in Sustainable Equity Investing written by Guillaume Coqueret and published by CRC Press. This book was released on 2022-03-08 with total page 135 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sustainable investing has recently gained traction throughout the world. This trend has multiple sources, which span from genuine ethical concerns to hopes of performance boosting, and also encompass risk mitigation. The resulting appetite for green assets is impacting the decisions of many investors. Perspectives in Sustainable Equity Investing is an up-to-date review of the academic literature on sustainable equity investing. It covers more than 800 academic sources grouped into six thematic chapters. Designed for corporate sustainability and financial management professionals, this is an ideal reference for ESG-driven financiers (both retail and institutional). Students majoring in finance or economics with some background or interest in ESG concerns would also find this compact overview useful. Key Features: Introduces the reader to terms and nomenclature used in the field. Surveys the link between sustainability and performance (including risk). Details the integration of sustainable criteria in complex portfolio optimization. Reviews the financial liabilities induced by climate change.

Download or read book Black Litterman Model for Continuous Distributions written by Jan Palczewski and published by . This book was released on 2018 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Black-Litterman methodology of portfolio optimization, developed at the turn of the 1990s, combines statistical information on asset returns with investor's views within the Markowitz mean-variance framework. The main assumption underlying the Black-Litterman model is that asset returns and investor's views are multivariate normally distributed. However, empirical research demonstrates that the distribution of asset returns has fat tails and is asymmetric, which contradicts normality. Recent advances in risk measurement advocate replacing the variance by risk measures that take account of tail behavior of the portfolio return distribution. This paper extends the Black-Litterman model into general continuous distributions and deviation measures of risk. Using ideas from the Black-Litterman methodology, we design numerical methods (with variance reduction techniques) for the inverse portfolio optimization that extracts statistical information from historical data in a stable way. We introduce a quantitative model for stating investor's views and blending them consistently with the market information. The theory is complemented by efficient numerical methods with the implementation distributed in the form of publicly available R packages. We conduct practical tests, which demonstrate significant impact of the choice of distributions on optimal portfolio weights to the extent that the classical Black-Litterman procedure cannot be viewed as an adequate approximation.

Download or read book Active Portfolio Management A Quantitative Approach for Producing Superior Returns and Selecting Superior Returns and Controlling Risk written by Richard C. Grinold and published by McGraw Hill Professional. This book was released on 1999-11-16 with total page 596 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This new edition of Active Portfolio Management continues the standard of excellence established in the first edition, with new and clear insights to help investment professionals." -William E. Jacques, Partner and Chief Investment Officer, Martingale Asset Management. "Active Portfolio Management offers investors an opportunity to better understand the balance between manager skill and portfolio risk. Both fundamental and quantitative investment managers will benefit from studying this updated edition by Grinold and Kahn." -Scott Stewart, Portfolio Manager, Fidelity Select Equity ® Discipline Co-Manager, Fidelity Freedom ® Funds. "This Second edition will not remain on the shelf, but will be continually referenced by both novice and expert. There is a substantial expansion in both depth and breadth on the original. It clearly and concisely explains all aspects of the foundations and the latest thinking in active portfolio management." -Eric N. Remole, Managing Director, Head of Global Structured Equity, Credit Suisse Asset Management. Mathematically rigorous and meticulously organized, Active Portfolio Management broke new ground when it first became available to investment managers in 1994. By outlining an innovative process to uncover raw signals of asset returns, develop them into refined forecasts, then use those forecasts to construct portfolios of exceptional return and minimal risk, i.e., portfolios that consistently beat the market, this hallmark book helped thousands of investment managers. Active Portfolio Management, Second Edition, now sets the bar even higher. Like its predecessor, this volume details how to apply economics, econometrics, and operations research to solving practical investment problems, and uncovering superior profit opportunities. It outlines an active management framework that begins with a benchmark portfolio, then defines exceptional returns as they relate to that benchmark. Beyond the comprehensive treatment of the active management process covered previously, this new edition expands to cover asset allocation, long/short investing, information horizons, and other topics relevant today. It revisits a number of discussions from the first edition, shedding new light on some of today's most pressing issues, including risk, dispersion, market impact, and performance analysis, while providing empirical evidence where appropriate. The result is an updated, comprehensive set of strategic concepts and rules of thumb for guiding the process of-and increasing the profits from-active investment management.

Download or read book Robust Portfolio Optimization and Management written by Frank J. Fabozzi and published by John Wiley & Sons. This book was released on 2007-04-27 with total page 513 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Portfolio Selection written by Harry Markowitz and published by Yale University Press. This book was released on 2008-10-01 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt: Embracing finance, economics, operations research, and computers, this book applies modern techniques of analysis and computation to find combinations of securities that best meet the needs of private or institutional investors.

Download or read book Modern Portfolio and Optimization Application written by Jirawat Tansiritanes and published by . This book was released on 2009 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Introduction to Risk Parity and Budgeting written by Thierry Roncalli and published by CRC Press. This book was released on 2016-04-19 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although portfolio management didn't change much during the 40 years after the seminal works of Markowitz and Sharpe, the development of risk budgeting techniques marked an important milestone in the deepening of the relationship between risk and asset management. Risk parity then became a popular financial model of investment after the global fina

Download or read book Black Littermann and Mean variance Efficient Portfolios written by Marcel Bross and published by . This book was released on 2005 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book An Improvement of the Global Minimum Variance Portfolio Using a Black Litterman Approach written by Maximilian Adelmann and published by . This book was released on 2016 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt: Asset management companies are constantly searching for portfolio optimization models that are on the one hand clear and intuitive and on the other provide high and reliable returns. This paper presents a modified version of the well-known Black-Litterman portfolio optimization approach. Unlike in the original model, the intuitive global minimum variance (GMV) portfolio serves as the reference portfolio. The introduction of a general rule for investors' views in combination with a simplification of the original Black-Litterman approach facilitates the implementation of the model and enables us to remove so-called dead assets from the GMV portfolio. As an additional advantageous feature our model is only based on variance-covariance estimations, and relative return estimations for our general rule. A numerical application of our modified Black-Litterman model to empirical data sets demonstrates that portfolios based on the model clearly outperform the GMV portfolio and the 1/N portfolio in terms of compound annual returns and out-of-sample Sharpe ratios.

Download or read book Risk and Asset Allocation written by Attilio Meucci and published by Springer Science & Business Media. This book was released on 2009-05-22 with total page 547 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discusses in the practical and theoretical aspects of one-period asset allocation, i.e. market Modeling, invariants estimation, portfolia evaluation, and portfolio optimization in the prexence of estimation risk The book is software based, many of the exercises simulate in Matlab the solution to practical problems and can be downloaded from the book's web-site

Download or read book Analyzing Dependent Data with Vine Copulas written by Claudia Czado and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides a step-by-step introduction to the class of vine copulas, their statistical inference and applications. It focuses on statistical estimation and selection methods for vine copulas in data applications. These flexible copula models can successfully accommodate any form of tail dependence and are vital to many applications in finance, insurance, hydrology, marketing, engineering, chemistry, aviation, climatology and health. The book explains the pair-copula construction principles underlying these statistical models and discusses how to perform model selection and inference. It also derives simulation algorithms and presents real-world examples to illustrate the methodological concepts. The book includes numerous exercises that facilitate and deepen readers understanding, and demonstrates how the R package VineCopula can be used to explore and build statistical dependence models from scratch. In closing, the book provides insights into recent developments and open research questions in vine copula based modeling. The book is intended for students as well as statisticians, data analysts and any other quantitatively oriented researchers who are new to the field of vine copulas. Accordingly, it provides the necessary background in multivariate statistics and copula theory for exploratory data tools, so that readers only need a basic grasp of statistics and probability.

Download or read book Uncertainty in the Black Litterman Model A Practical Note written by Adrian Fuhrer and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Mean Variance Portfolio Optimization Based on Ordinal Information written by Cela Eranda and published by . This book was released on 2019 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt: We propose a new approach that allows for incorporating qualitative views, such as ordering information, into estimates of future asset returns within the Black-Litterman model. We develop a mathematical framework and numerical computation methods for this setting. We find importance sampling to be the most appropriate numerical approach in terms of accuracy and computation time. Using empirical stock market data, we find our extended Black-Litterman model to process ordering information on future asset returns better than two previously suggested approaches. Our new estimator is successfully evaluated in the context of mean-variance portfolio optimization.