Download or read book On the Estimation of the Global Minimum Variance Portfolio written by Alexander Kempf and published by . This book was released on 2005 with total page 27 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Computational Finance and Financial Econometrics written by Eric Zivot and published by CRC Press. This book was released on 2017-01-15 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents mathematical, programming and statistical tools used in the real world analysis and modeling of financial data. The tools are used to model asset returns, measure risk, and construct optimized portfolios using the open source R programming language and Microsoft Excel. The author explains how to build probability models for asset returns, to apply statistical techniques to evaluate if asset returns are normally distributed, to use Monte Carlo simulation and bootstrapping techniques to evaluate statistical models, and to use optimization methods to construct efficient portfolios.

Download or read book High Dimensional Covariance Estimation written by Mohsen Pourahmadi and published by John Wiley & Sons. This book was released on 2013-06-24 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: Methods for estimating sparse and large covariance matrices Covariance and correlation matrices play fundamental roles in every aspect of the analysis of multivariate data collected from a variety of fields including business and economics, health care, engineering, and environmental and physical sciences. High-Dimensional Covariance Estimation provides accessible and comprehensive coverage of the classical and modern approaches for estimating covariance matrices as well as their applications to the rapidly developing areas lying at the intersection of statistics and machine learning. Recently, the classical sample covariance methodologies have been modified and improved upon to meet the needs of statisticians and researchers dealing with large correlated datasets. High-Dimensional Covariance Estimation focuses on the methodologies based on shrinkage, thresholding, and penalized likelihood with applications to Gaussian graphical models, prediction, and mean-variance portfolio management. The book relies heavily on regression-based ideas and interpretations to connect and unify many existing methods and algorithms for the task. High-Dimensional Covariance Estimation features chapters on: Data, Sparsity, and Regularization Regularizing the Eigenstructure Banding, Tapering, and Thresholding Covariance Matrices Sparse Gaussian Graphical Models Multivariate Regression The book is an ideal resource for researchers in statistics, mathematics, business and economics, computer sciences, and engineering, as well as a useful text or supplement for graduate-level courses in multivariate analysis, covariance estimation, statistical learning, and high-dimensional data analysis.

Download or read book Estimating the Global Minimum Variance Portfolio written by Christoph Memmel and published by . This book was released on 2006 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt: According to standard portfolio theory, the tangency portfolio is the only efficient stock portfolio. However, empirical studies show that an investment in the global minimum variance portfolio often yields better out-of-sample results than does an investment in the tangency portfolio and suggest investing in the global minimum variance portfolio. But little is known about the distributions of the weights and return parameters of this portfolio. Our contribution is to determine these distributions. By doing so, we answer several important questions in asset management.

Download or read book Mean Variance Analysis in Portfolio Choice and Capital Markets written by Harry M. Markowitz and published by John Wiley & Sons. This book was released on 2000-02-15 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: In 1952, Harry Markowitz published "Portfolio Selection," a paper which revolutionized modern investment theory and practice. The paper proposed that, in selecting investments, the investor should consider both expected return and variability of return on the portfolio as a whole. Portfolios that minimized variance for a given expected return were demonstrated to be the most efficient. Markowitz formulated the full solution of the general mean-variance efficient set problem in 1956 and presented it in the appendix to his 1959 book, Portfolio Selection. Though certain special cases of the general model have become widely known, both in academia and among managers of large institutional portfolios, the characteristics of the general solution were not presented in finance books for students at any level. And although the results of the general solution are used in a few advanced portfolio optimization programs, the solution to the general problem should not be seen merely as a computing procedure. It is a body of propositions and formulas concerning the shapes and properties of mean-variance efficient sets with implications for financial theory and practice beyond those of widely known cases. The purpose of the present book, originally published in 1987, is to present a comprehensive and accessible account of the general mean-variance portfolio analysis, and to illustrate its usefulness in the practice of portfolio management and the theory of capital markets. The portfolio selection program in Part IV of the 1987 edition has been updated and contains exercises and solutions.

Download or read book Dominating Estimators for the Global Minimum Variance Portfolio written by Gabriel Frahm and published by . This book was released on 2009 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Predicting the Global Minimum Variance Portfolio written by Laura Reh and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: We propose a novel dynamic approach to forecast the weights of the global minimum variance portfolio (GMVP). The GMVP weights are the population coefficients of a linear regression of a benchmark return on a vector of return differences. This representation enables us to derive a consistent loss function from which we can infer the optimal GMVP weights without imposing any distributional assumptions on the returns. In order to capture time variation in the returns' conditional covariance structure, we model the portfolio weights through a recursive least squares (RLS) scheme as well as by generalized autoregressive score (GAS) type dynamics. Sparse parameterizations combined with targeting towards nonlinear shrinkage estimates of the long-run GMVP weights ensure scalability with respect to the number of assets. An empirical analysis of daily and monthly financial returns shows that the proposed models perform well in- and out-of-sample in comparison to existing approaches.

Download or read book Revision Policy for the Two Assets Global Minimum Variance Portfolio written by Vasyl Golosnoy and published by . This book was released on 2003 with total page 27 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Estimation of the Global Minimum Variance Portfolio in High Dimensions written by Taras Bodnar and published by . This book was released on 2013 with total page 33 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book A Test for the Weights of the Global Minimum Variance Portfolio in an Elliptical Model written by Taras Bodnar and published by . This book was released on 2004 with total page 26 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 Based and Factor Investing written by Emmanuel Jurczenko and published by Elsevier. This book was released on 2015-11-24 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a compilation of recent articles written by leading academics and practitioners in the area of risk-based and factor investing (RBFI). The articles are intended to introduce readers to some of the latest, cutting edge research encountered by academics and professionals dealing with RBFI solutions. Together the authors detail both alternative non-return based portfolio construction techniques and investing style risk premia strategies. Each chapter deals with new methods of building strategic and tactical risk-based portfolios, constructing and combining systematic factor strategies and assessing the related rules-based investment performances. This book can assist portfolio managers, asset owners, consultants, academics and students who wish to further their understanding of the science and art of risk-based and factor investing. Contains up-to-date research from the areas of RBFI Features contributions from leading academics and practitioners in this field Features discussions of new methods of building strategic and tactical risk-based portfolios for practitioners, academics and students

Download or read book DIY Financial Advisor written by Wesley R. Gray and published by John Wiley & Sons. This book was released on 2015-08-31 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: DIY Financial Advisor: A Simple Solution to Build and Protect Your Wealth DIY Financial Advisor is a synopsis of our research findings developed while serving as a consultant and asset manager for family offices. By way of background, a family office is a company, or group of people, who manage the wealth a family has gained over generations. The term 'family office' has an element of cachet, and even mystique, because it is usually associated with the mega-wealthy. However, practically speaking, virtually any family that manages its investments—independent of the size of the investment pool—could be considered a family office. The difference is mainly semantic. DIY Financial Advisor outlines a step-by-step process through which investors can take control of their hard-earned wealth and manage their own family office. Our research indicates that what matters in investing are minimizing psychology traps and managing fees and taxes. These simple concepts apply to all families, not just the ultra-wealthy. But can—or should—we be managing our own wealth? Our natural inclination is to succumb to the challenge of portfolio management and let an 'expert' deal with the problem. For a variety of reasons we discuss in this book, we should resist the gut reaction to hire experts. We suggest that investors maintain direct control, or at least a thorough understanding, of how their hard-earned wealth is managed. Our book is meant to be an educational journey that slowly builds confidence in one's own ability to manage a portfolio. We end our book with a potential solution that could be applicable to a wide-variety of investors, from the ultra-high net worth to middle class individuals, all of whom are focused on similar goals of preserving and growing their capital over time. DIY Financial Advisor is a unique resource. This book is the only comprehensive guide to implementing simple quantitative models that can beat the experts. And it comes at the perfect time, as the investment industry is undergoing a significant shift due in part to the use of automated investment strategies that do not require a financial advisor's involvement. DIY Financial Advisor is an essential text that guides you in making your money work for you—not for someone else!

Download or read book Theory and Practice of Recursive Identification written by Lennart Ljung and published by . This book was released on 1987 with total page 529 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Constructing a Global Minimum Variance Portfolio Using Microsoft Excel written by Kittima Kanmaravanich and published by . This book was released on 2011 with total page 68 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Global Minimum Variance Portfolio written by Majeed Simaan and published by . This book was released on 2018 with total page 23 pages. Available in PDF, EPUB and Kindle. Book excerpt: We conduct a horse race using three asset return volatility estimates: the sample variance, the exponential smoother used by RiskMetrics, and the generalized autoregressive conditional heteroskedasticity (GARCH). Our results are performed in both univariate and multivariate analysis. Our goal is to test whether using econometric tools achieves better economic performance. Economic performance is captured by portfolio performance as in DeMiguel et al (2009), who use three metrics to evaluate portfolios: risk-return, Sharpe-ratio, and turnover. Our portfolio of interest is the global minimum variance (GMV) portfolio since its inputs are determined solely by the variances and covariances of the asset returns. Computing the three portfolio performances for the three volatility candidate, we provide an evidence in support of the GARCH approach; however, this edge is undermined by greater portfolio turnover and larger estimation error, when the number assets in the portfolio is large.

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