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Out Of Sample Performance Based Estimation Of Expected Returns For Portfolio Selection
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Book Synopsis Out-of-sample Performance-based Estimation of Expected Returns for Portfolio Selection by : Peng-Chu Chen
Download or read book Out-of-sample Performance-based Estimation of Expected Returns for Portfolio Selection written by Peng-Chu Chen and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper provides a framework for obtaining the estimator of expected asset returns for portfolio selection. The framework relies on a linear model where the expected returns are the coefficients to be estimated. The model is fitted to a synthetic dataset by Bayesian regression. The estimator is computed using a Gibbs sampler; it is consistent and asymptotically efficient when the size of the synthetic dataset grows to infinity. An empirical study shows that, under appropriate conditions, mean-variance portfolios constructed using this estimator yield better out-of-sample average returns and Sharpe ratios than benchmark portfolios, with or without a norm constraint.
Book Synopsis Out-of-sample Performance-based Estimation Methods for Portfolio Selection by : 汪岩
Download or read book Out-of-sample Performance-based Estimation Methods for Portfolio Selection written by 汪岩 and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Sparse and Stable Portfolio Selection with Parameter Uncertainty by : Jiahan Li
Download or read book Sparse and Stable Portfolio Selection with Parameter Uncertainty written by Jiahan Li and published by . This book was released on 2015 with total page 31 pages. Available in PDF, EPUB and Kindle. Book excerpt: A number of alternative mean-variance portfolio strategies have been recently proposed to improve the empirical performance of the classic Markowitz mean-variance framework. Designed as remedies for parameter uncertainty and estimation errors in portfolio selection problems, these alternative portfolio strategies deliver substantially better out-of-sample performance. In this paper, we first show how to solve a general portfolio selection problem in a linear regression framework. Then we propose to reduce the estimation risk of expected returns and the variance-covariance matrix of asset returns by imposing additional constraints on the portfolio weights. With results from linear regression models, we show that portfolio weights derived from new approaches enjoy two favorable properties: sparsity and stability. Moreover, we present insights into these new approaches as well as their connections to alternative strategies in literature. Four empirical studies show that the proposed strategies have better out-of-sample performance and lower turnover than many other strategies, especially when the estimation risk is large.
Book Synopsis Predictions, Nonlinearities and Portfolio Choice by : Friedrich Christian Kruse
Download or read book Predictions, Nonlinearities and Portfolio Choice written by Friedrich Christian Kruse and published by BoD – Books on Demand. This book was released on 2012 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: Finance researchers and asset management practitioners put a lot of effort into the question of optimal asset allocation. With this respect, a lot of research has been conducted on portfolio decision making as well as quantitative modeling and prediction models. This study brings together three fields of research, which are usually analyzed in an isolated manner in the literature: - Predictability of asset returns and their covariance matrix - Optimal portfolio decision making - Nonlinear modeling, performed by artificial neural networks, and their impact on predictions as well as optimal portfolio construction Including predictability in asset allocation is the focus of this work and it pays special attention to issues related to nonlinearities. The contribution of this study to the portfolio choice literature is twofold. First, motivated by the evidence of linear predictability, the impact of nonlinear predictions on portfolio performances is analyzed. Predictions are empirically performed for an investor who invests in equities (represented by the DAX index), bonds (represented by the REXP index) and a risk-free rate. Second, a solution to the dynamic programming problem for intertemporal portfolio choice is presented. The method is based on functional approximations of the investor's value function with artificial neural networks. The method is easily capable of handling multiple state variables. Hence, the effect of adding predictive parameters to the state space is the focus of analysis as well as the impacts of estimation biases and the view of a Bayesian investor on intertemporal portfolio choice. One important empirical result shows that residual correlation among state variables have an impact on intertemporal portfolio decision making.
Book Synopsis Reducing Estimation Risk in Optimal Portfolio Selection When Short Sales are Allowed by : Gordon J. Alexander
Download or read book Reducing Estimation Risk in Optimal Portfolio Selection When Short Sales are Allowed written by Gordon J. Alexander and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The issue of estimation risk is of particular interest to the decision-making processes of portfolio managers who use long-short investment strategies. Accordingly, our paper explores the question of whether a VaR constraint reduces estimation risk when short sales are allowed. We find that such a constraint notably decreases errors in estimates of the expected return, standard deviation, and VaR of optimal portfolios. Furthermore, optimal portfolios in the presence of the constraint are substantially closer to the 'true' efficient frontier than those in its absence. Finally, we provide VaR bounds and confidence levels for the constraint that lead to the best out-of-sample performance.
Book Synopsis Estimation of Expected Returns, Time Consistency of a Stock Return Model, and Their Application to Portfolio Selection by : Huaqiang Ma
Download or read book Estimation of Expected Returns, Time Consistency of a Stock Return Model, and Their Application to Portfolio Selection written by Huaqiang Ma and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Robust Portfolio Selection Based on the Shrinkage Estimation by :
Download or read book Robust Portfolio Selection Based on the Shrinkage Estimation written by and published by . This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: When portfolio selection is implemented by using the past sample values, parameter uncertainty may lead to suboptimal portfolios. Previous studies of portfolio selection demonstrate that classical approach based on the simple mean estimator is less reliable cause of inherent estimation error. In this paper, we investigate a shrinkage estimator based on Stein's idea in measuring the expected returns. We apply the research of Jorion (1985) to Taiwan Stock market, present the effects of estimation error on the portfolio selection and demonstrate that the shrinkage estimator is robust and dominates the classical estimator on the MSE criterion. In addition, we also examine the effect of different shrinkage target on the performance of the Bayes-Stein estimator and find that this estimator still has lower risk than the classical sample mean.
Book Synopsis A Statistical Response to Challenges in Vast Portfolio Selection by : Danqiao Guo
Download or read book A Statistical Response to Challenges in Vast Portfolio Selection written by Danqiao Guo and published by . This book was released on 2019 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: The thesis is written in response to emerging issues brought about by an increasing number of assets allocated in a portfolio and seeks answers to puzzling empirical findings in the portfolio management area. Over the years, researchers and practitioners working in the portfolio optimization area have been concerned with estimation errors in the first two moments of asset returns. The thesis comprises several related chapters on our statistical inquiry into this subject. Chapter 1 of the thesis contains an introduction to what will be reported in the remaining chapters. A few well-known covariance matrix estimation methods in the literature involve adjustment of sample eigenvalues. Chapter 2 of the thesis examines the effects of sample eigenvalue adjustment on the out-of-sample performance of a portfolio constructed from the sample covariance matrix. We identify a few sample eigenvalue adjustment patterns that lead to a definite improvement in the out-of-sample portfolio Sharpe ratio when the true covariance matrix admits a high-dimensional factor model. Chapter 3 shows that even when the covariance matrix is poorly estimated, it is still possible to obtain a robust maximum Sharpe ratio (MSR) portfolio by exploiting the uneven distribution of estimation errors across principal components. This is accomplished by approximating the vector of expected future asset returns using a few relatively accurate sample principal components. We discuss two approximation methods. The first method leads to a subtle connection to existing approaches in the literature, while the second one named the ``spectral selection method" is novel and able to address main shortcomings of existing methods in the literature. A few academic studies report an unsatisfactory performance of the optimized portfolios relative to that of the 1/N portfolio. Chapter 4 of the thesis reports an in-depth investigation into the reasons behind the reported superior performance of the 1/N portfolio. It is supported by both theoretical and empirical evidence that the success of the 1/N portfolio is by no means due to the failure of the portfolio optimization theory. Instead, a major reason behind the superiority of the 1/N portfolio is its adjacency to the mean-variance optimal portfolio. Chapter 5 examines the performance of randomized 1/N stock portfolios over time. During the last four decades these portfolios outperformed the market. The construction of these portfolios implies that their constituent stocks are in general older than those in the market as a whole. We show that the differential performance can be explained by the relation between stock returns and firm age. We document a significant relation between age and returns in the US stock market. Since 1977 stock returns have been an increasing function of age apart from the oldest ages. For this period the age effect completely dominates the size effect.
Book Synopsis The Theory and Practice of Investment Management by : Frank J. Fabozzi
Download or read book The Theory and Practice of Investment Management written by Frank J. Fabozzi and published by John Wiley & Sons. This book was released on 2011-04-18 with total page 708 pages. Available in PDF, EPUB and Kindle. Book excerpt: An updated guide to the theory and practice of investment management Many books focus on the theory of investment management and leave the details of the implementation of the theory up to you. This book illustrates how theory is applied in practice while stressing the importance of the portfolio construction process. The Second Edition of The Theory and Practice of Investment Management is the ultimate guide to understanding the various aspects of investment management and investment vehicles. Tying together theoretical advances in investment management with actual practical applications, this book gives you a unique opportunity to use proven investment management techniques to protect and grow a portfolio under many different circumstances. Contains new material on the latest tools and strategies for both equity and fixed income portfolio management Includes key take-aways as well as study questions at the conclusion of each chapter A timely updated guide to an important topic in today's investment world This comprehensive investment management resource combines real-world financial knowledge with investment management theory to provide you with the practical guidance needed to succeed within the investment management arena.
Book Synopsis Empirical Asset Pricing by : Wayne Ferson
Download or read book Empirical Asset Pricing written by Wayne Ferson and published by MIT Press. This book was released on 2019-03-12 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to the theory and methods of empirical asset pricing, integrating classical foundations with recent developments. This book offers a comprehensive advanced introduction to asset pricing, the study of models for the prices and returns of various securities. The focus is empirical, emphasizing how the models relate to the data. The book offers a uniquely integrated treatment, combining classical foundations with more recent developments in the literature and relating some of the material to applications in investment management. It covers the theory of empirical asset pricing, the main empirical methods, and a range of applied topics. The book introduces the theory of empirical asset pricing through three main paradigms: mean variance analysis, stochastic discount factors, and beta pricing models. It describes empirical methods, beginning with the generalized method of moments (GMM) and viewing other methods as special cases of GMM; offers a comprehensive review of fund performance evaluation; and presents selected applied topics, including a substantial chapter on predictability in asset markets that covers predicting the level of returns, volatility and higher moments, and predicting cross-sectional differences in returns. Other chapters cover production-based asset pricing, long-run risk models, the Campbell-Shiller approximation, the debate on covariance versus characteristics, and the relation of volatility to the cross-section of stock returns. An extensive reference section captures the current state of the field. The book is intended for use by graduate students in finance and economics; it can also serve as a reference for professionals.
Book Synopsis Portfolio Optimization and Hedge Fund Style Allocation Decisions by : Noel Amenc
Download or read book Portfolio Optimization and Hedge Fund Style Allocation Decisions written by Noel Amenc and published by . This book was released on 2002 with total page 24 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper attempts to evaluate the out-of-sample performance of an improved estimator of the covariance structure of hedge fund index returns, focusing on its use for optimal portfolio selection. Using data from CSFB-Tremont hedge fund indices, we find that ex-post volatility of minimum variance portfolios generated using implicit factor based estimation techniques is between 1.5 and 6 times lower than that of a value-weighted benchmark, such differences being both economically and statistically significant. This strongly indicates that optimal inclusion of hedge funds in an investor portfolio can potentially generate a dramatic decrease in the portfolio volatility on an out-of-sample basis. Differences in mean returns, on the other hand, are not statistically significant, suggesting that the improvement in terms of risk control does not necessarily come at the cost of lower expected returns.
Book Synopsis Forecasting Expected Returns in the Financial Markets by : Stephen Satchell
Download or read book Forecasting Expected Returns in the Financial Markets written by Stephen Satchell and published by Elsevier. This book was released on 2011-04-08 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forecasting returns is as important as forecasting volatility in multiple areas of finance. This topic, essential to practitioners, is also studied by academics. In this new book, Dr Stephen Satchell brings together a collection of leading thinkers and practitioners from around the world who address this complex problem using the latest quantitative techniques. *Forecasting expected returns is an essential aspect of finance and highly technical *The first collection of papers to present new and developing techniques *International authors present both academic and practitioner perspectives
Book Synopsis A risk-gain-sparsity optimization approach by : Alessandra Congedo
Download or read book A risk-gain-sparsity optimization approach written by Alessandra Congedo and published by Roma TrE-Press. This book was released on 2024-06-12 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uno dei principi fondamentali dei modelli di selezione del portafoglio è la minimizzazione del rischio attraverso la diversificazione degli investimenti. Tuttavia, i benefici della diversificazione si riducono in presenza di un'elevata correlazione tra gli asset. È noto che la diversificazione attraverso l'uso di portafogli più ampi non è il modo migliore per ottenere un miglioramento della performance fuori campione. Inoltre, l'inclusione di un numero elevato di posizioni nel portafoglio aumenta i costi di gestione e di transazione. Mentre i modelli classici di selezione del portafoglio si concentrano sulla minimizzazione del rischio e sulla massimizzazione del rendimento, lo scopo di questo lavoro è quello di includere un terzo obiettivo: la norma-1. Ciò consente di selezionare portafogli sparsi, cioè con un numero limitato di attività, che sono più facili da gestire e consentono di ottenere buoni risultati in termini di rischio-rendimento. La nostra analisi empirica si basa su un dataset di riferimento disponibile pubblicamente e spesso utilizzato in letteratura. DOI: 10.13134/979-12-5977-332-6
Book Synopsis Optimization and Control for Systems in the Big-Data Era by : Tsan-Ming Choi
Download or read book Optimization and Control for Systems in the Big-Data Era written by Tsan-Ming Choi and published by Springer. This book was released on 2017-05-04 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on optimal control and systems engineering in the big data era. It examines the scientific innovations in optimization, control and resilience management that can be applied to further success. In both business operations and engineering applications, there are huge amounts of data that can overwhelm computing resources of large-scale systems. This “big data” provides new opportunities to improve decision making and addresses risk for individuals as well in organizations. While utilizing data smartly can enhance decision making, how to use and incorporate data into the decision making framework remains a challenging topic. Ultimately the chapters in this book present new models and frameworks to help overcome this obstacle. Optimization and Control for Systems in the Big-Data Era: Theory and Applications is divided into five parts. Part I offers reviews on optimization and control theories, and Part II examines the optimization and control applications. Part III provides novel insights and new findings in the area of financial optimization analysis. The chapters in Part IV deal with operations analysis, covering flow-shop operations and quick response systems. The book concludes with final remarks and a look to the future of big data related optimization and control problems.
Book Synopsis Advances in Investment Analysis and Portfolio Management by : Cheng-Few Lee
Download or read book Advances in Investment Analysis and Portfolio Management written by Cheng-Few Lee and published by Elsevier. This book was released on 2002-07-12 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: Twelve papers focus on investment analysis, portfolio theory, and their implementation in portfolio management
Book Synopsis How Efficient Use of Information Changes Portfolio Allocations by : Nato Kemkhadze
Download or read book How Efficient Use of Information Changes Portfolio Allocations written by Nato Kemkhadze and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Unknown model parameters, like expected returns, cannot be accurately estimated from short samples. Respective estimation error most likely leads to the portfolio, inconsistent with its target risk/return profile. We investigate the ways of reducing the impact of estimation error on portfolio selection in a particular mean-variance setting. We consider the cross-section of asset returns where assets possess predictability but up to an unknown scale function. Assuming stability in the return generating process, how best we use historical data to infer the optimal scaling of our expected return forecasts? In a Bayesian implementation we make inferences about unknown parameters using information on results of unrelated experiments coupled with the sample data. We express the optimal amount of money put at risk as a complicated function of a prior on manager's forecasting skills and observed returns. We find that, to fully exploit available information, an investor needs only first two moments of the posterior distribution of his forecasting skills. Portfolio holdings, derived under efficient use of information, strikingly differ from the holdings derived from the sample information only (i.e. using classical maximum likelihood estimation MLE). Optimization in the efficient way with prior favors concentrated portfolio holdings. Since concentrated holdings drive portfolio risk, fund managers should treat larger holdings with caution while they can afford not to be conservative on small holdings. Ignoring the prior and optimizing on observed returns only result in massively inflated allocations and leveraged portfolio, or no investments at all besides cash. Portfolio selection with prior that uses naive mode-estimates of the posterior instead of mean-estimates leads to as inconsistent portfolio, similar to the portfolio selection led by MLE-based estimates. The impact of efficient use of information on portfolio selection is generalized to the case of non-homogeneously predictable classes of assets, where each class has its own degree of predictability.
Book Synopsis The Oxford Handbook of Quantitative Asset Management by : Bernd Scherer
Download or read book The Oxford Handbook of Quantitative Asset Management written by Bernd Scherer and published by Oxford University Press. This book was released on 2012 with total page 530 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores the current state of the art in quantitative investment management across seven key areas. Chapters by academics and practitioners working in leading investment management organizations bring together major theoretical and practical aspects of the field.
