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Return Prediction And Portfolio Selection
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Book Synopsis Return Prediction and Portfolio Selection by : Min Zhu
Download or read book Return Prediction and Portfolio Selection written by Min Zhu and published by . This book was released on 2017 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt: The inquiries to return predictability are traditionally limited to the first two moments, mean and volatility. Analogously, literature on portfolio selection also stems from a moment-based analysis with up to the fourth moment being considered. This paper develops a distribution-based framework for both return prediction and portfolio selection. More specifically, a time-varying return distribution is modeled through quantile regression and copulas, using the quantile approach to extract information in marginal distributions and copulas to capture dependence structure. A nonlinear utility function is proposed for portfolio selection which utilizes the full underlying return distribution. An empirical application to US data highlights not only the predictability of the stock and bond return distributions, but also the additional information provided by the distributional approach which cannot be captured by the traditional moment-based methods.
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 Asset Return Prediction and Covariance Matrix Estimation for Portfolio Selection in Large Dimensions by : Gianluca De Nard
Download or read book Asset Return Prediction and Covariance Matrix Estimation for Portfolio Selection in Large Dimensions written by Gianluca De Nard and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Online Portfolio Selection by : Bin Li
Download or read book Online Portfolio Selection written by Bin Li and published by CRC Press. This book was released on 2018-10-30 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the aim to sequentially determine optimal allocations across a set of assets, Online Portfolio Selection (OLPS) has significantly reshaped the financial investment landscape. Online Portfolio Selection: Principles and Algorithms supplies a comprehensive survey of existing OLPS principles and presents a collection of innovative strategies that leverage machine learning techniques for financial investment. The book presents four new algorithms based on machine learning techniques that were designed by the authors, as well as a new back-test system they developed for evaluating trading strategy effectiveness. The book uses simulations with real market data to illustrate the trading strategies in action and to provide readers with the confidence to deploy the strategies themselves. The book is presented in five sections that: Introduce OLPS and formulate OLPS as a sequential decision task Present key OLPS principles, including benchmarks, follow the winner, follow the loser, pattern matching, and meta-learning Detail four innovative OLPS algorithms based on cutting-edge machine learning techniques Provide a toolbox for evaluating the OLPS algorithms and present empirical studies comparing the proposed algorithms with the state of the art Investigate possible future directions Complete with a back-test system that uses historical data to evaluate the performance of trading strategies, as well as MATLAB® code for the back-test systems, this book is an ideal resource for graduate students in finance, computer science, and statistics. It is also suitable for researchers and engineers interested in computational investment. Readers are encouraged to visit the authors’ website for updates: http://olps.stevenhoi.org.
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 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 On Market Timing and Investment Performance Part II: Statistical Procedures for Evaluating Forecasting Skills by : Roy Henriksson
Download or read book On Market Timing and Investment Performance Part II: Statistical Procedures for Evaluating Forecasting Skills written by Roy Henriksson and published by . This book was released on 2023-07-18 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Portfolio Optimization with Industry Return Prediction Models by : Wolfgang Bessler
Download or read book Portfolio Optimization with Industry Return Prediction Models written by Wolfgang Bessler and published by . This book was released on 2017 with total page 52 pages. Available in PDF, EPUB and Kindle. Book excerpt: We postulate that utilizing return prediction models with fundamental, macroeconomic, and technical indicators instead of using historical averages should result in superior asset allocation decisions. We investigate the predictive power of individual variables for forecasting industry returns in-sample and out-of-sample and then analyze multivariate predictive regression models including OLS, a regularization technique, principal components, a target-relevant latent factor approach, and forecast combinations. The gains from using industry return predictions are evaluated in an out-of-sample Black-Litterman portfolio optimization framework. We provide empirical evidence that portfolio optimization utilizing industry return prediction models significantly outperform portfolios using historical averages and those being passively managed.
Book Synopsis Fat-Tailed and Skewed Asset Return Distributions by : Svetlozar T. Rachev
Download or read book Fat-Tailed and Skewed Asset Return Distributions written by Svetlozar T. Rachev and published by John Wiley & Sons. This book was released on 2005-09-15 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: While mainstream financial theories and applications assume that asset returns are normally distributed, overwhelming empirical evidence shows otherwise. Yet many professionals don’t appreciate the highly statistical models that take this empirical evidence into consideration. Fat-Tailed and Skewed Asset Return Distributions examines this dilemma and offers readers a less technical look at how portfolio selection, risk management, and option pricing modeling should and can be undertaken when the assumption of a non-normal distribution for asset returns is violated. Topics covered in this comprehensive book include an extensive discussion of probability distributions, estimating probability distributions, portfolio selection, alternative risk measures, and much more. Fat-Tailed and Skewed Asset Return Distributions provides a bridge between the highly technical theory of statistical distributional analysis, stochastic processes, and econometrics of financial returns and real-world risk management and investments.
Book Synopsis Portfolio Structuring and the Value of Forecasting by : Jacques Lussier
Download or read book Portfolio Structuring and the Value of Forecasting written by Jacques Lussier and published by CFA Institute Research Foundation. This book was released on 2016-10-10 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis International Capital Flows by : Martin Feldstein
Download or read book International Capital Flows written by Martin Feldstein and published by University of Chicago Press. This book was released on 2007-12-01 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent changes in technology, along with the opening up of many regions previously closed to investment, have led to explosive growth in the international movement of capital. Flows from foreign direct investment and debt and equity financing can bring countries substantial gains by augmenting local savings and by improving technology and incentives. Investing companies acquire market access, lower cost inputs, and opportunities for profitable introductions of production methods in the countries where they invest. But, as was underscored recently by the economic and financial crises in several Asian countries, capital flows can also bring risks. Although there is no simple explanation of the currency crisis in Asia, it is clear that fixed exchange rates and chronic deficits increased the likelihood of a breakdown. Similarly, during the 1970s, the United States and other industrial countries loaned OPEC surpluses to borrowers in Latin America. But when the U.S. Federal Reserve raised interest rates to control soaring inflation, the result was a widespread debt moratorium in Latin America as many countries throughout the region struggled to pay the high interest on their foreign loans. International Capital Flows contains recent work by eminent scholars and practitioners on the experience of capital flows to Latin America, Asia, and eastern Europe. These papers discuss the role of banks, equity markets, and foreign direct investment in international capital flows, and the risks that investors and others face with these transactions. By focusing on capital flows' productivity and determinants, and the policy issues they raise, this collection is a valuable resource for economists, policymakers, and financial market participants.
Book Synopsis Artificial Intelligence in Asset Management by : Söhnke M. Bartram
Download or read book Artificial Intelligence in Asset Management written by Söhnke M. Bartram and published by CFA Institute Research Foundation. This book was released on 2020-08-28 with total page 95 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence (AI) has grown in presence in asset management and has revolutionized the sector in many ways. It has improved portfolio management, trading, and risk management practices by increasing efficiency, accuracy, and compliance. In particular, AI techniques help construct portfolios based on more accurate risk and return forecasts and more complex constraints. Trading algorithms use AI to devise novel trading signals and execute trades with lower transaction costs. AI also improves risk modeling and forecasting by generating insights from new data sources. Finally, robo-advisors owe a large part of their success to AI techniques. Yet the use of AI can also create new risks and challenges, such as those resulting from model opacity, complexity, and reliance on data integrity.
Book Synopsis Portfolio Selection by : Harry Markowitz
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.
Book Synopsis Biological Systems: Nonlinear Dynamics Approach by : Jorge Carballido-Landeira
Download or read book Biological Systems: Nonlinear Dynamics Approach written by Jorge Carballido-Landeira and published by Springer. This book was released on 2019-04-29 with total page 111 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book collects recent advances in the field of nonlinear dynamics in biological systems. Focusing on medical applications as well as more fundamental questions in biochemistry, it presents recent findings in areas such as control in chemically driven reaction-diffusion systems, electrical wave propagation through heart tissue, neural network growth, chiral symmetry breaking in polymers and mechanochemical pattern formation in the cytoplasm, particularly in the context of cardiac cells. It is a compilation of works, including contributions from international scientists who attended the “2nd BCAM Workshop on Nonlinear Dynamics in Biological Systems,” held at the Basque Center for Applied Mathematics, Bilbao in September 2016. Embracing diverse disciplines and using multidisciplinary approaches – including theoretical concepts, simulations and experiments – these contributions highlight the nonlinear nature of biological systems in order to be able to reproduce their complex behavior. Edited by the conference organizers and featuring results that represent recent findings and not necessarily those presented at the conference, the book appeals to applied mathematicians, biophysicists and computational biologists.
Book Synopsis Neural and Adaptive Systems by : José C. Principe
Download or read book Neural and Adaptive Systems written by José C. Principe and published by John Wiley & Sons. This book was released on 2000 with total page 680 pages. Available in PDF, EPUB and Kindle. Book excerpt: Develop New Insight into the Behavior of Adaptive Systems This one-of-a-kind interactive book and CD-ROM will help you develop a better understanding of the behavior of adaptive systems. Developed as part of a project aimed at innovating the teaching of adaptive systems in science and engineering, it unifies the concepts of neural networks and adaptive filters into a common framework. It begins by explaining the fundamentals of adaptive linear regression and builds on these concepts to explore pattern classification, function approximation, feature extraction, and time-series modeling/prediction. The text is integrated with the industry standard neural network/adaptive system simulator NeuroSolutions. This allows the authors to demonstrate and reinforce key concepts using over 200 interactive examples. Each of these examples is 'live,' allowing the user to change parameters and experiment first-hand with real-world adaptive systems. This creates a powerful environment for learning through both visualization and experimentation. Key Features of the Text The text and CD combine to become an interactive learning tool. Emphasis is on understanding the behavior of adaptive systems rather than mathematical derivations. Each key concept is followed by an interactive example. Over 200 fully functional simulations of adaptive systems are included. The text and CD offer a unified view of neural networks, adaptive filters, pattern recognition, and support vector machines. Hyperlinks allow instant access to keyword definitions, bibliographic references, equations, and advanced discussions of concepts. The CD-ROM Contains: A complete, electronic version of the text in hypertext format NeuroSolutions, an industry standard, icon-based neural network/adaptive system simulator A tutorial on how to use NeuroSolutions Additional data files to use with the simulator "An innovative approach to describing neurocomputing and adaptive learning systems from a perspective which unifies classical linear adaptive systems approaches with the modern advances in neural networks. It is rich in examples and practical insight." —James Zeidler, University of California, San Diego
Book Synopsis Portfolio Selection Using Multi-Objective Optimisation by : Saurabh Agarwal
Download or read book Portfolio Selection Using Multi-Objective Optimisation written by Saurabh Agarwal and published by Springer. This book was released on 2017-08-21 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores the risk-return paradox in portfolio selection by incorporating multi-objective criteria. Empirical research is presented on the development of alternate portfolio models and their relative performance in the risk/return framework to provide solutions to multi-objective optimization. Next to outlining techniques for undertaking individual investor’s profiling and portfolio programming, it also offers a new and practical approach for multi-objective portfolio optimization. This book will be of interest to Foreign Institutional Investors (FIIs), Mutual Funds, investors, and researchers and students in the field.
Book Synopsis Machine Learning for Asset Management by : Emmanuel Jurczenko
Download or read book Machine Learning for Asset Management written by Emmanuel Jurczenko and published by John Wiley & Sons. This book was released on 2020-10-06 with total page 460 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new edited volume consists of a collection of original articles written by leading financial economists and industry experts in the area of machine learning for asset management. The chapters introduce the reader to some of the latest research developments in the area of equity, multi-asset and factor investing. Each chapter deals with new methods for return and risk forecasting, stock selection, portfolio construction, performance attribution and transaction costs modeling. This volume will be of great help to portfolio managers, asset owners and consultants, as well as academics and students who want to improve their knowledge of machine learning in asset management.
