Download or read book Empirical Analysis of Stock Market Return Predictability written by Justus Heuer and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Return Predictability in Santiago Stock Exchange written by Carlos Elias and published by . This book was released on 2017 with total page 37 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper provides a comprehensive analysis on stock return predictability in Santiago Stock Exchange from January 2007 to January 2016 by employing portfolio method. In the risk-related predictors, we found no statistically significant predictive power of beta, total volatility, and idiosyncratic volatility in all stock sets. In addition to market cap and short-term reversal, the two cheapness variables, book-to-market and cash-flow-to-price ratios showed consistent economically and statistically significant predictive powers in determining the stock returns in the Santiago Stock Exchange. We also found that regrouping the stocks as small and large, low and high book-to-market, beta, and momentum according to the median values adds insights to the analysis. Our results show that the set of large stocks in the exchange is the least predictable set of stocks, however, momentum is efficiently predicted their return. Momentum is significant only for the large stocks and low book-to-market stocks, and risk-related predictors are good for high beta stocks only.
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.
Download or read book Stock Return Predictability written by Arthur Ritter and published by GRIN Verlag. This book was released on 2015-05-27 with total page 21 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research Paper (postgraduate) from the year 2015 in the subject Business economics - Banking, Stock Exchanges, Insurance, Accounting, grade: 17 (1,3), University of St Andrews (School of Management), course: Investment and Portfolio Management, language: English, abstract: Empirical evidence of stock return predictability obtained by financial ratios or macroeconomic factors has received substantial attention and remains a controversial topic to date. This is no surprise given that the existence of return predictability is not only of interest to practitioners but also introduces severe implications for financial models of risk and return. Founded on the assumption of efficient capital markets, research on capital asset pricing models has instigated this emergence of stock return predictability factors. Analysing these factors categorically, this paper will provide a balanced discussion of advocates as well as sceptics of stock return predictability. This essay will commence by firstly outlining the fundamental assumptions of an efficient capital market and its implications for return predictability. Subsequently, a thorough focus will be placed on the most significant predictability factors, including fundamental financial ratios and macroeconomic indicators as well as the validity of sampling methods used to attain return forecasts. Lastly this essay will reflect on the findings while proposing areas of further research.
Download or read book Predictability of the Swiss Stock Market with Respect to Style written by Patrick Scheurle and published by Springer Science & Business Media. This book was released on 2010-07-03 with total page 185 pages. Available in PDF, EPUB and Kindle. Book excerpt: Patrick Scheurle investigates refined market segments such as small value stocks or large growth stocks with respect to return predictability. The empirical research reveals significant positive first-order serial correlation in the returns of large value stocks, large neutral stocks, small neutral stocks, and small growth stocks.
Download or read book Empirical Studies on Stock Return Predictability written by Jingya Wang and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Complex Systems in Finance and Econometrics written by Robert A. Meyers and published by Springer Science & Business Media. This book was released on 2010-11-03 with total page 919 pages. Available in PDF, EPUB and Kindle. Book excerpt: Finance, Econometrics and System Dynamics presents an overview of the concepts and tools for analyzing complex systems in a wide range of fields. The text integrates complexity with deterministic equations and concepts from real world examples, and appeals to a broad audience.
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:
Download or read book The Optimal Use of Return Predictability written by Abhay Abhyankar and published by . This book was released on 2019 with total page 45 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper we investigate the empirical performance of unconditionally efficient portfolios strategies for a number of commonly used predictive variables. These strategies, which optimally utilize asset return predictability in portfolio formation were studied by Hansen and Richard (1987) and Ferson and Siegel (2001). Our criterion is to maximize various ex-post performance measures and we conduct both in-sample as well as out-of-sample analysis. Our analysis allows us to determine the economic value of using different predictor variables and also groups of predictor variables.Overall we find that the optimal use of conditioning information significantly improves the risk-return tradeoff available to a mean-variance investor relative to fixed weight strategies. These findings are consistent across portfolio efficiency measures such as Sharpe ratios, portfolio variance subject to a mean constraint or portfolio mean subject to a volatility constraint as well as measures of economic value such as switching costs.In addition we also compare the performance of the unconditionally efficient strategies with conditionally efficient strategies from an investment-based perspective. We find that the performance of the two strategies is quite different due to the differing response of the portfolio weights of the two strategies to conditioning information.
Download or read book Predicting Stock Returns written by David G McMillan and published by Springer. This book was released on 2017-11-30 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive analysis of asset price movement. It examines different aspects of stock return predictability, the interaction between stock return and dividend growth predictability, the relationship between stocks and bonds, and the resulting implications for asset price movement. By contributing to our understanding of the factors that cause price movement, this book will be of benefit to researchers, practitioners and policy makers alike.
Download or read book International Evidence for Return Predictability and the Implications for Long run Covariation of the G7 Stock Markets written by Thomas Nitschka and published by . This book was released on 2007 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Empirical Studies on Stock Return Predictability and International Risk Exposure written by Qinye Lu and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Stock Return Predictability a Neural Network Approach written by Olaf Westheider and published by . This book was released on 1994 with total page 46 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The Predictabilty of German Stock Returns written by Judith Klähn and published by Deutscher Universitätsverlag. This book was released on 2000-06-28 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ten years ago, most textbooks on financial management advocated the thesis that stock returns are essentially unpredictable. This theory is called the Random Walk Approach to the development of asset prices. The approach said that the stock market is subject to random changes, which are, by definition, unpredictable. Apparent predictabilities, if ever discovered, were either dismissed as statistical artifacts or as data that cannot be exploited after transaction costs. In the meantime, the world of financial economics has turned upside down. We now realize clearly that returns are indeed predictable to a large extent. Recent studies have confirmed that U.S. stock returns are highly predictable. In this new research context, Judith Klahn posed the question whether German stock returns follow the same pattern. The predictability of German stock returns is the topic of her thesis. She is in a position to identify the relevant variables in the German context. Her basic result is that the driving forces of the German stock market and the U.S. stock market differ in most aspects. According to the Handelsblatt, Judith Klahn's statement is: "Deutscher Aktienmarkt ist kaum mit der Wall Street vergleichbar" (No. 120, June 25, 1999, p. 47).
Download or read book Machine Learning in Asset Pricing written by Stefan Nagel and published by Princeton University Press. This book was released on 2021-05-11 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt: A groundbreaking, authoritative introduction to how machine learning can be applied to asset pricing Investors in financial markets are faced with an abundance of potentially value-relevant information from a wide variety of different sources. In such data-rich, high-dimensional environments, techniques from the rapidly advancing field of machine learning (ML) are well-suited for solving prediction problems. Accordingly, ML methods are quickly becoming part of the toolkit in asset pricing research and quantitative investing. In this book, Stefan Nagel examines the promises and challenges of ML applications in asset pricing. Asset pricing problems are substantially different from the settings for which ML tools were developed originally. To realize the potential of ML methods, they must be adapted for the specific conditions in asset pricing applications. Economic considerations, such as portfolio optimization, absence of near arbitrage, and investor learning can guide the selection and modification of ML tools. Beginning with a brief survey of basic supervised ML methods, Nagel then discusses the application of these techniques in empirical research in asset pricing and shows how they promise to advance the theoretical modeling of financial markets. Machine Learning in Asset Pricing presents the exciting possibilities of using cutting-edge methods in research on financial asset valuation.
Download or read book Essays on the Predictability and Volatility of Returns in the Stock Market written by Ruojun Wu and published by . This book was released on 2008 with total page 137 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation studies the effect of parameter uncertainty on the return predictability and volatility of the stock market. The first two chapters focus on the decomposition of market volatility, and the third chapter studies the return predictability. When facing imperfect information, the investors tend to form a learning scheme that encompasses both historical data and prior beliefs. In the variance decomposition framework, the introducing of learning directly impacts the way that return forecasts are revised and consequently the relative component of market volatility based on these forecasts, namely the price movements from revision on future discount rates and those from future cash flows. According to the empirical study in Chapter 1, the former is not necessarily the major driving force of market volatility, which provides an alternative view on what moves stock prices. Learning is modeled and estimated by Bayesian method. Chapter 2 follows the topic in Chapter 1 and studies the role of persistent state variables in return decomposition in order to provide more robust inference on variance decomposition. In Chapter 3 we propose to utilize theoretical constraints to help predict market returns when in sample data is very noisy and creates model uncertainty for the investors. The constraints are also incorporated by Bayesian method. We show in the out-of-sample forecast experiment that models with theoretical constraints produce better forecasts.
Download or read book The Handbook of Equity Market Anomalies written by Leonard Zacks and published by John Wiley & Sons. This book was released on 2011-08-24 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Investment pioneer Len Zacks presents the latest academic research on how to beat the market using equity anomalies The Handbook of Equity Market Anomalies organizes and summarizes research carried out by hundreds of finance and accounting professors over the last twenty years to identify and measure equity market inefficiencies and provides self-directed individual investors with a framework for incorporating the results of this research into their own investment processes. Edited by Len Zacks, CEO of Zacks Investment Research, and written by leading professors who have performed groundbreaking research on specific anomalies, this book succinctly summarizes the most important anomalies that savvy investors have used for decades to beat the market. Some of the anomalies addressed include the accrual anomaly, net stock anomalies, fundamental anomalies, estimate revisions, changes in and levels of broker recommendations, earnings-per-share surprises, insider trading, price momentum and technical analysis, value and size anomalies, and several seasonal anomalies. This reliable resource also provides insights on how to best use the various anomalies in both market neutral and in long investor portfolios. A treasure trove of investment research and wisdom, the book will save you literally thousands of hours by distilling the essence of twenty years of academic research into eleven clear chapters and providing the framework and conviction to develop market-beating strategies. Strips the academic jargon from the research and highlights the actual returns generated by the anomalies, and documented in the academic literature Provides a theoretical framework within which to understand the concepts of risk adjusted returns and market inefficiencies Anomalies are selected by Len Zacks, a pioneer in the field of investing As the founder of Zacks Investment Research, Len Zacks pioneered the concept of the earnings-per-share surprise in 1982 and developed the Zacks Rank, one of the first anomaly-based stock selection tools. Today, his firm manages U.S. equities for individual and institutional investors and provides investment software and investment data to all types of investors. Now, with his new book, he shows you what it takes to build a quant process to outperform an index based on academically documented market inefficiencies and anomalies.
