Download or read book Common Patterns of Predictability in the Cross Section of International Stock Returns written by Steven L. Heston and published by . This book was released on 2007 with total page 35 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper studies the performance of international stock strategies based on historical returns. Stocks that outperform the local market in a particular month continue to outperform the local market in future years in that same calendar month. This effect lasts for 10 years and the same pattern appears in Canada, Japan, and twelve European countries. This return pattern is independent of country, currency effects, and market capitalization. These strategies are not highly correlated across countries; this indicates they do not reflect pervasive international risk. Instead this common seasonal structure in international stocks suggests countries share similar segmented return mechanisms.
Download or read book The Cross section of Stock Returns written by Stijn Claessens and published by World Bank Publications. This book was released on 1995 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Parallels between the Cross Sectional Predictability of Stock and Country Returns written by Clifford S. Asness and published by . This book was released on 1998 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Book-to-market ratio (BE/ME), market equity (ME), and one- year past return (momentum) (MOM) help explain the cross- section of expected individual stock returns within the U.S. and within other countries. Examining equity markets as a whole, in contrast to individual stocks, we uncover strong parallels between the explanatory power of these variables for individual stocks and for countries. First, country versions of BE/ME, ME, and MOM help explain the cross-section of expected country returns. Second, the January seasonal in ME's explanatory power for stocks also appears for countries. Third, portfolios formed by sorting stocks and countries on these variables produce similar patterns in profitability before and after the portfolio formation date.
Download or read book Intraday Patterns in the Cross Section of Stock Returns written by Steven L. Heston and published by . This book was released on 2019 with total page 59 pages. Available in PDF, EPUB and Kindle. Book excerpt: Motivated by the literature on investment flows and optimal trading, we examine intraday predictability in the cross-section of stock returns. We find a striking pattern of return continuation at half-hour intervals that are exact multiples of a trading day, and this effect lasts for at least 40 trading days. Volume, order imbalance, volatility, and bid-ask spreads exhibit similar patterns, but do not explain the return patterns. We also show that short-term return reversal is driven by temporary liquidity imbalances lasting less than an hour and bid-ask bounce. Timing trades can reduce execution costs by the equivalent of the effective spread.
Download or read book Return Predictability written by Julien Penasse 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 Predicting Global Stock Returns written by Erik Hjalmarsson and published by . This book was released on 2008 with total page 60 pages. Available in PDF, EPUB and Kindle. Book excerpt: I test for stock return predictability in the largest and most comprehensive data set analyzed so far, using four common forecasting variables: the dividend- and earnings-price ratios, the short interest rate, and the term spread. The data contain over 20,000 monthly observations from 40 international markets, including 24 developed and 16 emerging economies. In addition, I develop new methods for predictive regressions with panel data. Inference based on the standard fixed effects estimator is shown to suffer from severe size distortions in the typical stock return regression, and an alternative robust estimator is proposed. The empirical results indicate that the short interest rate and the term spread are fairly robust predictors of stock returns in developed markets. In contrast, no strong or consistent evidence of predictability is found when considering the earnings- and dividend-price ratios as predictors.
Download or read book Consumption Habit and International Stock Returns written by Yuming Li and published by . This book was released on 2004 with total page 33 pages. Available in PDF, EPUB and Kindle. Book excerpt: We use the consumption-based asset pricing model with habit formation to study the predictability and cross section of returns from the international equity markets. We find that the predictability of returns from many developed countries' equity markets is explained in part by changing prices of risks associated with consumption relative to habit at the world as well as local levels. We also provide an exploratory investigation of the cross-sectional implications of the model under the complete world market integration hypothesis and find that the model performs mildly better than the traditional consumption-based model, the unconditional and conditional world CAPMs and a three-factor international asset pricing model.
Download or read book International Stock Return Predictability written by Pierre Giot and published by . This book was released on 2016 with total page 65 pages. Available in PDF, EPUB and Kindle. Book excerpt: The predictability of stock returns in ten countries is assessed taking into account recently developed out-of-sample statistical tests and risk-adjusted metrics. Predictive variables include both valuation ratios and interest rate variables. Out-of-sample predictive power is found to be greatest for the short-term and long-term interest rate variables. Given the importance of trading profitability in assessing market efficiency, we show that such statistical predictive power is economically meaningless across countries and investment horizons. All in all, no common pattern of stock return predictability emerges across countries, be it on statistical or economic grounds.
Download or read book Economic Links and Cross predictability of Stock Returns written by Sebastian Müller and published by . This book was released on 2017 with total page 83 pages. Available in PDF, EPUB and Kindle. Book excerpt: Prior research has shown that information diffuses gradually across stocks that are economically linked at the industry level. I document a similar pattern when stock portfolios are formed based on characteristics that are used in the anomaly literature (e.g., size, value, asset growth). Specifically, characteristics are useful to identify economic links, and earnings surprises contain information about future returns of other firms that share similar characteristics (i.e., “similar-style” firms). Such style-based earnings surprises can be used to predict style returns in the time-series. For the cross-section of stocks, I create a composite style-based earnings surprise measure (SESM), which generates an equal-weighted (value-weighted) long-short strategy return of 167 (101) basis points per month. I do not find that industry spillovers, the traditional post-earnings announcement drift, unconditional abnormal style returns, or risk can explain the return predictability. My findings suggest a further channel of gradual information diffusion in security markets.
Download or read book Essays on Predicting and Explaining the Cross Section of Stock Returns written by Xun Zhong and published by . This book was released on 2019 with total page 181 pages. Available in PDF, EPUB and Kindle. Book excerpt: My dissertation consists of three chapters that study various aspects of stock return predictability. In the first chapter, I explore the interplay between the aggregation of information about stock returns and p-hacking. P-hacking refers to the practice of trying out various variables and model specifications until the result appears to be statistically significant, that is, the p-value of the test statistic is below a particular threshold. The standard information aggregation techniques exacerbate p-hacking by increasing the probability of the type I error. I propose an aggregation technique, which is a simple modification of 3PRF/PLS, that has an opposite property: the predictability tests applied to the combined predictor become more conservative in the presence of p-hacking. I quantify the advantages of my approach relative to the standard information aggregation techniques by using simulations. As an illustration, I apply the modified 3PRF/PLS to three sets of return predictors proposed in the literature and find that the forecasting ability of combined predictors in two cases cannot be explained by p-hacking. In the second chapter, I explore whether the stochastic discount factors (SDFs) of five characteristic-based asset pricing models can be explained by a large set of macroeconomic shocks. Characteristic-based factor models are linear models whose risk factors are returns on trading strategies based on firm characteristics. Such models are very popular in finance because of their superior ability to explain the cross-section of expected stock returns, but they are also criticized for their lack of interpretability. Each characteristic-based factor model is uniquely characterized by its SDF. To approximate the SDFs by a comprehensive set of 131 macroeconomic shocks without overfitting, I employ the elastic net regression, which is a machine learning technique. I find that the best combination of macroeconomic shocks can explain only a relatively small part of the variation in the SDFs, and the whole set of macroeconomic shocks approximates the SDFs not better than only few shocks. My findings suggest that behavioral factors and sentiment are important determinants of asset prices. The third chapter investigates whether investors efficiently aggregate analysts' earnings forecasts and whether combinations of the forecasts can predict announcement returns. The traditional consensus forecast of earnings used by academics and practitioners is the simple average of all analysts' earnings forecasts (Naive Consensus). However, this measure ignores that there exists a cross-sectional variation in analysts' forecast accuracy and persistence in such accuracy. I propose a consensus that is an accuracy-weighted average of all analysts' earnings forecasts (Smart Consensus). I find that Smart Consensus is a more accurate predictor of firms' earnings per share (EPS) than Naive Consensus. If investors weight forecasts efficiently according to the analysts' forecast accuracy, the market reaction to earnings announcements should be positively related to the difference between firms' reported earnings and Smart Consensus (Smart Surprise) and should be unrelated to the difference between firms' reported earnings and Naive Consensus (Naive Surprise). However, I find that market reaction to earnings announcements is positively related to both measures. Thus, investors do not aggregate forecasts efficiently. In addition, I find that the market reaction to Smart Surprise is stronger in stocks with higher institutional ownership. A trading strategy based on Expectation Gap, which is the difference between Smart and Naive Consensuses, generates positive risk-adjusted returns in the three-day window around earnings announcements.
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 And Nothing Else Matters On the Dimensionality and Predictability of International Stock Returns written by Heiko Jacobs and published by . This book was released on 2018 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt: We explore the dimensionality of stock returns in North America, Europe, Japan, Pacific, and Emerging Markets on the basis of 240 cross-sectional predictors. Our approach allows us to identify those predictors that are most consistently related to nonmicro-cap stock returns (i.e., independent of other predictors, adjusted for data mining, existent in different time periods, and across regions). There is a large geographic heterogeneity in the significance of individual characteristics and in time trends, which leads to substantial out-of-sample diversification gains for global multidimensional hedge portfolios. Our results are most consistent with the mispricing hypothesis for anomalies.
Download or read book Forecasting Stock Returns in Good and Bad Times written by Dashan Huang and published by . This book was released on 2017 with total page 41 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper proposes a two-state predictive regression model and shows that stock market 12-month return (TMR), the time-series momentum predictor of Moskowitz, Ooi, and Pedersen (2012), forecasts the aggregate stock market negatively in good times and positively in bad times. The out-of-sample R-squares are 0.96% and 1.72% in good and bad times, or 1.28% and 1.41% in NBER economic expansions and recessions, respectively. The TMR predictability pattern holds in the cross-section of U.S. stocks and the international markets. Our study shows that the absence of return predictability in good times, an important finding of recent studies, is largely driven by the use of the popular one-state predictive regression model.
Download or read book Empirical Asset Pricing written by Turan G. Bali and published by John Wiley & Sons. This book was released on 2016-02-26 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: “Bali, Engle, and Murray have produced a highly accessible introduction to the techniques and evidence of modern empirical asset pricing. This book should be read and absorbed by every serious student of the field, academic and professional.” Eugene Fama, Robert R. McCormick Distinguished Service Professor of Finance, University of Chicago and 2013 Nobel Laureate in Economic Sciences “The empirical analysis of the cross-section of stock returns is a monumental achievement of half a century of finance research. Both the established facts and the methods used to discover them have subtle complexities that can mislead casual observers and novice researchers. Bali, Engle, and Murray’s clear and careful guide to these issues provides a firm foundation for future discoveries.” John Campbell, Morton L. and Carole S. Olshan Professor of Economics, Harvard University “Bali, Engle, and Murray provide clear and accessible descriptions of many of the most important empirical techniques and results in asset pricing.” Kenneth R. French, Roth Family Distinguished Professor of Finance, Tuck School of Business, Dartmouth College “This exciting new book presents a thorough review of what we know about the cross-section of stock returns. Given its comprehensive nature, systematic approach, and easy-to-understand language, the book is a valuable resource for any introductory PhD class in empirical asset pricing.” Lubos Pastor, Charles P. McQuaid Professor of Finance, University of Chicago Empirical Asset Pricing: The Cross Section of Stock Returns is a comprehensive overview of the most important findings of empirical asset pricing research. The book begins with thorough expositions of the most prevalent econometric techniques with in-depth discussions of the implementation and interpretation of results illustrated through detailed examples. The second half of the book applies these techniques to demonstrate the most salient patterns observed in stock returns. The phenomena documented form the basis for a range of investment strategies as well as the foundations of contemporary empirical asset pricing research. Empirical Asset Pricing: The Cross Section of Stock Returns also includes: Discussions on the driving forces behind the patterns observed in the stock market An extensive set of results that serve as a reference for practitioners and academics alike Numerous references to both contemporary and foundational research articles Empirical Asset Pricing: The Cross Section of Stock Returns is an ideal textbook for graduate-level courses in asset pricing and portfolio management. The book is also an indispensable reference for researchers and practitioners in finance and economics. Turan G. Bali, PhD, is the Robert Parker Chair Professor of Finance in the McDonough School of Business at Georgetown University. The recipient of the 2014 Jack Treynor prize, he is the coauthor of Mathematical Methods for Finance: Tools for Asset and Risk Management, also published by Wiley. Robert F. Engle, PhD, is the Michael Armellino Professor of Finance in the Stern School of Business at New York University. He is the 2003 Nobel Laureate in Economic Sciences, Director of the New York University Stern Volatility Institute, and co-founding President of the Society for Financial Econometrics. Scott Murray, PhD, is an Assistant Professor in the Department of Finance in the J. Mack Robinson College of Business at Georgia State University. He is the recipient of the 2014 Jack Treynor prize.
Download or read book The Cross Section of Stock Returns written by Stijn Claessens and published by . This book was released on 2016 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt: Several factors besides m ...
Download or read book The Cross Section of Stock Returns Evidence from Emerging Markets written by Susmita Dasgupta and published by . This book was released on 1999 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Predicting International Stock Returns with Conditional Price to Fundamental Ratios written by Jochen Lawrenz and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Taking the perspective of international asset allocation, this paper tests if predictive regressions conditional on time-series and cross-sectional information can improve forecasts of stock index returns. We use different current price-to-fundamental ratios as predictors and condition the sample on the indicator if time-series and cross-section deliver consistent versus opposing signals. Using panel regressions, we find that only consistent ratios (i) display significant mean-reverting behavior, (ii) provide strong in-sample as well as out-of-sample evidence for return predictability, and (iii) yield economic gains in a Bayesian asset allocation framework.
