Download or read book Predicting Firm Level Stock Returns written by David G. McMillan and published by . This book was released on 2017 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper examines the predictive ability of several stock price ratios, stock return dispersion and distribution for individual firm level stock returns. Analysis typically focusses on market level returns, however, for the asset pricing model that underlies predictability to hold, firm-level predictability should also be present. In addition, we examine the economic content of predictability by considering whether the predictive coefficient has the theoretically correct sign and whether it is related to future output growth. Movement in stock returns should reflect investor expectations regarding future economic conditions. While stock returns are often too noisy to act as predictors for future economic behaviour, factors that predict stock returns should equally have predictive power for output growth. In our analysis, we use the time-varying predictive coefficient to predict output growth, as the coefficient reflects the sensitivity of stock returns to the predictor variable and thus can be regarded as investors' confidence in the predictive relation. The results suggest that several stock price ratios have predictive power for individual firm stock returns, exhibit the correct coefficient sign and has predictive power for output growth. Each of these ratios has a measure of fundamentals dividend by the stock price and has a positive predictive relation with stock returns and output growth. This implies that as investors expect future economic conditions to improve and earnings and dividends to rise, so expected stock returns will increase. This supports the stock return predictive relation that arises through the cash flow channel.

Download or read book Using Accounting Data to Predict Firm level and Aggregate Stock Returns written by Wei Zhu and published by . This book was released on 2013 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Asymmetric Dependence in Finance written by Jamie Alcock and published by John Wiley & Sons. This book was released on 2018-06-05 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: Avoid downturn vulnerability by managing correlation dependency Asymmetric Dependence in Finance examines the risks and benefits of asset correlation, and provides effective strategies for more profitable portfolio management. Beginning with a thorough explanation of the extent and nature of asymmetric dependence in the financial markets, this book delves into the practical measures fund managers and investors can implement to boost fund performance. From managing asymmetric dependence using Copulas, to mitigating asymmetric dependence risk in real estate, credit and CTA markets, the discussion presents a coherent survey of the state-of-the-art tools available for measuring and managing this difficult but critical issue. Many funds suffered significant losses during recent downturns, despite having a seemingly well-diversified portfolio. Empirical evidence shows that the relation between assets is much richer than previously thought, and correlation between returns is dependent on the state of the market; this book explains this asymmetric dependence and provides authoritative guidance on mitigating the risks. Examine an options-based approach to limiting your portfolio's downside risk Manage asymmetric dependence in larger portfolios and alternate asset classes Get up to speed on alternative portfolio performance management methods Improve fund performance by applying appropriate models and quantitative techniques Correlations between assets increase markedly during market downturns, leading to diversification failure at the very moment it is needed most. The 2008 Global Financial Crisis and the 2006 hedge-fund crisis provide vivid examples, and many investors still bear the scars of heavy losses from their well-managed, well-diversified portfolios. Asymmetric Dependence in Finance shows you what went wrong, and how it can be corrected and managed before the next big threat using the latest methods and models from leading research in quantitative finance.

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 Firm level Risk Exposures and Stock Returns in the Wake of COVID 19 written by Steven J. Davis and published by . This book was released on 2020 with total page 80 pages. Available in PDF, EPUB and Kindle. Book excerpt: Firm-level stock returns differ enormously in reaction to COVID-19 news. We characterize these reactions using the Risk Factors discussions in pre-pandemic 10-K filings and two text-analytic approaches: expert-curated dictionaries and supervised machine learning (ML). Bad COVID-19 news lowers returns for firms with high exposures to travel, traditional retail, aircraft production and energy supply -- directly and via downstream demand linkages -- and raises them for firms with high exposures to healthcare policy, e-commerce, web services, drug trials and materials that feed into supply chains for semiconductors, cloud computing and telecommunications. Monetary and fiscal policy responses to the pandemic strongly impact firm-level returns as well, but differently than pandemic news. Despite methodological differences, dictionary and ML approaches yield remarkably congruent return predictions. Importantly though, ML operates on a vastly larger feature space, yielding richer characterizations of risk exposures and outperforming the dictionary approach in goodness-of-fit. By integrating elements of both approaches, we uncover new risk factors and sharpen our explanations for firm-level returns. To illustrate the broader utility of our methods, we also apply them to explain firm-level returns in reaction to the March 2020 Super Tuesday election results.

Download or read book Growth Or Glamour written by John Y. Campbell and published by . This book was released on 2005 with total page 66 pages. Available in PDF, EPUB and Kindle. Book excerpt: The cash flows of growth stocks are particularly sensitive to temporary movements in aggregate stock prices (driven by movements in the equity risk premium), while the cash flows of value stocks are particularly sensitive to permanent movements in aggregate stock prices (driven by market-wide shocks to cash flows.) Thus the high betas of growth stocks with the market's discount-rate shocks, and of value stocks with the market's cash-flow shocks, are determined by the cash-flow fundamentals of growth and value companies. Growth stocks are not merely "glamour stocks" whose systematic risks are purely driven by investor sentiment. More generally, accounting measures of firm-level risk have predictive power for firms' betas with market-wide cash flows, and this predictive power arises from the behavior of firms' cash flows. The systematic risks of stocks with similar accounting characteristics are primarily driven by the systematic risks of their fundamentals.

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 Returns and Volatility written by Gregory R. Duffee and published by . This book was released on 2001 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: It has been previously documented that individual firms' stock return volatility rises after stock prices fall. This paper finds that this statistical relation is largely due to a positive contemporaneous relation between firm stock returns and firm stock return volatility. This positive relation is strongest for both small firms and firms with little financial leverage. At the aggregate level, the sign of this contemporaneous relation is reversed. The reasons for the difference between the aggregate- and firm-level relations are explored.

Download or read book Predicting Stock Returns Using Industry Relative Firm Characteristics written by Clifford S. Asness and published by . This book was released on 2000 with total page 46 pages. Available in PDF, EPUB and Kindle. Book excerpt: Better proxies for the information about future returns contained in firm characteristics such as size, book-to-market equity, cash flow-to-price, percent change in employees, and various past return measures are obtained by breaking these explanatory variables into two industry-related components. The components represent (1) the difference between firms' own characteristics and the average characteristics of their industries (within-industry variables), and (2) the average characteristics of firms' industries (across-industry variables). Each variable is reliably priced within-industry and measuring the variables within-industry produces more precise estimates than measuring the variables in their more common form. Contrary to Moskowitz and Grinblatt [1999], we find that within-industry momentum (i.e., the firm's past return less the industry average return) has predictive power for the firm's stock return beyond that captured by across-industry momentum. We also document a significant short-term (one-month) industry momentum effect which remains strongly significant when we restrict the sample to only the most liquid firms.

Download or read book Predicting Stock Returns with Firm Characteristics by Machine Learning Techniques written by Shihao Gu and published by . This book was released on 2017 with total page 39 pages. Available in PDF, EPUB and Kindle. Book excerpt: We propose multiple advanced learning methods to deal with the "curse of dimensionality" challenge in the cross-sectional stock returns. Our purpose is to predict the one-month-ahead stock returns by the rm characteristics which are so-called "anomalies". Compared with the traditional methods like portfolio sorting and Fama Factor models, we focus on using all existing machine learning methods to do the prediction rather than the explanation. To alleviate the concern of excessive data mining, we use several regularization penalties that can lead to a sparse and robust model. Our method can identify the return predictors with incremental pricing information and learn the interaction effects by applying to a hierarchical structure. Our best method can achieve much higher out of sample R2 and portfolio Sharp Ratios than traditional linear regression method.

Download or read book Measuring Capital in the New Economy written by Carol Corrado and published by University of Chicago Press. This book was released on 2009-02-15 with total page 602 pages. Available in PDF, EPUB and Kindle. Book excerpt: As the accelerated technological advances of the past two decades continue to reshape the United States' economy, intangible assets and high-technology investments are taking larger roles. These developments have raised a number of concerns, such as: how do we measure intangible assets? Are we accurately appraising newer, high-technology capital? The answers to these questions have broad implications for the assessment of the economy's growth over the long term, for the pace of technological advancement in the economy, and for estimates of the nation's wealth. In Measuring Capital in the New Economy, Carol Corrado, John Haltiwanger, Daniel Sichel, and a host of distinguished collaborators offer new approaches for measuring capital in an economy that is increasingly dominated by high-technology capital and intangible assets. As the contributors show, high-tech capital and intangible assets affect the economy in ways that are notoriously difficult to appraise. In this detailed and thorough analysis of the problem and its solutions, the contributors study the nature of these relationships and provide guidance as to what factors should be included in calculations of different types of capital for economists, policymakers, and the financial and accounting communities alike.

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 A Theory of Firm Characteristics and Stock Returns The Role of Investment Specific Shocks written by and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Forecasting Skewness in Stock Returns written by Mariko Fujii and published by . This book was released on 2006 with total page 76 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book When Does Short Interest Predict Stock Returns Evidence Around the Business Cycle written by Peter Dixon and published by . This book was released on 2018 with total page 55 pages. Available in PDF, EPUB and Kindle. Book excerpt: We explore business cycle variation in the relation between short interest and future stock returns. During economic expansions, firm-level short interest is a strong negative predictor of the cross-section of stock returns. In contrast, during recessions, short interest aggregated across firms is a strong negative predictor of future market returns. These findings are consistent with Kacperczyk, Van Nieuwerburgh, and Veldkamp's (2016) model in which rational yet cognitively constrained traders collect aggregate (firm-specific) information in recessions (expansions) because these times are marked by higher (lower) aggregate volatility and price of risk.

Download or read book What Drives Firm level Stock Returns written by Tuomo Vuolteenaho and published by . This book was released on 2001 with total page 22 pages. Available in PDF, EPUB and Kindle. Book excerpt: I use a vector autoregressive model (VAR) to decompose an individual firm's stock return into two components: changes in cash-flow expectations (i.e., cash-flow news) and changes in discount rates (i.e., expected-return news). The VAR yields three main results. First, firm-level stock returns are mainly driven by cash-flow news. For a typical stock, the variance of cash-flow news is more than twice that of expected-return news. Second, shocks to expected returns and cash flows are positively correlated for a typical small stock. Third, expected-return-news series are highly correlated across firms, while cash-flow news can largely be diversified away in aggregate portfolios

Download or read book Real Options Volatility and Stock Returns written by Gustavo Grullon and published by . This book was released on 2013 with total page 49 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper provides evidence that the positive relation between firm-level stock returns and firm-level return volatility is due to real options that firms possess. Consistent with the theoretical prediction that the value of a real option should be increasing in the volatility of the underlying asset, we find that the positive volatility-return relation is much stronger for firms that are more likely to have more real options. We also find that the sensitivity of firm values to changes in volatility declines significantly after firms exercise their real options. Finally, we reconcile the aggregate-level evidence of a negative relation between returns and return volatility with the positive relation at the firm level by showing that the negative relation at the aggregate level may be due to aggregate market conditions that simultaneously affect both market returns and return volatility.