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Stock market overreacts to both anticipated and unanticipated stock-specific news. In spite of any firm-specific news, evidences of extreme price changes have been observed in the stock market. Significant abnormal returns are found in the opposite direction indicating the existence of an overreaction effect. It is also found that the magnitude of reversal is inversely proportional to the event-period stock returns. The overreaction effect continues only about two days after the event date for this present sample. Thus, the ultimate understanding of overreaction effects in preparing trading strategies will perk up investors' returns. Changes in beta are found more statistically significant where the most learning is possible, like in the case of more earnings surprise (good or bad news), smaller firms, higher amount of volatility or uncertainty, or announcements that come early rather than late in the announcement season.
We investigate whether the betas of individual stocks vary with the release of firm-specific news. Using daily firm-level betas estimated from intra-day prices for all constituents of the Samp;P 500 index, we find that the betas of individual stocks increase by an economically and statistically significant amount on days of quarterly earnings announcements, and revert to their average levels two to five days later. The increase in betas is greater for earnings announcements with larger positive or negative earnings surprises, for announcements that convey more information about other firms in the market, and for announcements that resolve greater ex-ante uncertainty. Our empirical results are all consistent with a simple learning model in which investors use information on announcing firms to revise their expectations about the profitability of the aggregate economy.
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.
The past twenty years have seen an extraordinary growth in the use of quantitative methods in financial markets. Finance professionals now routinely use sophisticated statistical techniques in portfolio management, proprietary trading, risk management, financial consulting, and securities regulation. This graduate-level textbook is intended for PhD students, advanced MBA students, and industry professionals interested in the econometrics of financial modeling. The book covers the entire spectrum of empirical finance, including: the predictability of asset returns, tests of the Random Walk Hypothesis, the microstructure of securities markets, event analysis, the Capital Asset Pricing Model and the Arbitrage Pricing Theory, the term structure of interest rates, dynamic models of economic equilibrium, and nonlinear financial models such as ARCH, neural networks, statistical fractals, and chaos theory. Each chapter develops statistical techniques within the context of a particular financial application. This exciting new text contains a unique and accessible combination of theory and practice, bringing state-of-the-art statistical techniques to the forefront of financial applications. Each chapter also includes a discussion of recent empirical evidence, for example, the rejection of the Random Walk Hypothesis, as well as problems designed to help readers incorporate what they have read into their own applications.
The IMF's 2012 Annual Report chronicles the response of the Fund's Executive Board and staff to the global financial crisis and other events during financial year 2012, which covers the period from May 1, 2011, through April 30, 2012. The print version of the Report is available in eight languages (Arabic, Chinese, English, French, German, Japanese, Russian, and Spanish), along with a CD-ROM (available in English only) that includes the Report text and ancillary materials, including the Fund's Financial Statements for FY2012.
We investigate how corporate stock returns respond to geopolitical risk in the case of South Korea, which has experienced large and unpredictable geopolitical swings that originate from North Korea. To do so, a monthly index of geopolitical risk from North Korea (the GPRNK index) is constructed using automated keyword searches in South Korean media. The GPRNK index, designed to capture both upside and downside risk, corroborates that geopolitical risk sharply increases with the occurrence of nuclear tests, missile launches, or military confrontations, and decreases significantly around the times of summit meetings or multilateral talks. Using firm-level data, we find that heightened geopolitical risk reduces stock returns, and that the reductions in stock returns are greater especially for large firms, firms with a higher share of domestic investors, and for firms with a higher ratio of fixed assets to total assets. These results suggest that international portfolio diversification and investment irreversibility are important channels through which geopolitical risk affects stock returns.
This review lays out a research perspective on earnings quality. We provide an overview of alternative definitions and measures of earnings quality and a discussion of research design choices encountered in earnings quality research. Throughout, we focus on a capital markets setting, as opposed, for example, to a contracting or stewardship setting. Our reason for this choice stems from the view that the capital market uses of accounting information are fundamental, in the sense of providing a basis for other uses, such as stewardship. Because resource allocations are ex ante decisions while contracting/stewardship assessments are ex post evaluations of outcomes, evidence on whether, how and to what degree earnings quality influences capital market resource allocation decisions is fundamental to understanding why and how accounting matters to investors and others, including those charged with stewardship responsibilities. Demonstrating a link between earnings quality and, for example, the costs of equity and debt capital implies a basic economic role in capital allocation decisions for accounting information; this role has only recently been documented in the accounting literature. We focus on how the precision of financial information in capturing one or more underlying valuation-relevant constructs affects the assessment and use of that information by capital market participants. We emphasize that the choice of constructs to be measured is typically contextual. Our main focus is on the precision of earnings, which we view as a summary indicator of the overall quality of financial reporting. Our intent in discussing research that evaluates the capital market effects of earnings quality is both to stimulate further research in this area and to encourage research on related topics, including, for example, the role of earnings quality in contracting and stewardship.
This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some successful applications of advanced data science solutions used to extract new knowledge from data in order to improve economic forecasting models. The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis. This book is relevant to all stakeholders involved in digital and data-intensive research in economics and finance, helping them to understand the main opportunities and challenges, become familiar with the latest methodological findings, and learn how to use and evaluate the performances of novel tools and frameworks. It primarily targets data scientists and business analysts exploiting data science technologies, and it will also be a useful resource to research students in disciplines and courses related to these topics. Overall, readers will learn modern and effective data science solutions to create tangible innovations for economic and financial applications.
Judging by the sheer number of papers reviewed in this Handbook, the empirical analysis of firms’ financing and investment decisions—empirical corporate finance—has become a dominant field in financial economics. The growing interest in everything “corporate is fueled by a healthy combination of fundamental theoretical developments and recent widespread access to large transactional data bases. A less scientific—but nevertheless important—source of inspiration is a growing awareness of the important social implications of corporate behavior and governance. This Handbook takes stock of the main empirical findings to date across an unprecedented spectrum of corporate finance issues, ranging from econometric methodology, to raising capital and capital structure choice, and to managerial incentives and corporate investment behavior. The surveys are written by leading empirical researchers that remain active in their respective areas of interest. With few exceptions, the writing style makes the chapters accessible to industry practitioners. For doctoral students and seasoned academics, the surveys offer dense roadmaps into the empirical research landscape and provide suggestions for future work. *The Handbooks in Finance series offers a broad group of outstanding volumes in various areas of finance *Each individual volume in the series should present an accurate self-contained survey of a sub-field of finance *The series is international in scope with contributions from field leaders the world over