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This book explores the relations between objective, media-related, and social attitudinal as well as behavioral realities of private, expert, and corporate agents in the traditions of mass communication, journalism studies and behavioral economics. Results based on time series analyses for German data show that the news reports in a volatile manner on the economy and may influence its development through third-person effects. Bad economic news does not cause a decrease in private purchase intentions. Bad news may lead to a change in corporate decisions, such as advertising expenditures, because corporate decision makers may presume changes in consumer behavior through news.
We assess the impact of media sentiment on international equity prices using more than 4.5 million Reuters articles published across the globe between 1991 and 2015. News sentiment robustly predicts daily returns in both advanced and emerging markets, even after controlling for known determinants of stock prices. But not all news-sentiment is alike. A local (country-specific) increase in news optimism (pessimism) predicts a small and transitory increase (decrease) in local returns. By contrast, changes in global news sentiment have a larger impact on equity returns around the world, which does not reverse in the short run. We also find evidence that news sentiment affects mainly foreign – rather than local – investors: although local news optimism attracts international equity flows for a few days, global news optimism generates a permanent foreign equity inflow. Our results confirm the value of media content in capturing investor sentiment.
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.
An investor's guide to understanding the most elusive (yet most important) aspect of successful investing - yourself. Why is it that the investing performance of so many smart people reliably and predictably falls short? The answer is not that they know too little about the markets. In fact, they know too little about themselves. Combining the latest findings from the academic fields of behavioral finance and experimental psychology with the down-and-dirty real-world wisdom of successful investors, Drs. Richard Peterson and Frank Murtha guide both new and experienced investors through the psychological learning process necessary to achieve their financial goals. In an easy and entertaining style that masks the book’s scientific rigor, the authors make complex scientific insights readily understandable and actionable, shattering a number of investing myths along the way. You will gain understanding of your true investing motivations, learn to avoid the unseen forces that subvert your performance, and build your investor identity - the foundation for long-lasting investing success. Replete with humorous games, insightful self-assessments, entertaining exercises, and concrete planning tools, this book goes beyond mere education. MarketPsych: How to Manage Fear and Build Your Investor Identity functions as a psychological outfitter for your unique investing journey, providing the tools, training and equipment to help you navigate the right paths, stay on them, and see your journey through to success.
Derived from the 2001 Santa Fe Institute Conference, "The Economy as an Evolving Complex System III" addresses a wide variety of issues in the fields of economics and complexity, accessing eclectic techniques from many disciplines, provided that they shed light on the economic problem. The subject, a perennial centerpiece of the SFI program of studies, has gained a wide range of followers for its methods of employing empirical evidence in the development of analytical economic theories.
Developed fifty years ago by the National Bureau of Economic Research, the analytic methods of business cycles and economic indicators enable economists to forecast economic trends by examining the repetitive sequences that occur in business cycles. The methodology has proven to be an inexpensive and useful tool that is now used extensively throughout the world. In recent years, however, significant new developments have emerged in the field of business cycles and economic indicators. This volume contains twenty-two articles by international experts who are working with new and innovative approaches to indicator research. They cover advances in three broad areas of research: the use of new developments in economic theory and time-series analysis to rationalise existing systems of indicators; more appropriate methods to evaluate the forecasting records of leading indicators, particularly of turning point probability; and the development of new indicators.
Handbook of U.S. Consumer Economics presents a deep understanding on key, current topics and a primer on the landscape of contemporary research on the U.S. consumer. This volume reveals new insights into household decision-making on consumption and saving, borrowing and investing, portfolio allocation, demand of professional advice, and retirement choices. Nearly 70% of U.S. gross domestic product is devoted to consumption, making an understanding of the consumer a first order issue in macroeconomics. After all, understanding how households played an important role in the boom and bust cycle that led to the financial crisis and recent great recession is a key metric. - Introduces household finance by examining consumption and borrowing choices - Tackles macro-problems by observing new, original micro-data - Looks into the future of consumer spending by using data, not questionnaires
This book tells the story of how the news media can help the inattentive members of the public become better educated and knowledgeable ‘economic citizens’. The authors argue that changes in the economy, journalism and consumer culture have made economic news more visible, more mainstream and more accessible. They show how economic news not only affects economic perceptions, but also interest in the economy, knowledge about the economy, and economic voting. Relying on statistical analyses, the book provides a comprehensive and systematic study of the effects of economic news.
The Handbook of News Analytics in Finance is a landmarkpublication bringing together the latest models and applications ofNews Analytics for asset pricing, portfolio construction, tradingand risk control. The content of the Hand Book is organised to provide arapid yet comprehensive understanding of this topic. Chapter 1 setsout an overview of News Analytics (NA) with an explanation of thetechnology and applications. The rest of the chapters are presentedin four parts. Part 1 contains an explanation of methods and modelswhich are used to measure and quantify news sentiment. In Part 2the relationship between news events and discovery of abnormalreturns (the elusive alpha) is discussed in detail by the leadingresearchers and industry experts. The material in this part alsocovers potential application of NA to trading and fund management.Part 3 covers the use of quantified news for the purpose ofmonitoring, early diagnostics and risk control. Part 4 is entirelyindustry focused; it contains insights of experts from leadingtechnology (content) vendors. It also contains a discussion oftechnologies and finally a compact directory of content vendor andfinancial analytics companies in the marketplace of NA. Thebook draws equally upon the expertise of academics andpractitioners who have developed these models and is supported bytwo major content vendors - RavenPack and Thomson Reuters - leadingproviders of news analytics software and machine readablenews. The book will appeal to decision makers in the banking, finance andinsurance services industry. In particular: asset managers;quantitative fund managers; hedge fund managers; algorithmictraders; proprietary (program) trading desks; sell-side firms;brokerage houses; risk managers and research departments willbenefit from the unique insights into this new and pertinent areaof financial modelling.