Download or read book News Sentiment and Stock Returns written by Jonathan Chassot and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Sentiment analysis has been a fast-growing field of study in recent years. Many works have been published on the subject and we have seen different techniques yield impressive results. Sentiment, however, is an abstract concept and there exists no consensus on how to measure it. RavenPack News Analytics (RPNA) is a news sentiment database which has been used in a couple of recent works. This paper focuses on the RavenPack News Analytics database and provides insights on the usefulness of its characteristics. We compare the Granger causality of different measures as well as that of different type of events. We find robust evidence of two less informative event groups, however, most of our results greatly vary based on the estimation set-up and we struggle to identify robust effects in general. The results of this study suggest that stock returns are oftentimes more influenced by sector sentiments than by their own sentiment.
Download or read book Time Varying Relationship of News Sentiment Implied Volatility and Stock Returns written by Lee A. Smales and published by . This book was released on 2016 with total page 23 pages. Available in PDF, EPUB and Kindle. Book excerpt: I examine the relationship between aggregate news sentiment, S&P 500 Index returns, and changes in the implied volatility index (VIX). I find a significant negative contemporaneous relationship between changes in VIX and both news sentiment and stock returns. This relationship is asymmetric whereby changes in VIX are larger following negative news and/or stock market declines. VAR analysis of the dynamics and cross-dependencies between variables reveals a strong positive relationship between previous and current period changes in implied volatility and stock returns, while current period and lagged news sentiment has a significant positive (negative) relationship with stock returns (changes in VIX). I develop a simple trading strategy whereby high (low) levels of implied volatility signal attractive opportunities to take long (short) positions in the underlying index, while extremely negative (positive) news sentiment signals opportunities to enter short (long) index positions.
Download or read book Data Science for Economics and Finance written by Sergio Consoli and published by Springer Nature. This book was released on 2021 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book News and Investor Sentiment written by 許嫣茹 and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book News Versus Sentiment written by Steven L. Heston 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 News Sentiment Factor Models and Abnormal Stock Returns written by Svetlana Borovkova and published by . This book was released on 2015 with total page 11 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper investigates how stock-specific and market-wide news sentiments, obtained from Thomson Reuters News Analytics, affect abnormal returns of S&P 500 stocks. It is well-known that the relationships between the stock-specific news sentiment and raw stock returns are rather weak. This can be explained by the fact that stock returns are driven predominantly by the market factor as well as some other well-known fundamental factors, and in a lesser extent by the idiosyncratic stock-specific information. Using factor models of Fama and French and of Carhart, we remove the influence of the fundamental factors from S&P500 stock returns. This allows us to investigate the relationships between the news sentiment and abnormal, i.e., idiosyncratic component of returns. We use both stock-specific and constructed market-wide sentiments for this purpose.We find that abnormal returns show a strong relationship with the news sentiment, which is consistent across sectors. Moreover, we find that the market-wide news sentiment significantly amplifies the effect of stock-specific news. Furthermore, we investigate separately the effect of news on various sectors, on small, medium and large stocks (in terms of size and book-to-market) and on less and more volatile stocks, and find that there are significant deviations on how abnormal returns react to positive and negative sentiment in news. Since the factor models are fundamentally tradable, our findings can be used to create profitable trading strategies.
Download or read book The Handbook of News Analytics in Finance written by Gautam Mitra and published by John Wiley & Sons. This book was released on 2011-07-13 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Investor Sentiment Stock Returns and Analyst Recommendation Changes written by Karam Kim and published by . This book was released on 2019 with total page 14 pages. Available in PDF, EPUB and Kindle. Book excerpt: This study examines the responses of investor sentiment and stock market returns to announcements of changes in analyst recommendation as well as the effect of these announcements on the relationship between sentiment and stock returns. Investor sentiment is more sensitive to upgrade announcements than to downgrade announcements, implying that news about upgrades reduces information asymmetry among investors. Furthermore, investor sentiment significantly affects the response of stock returns to downgrade announcements because investor sentiment is pessimistic before bad news is released, whereas we do not find a similar result for upgrade announcements.
Download or read book Trading on Sentiment written by Richard L. Peterson and published by John Wiley & Sons. This book was released on 2016-03-21 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: In his debut book on trading psychology, Inside the Investor’s Brain, Richard Peterson demonstrated how managing emotions helps top investors outperform. Now, in Trading on Sentiment, he takes you inside the science of crowd psychology and demonstrates that not only do price patterns exist, but the most predictable ones are rooted in our shared human nature. Peterson’s team developed text analysis engines to mine data - topics, beliefs, and emotions - from social media. Based on that data, they put together a market-neutral social media-based hedge fund that beat the S&P 500 by more than twenty-four percent—through the 2008 financial crisis. In this groundbreaking guide, he shows you how they did it and why it worked. Applying algorithms to social media data opened up an unprecedented world of insight into the elusive patterns of investor sentiment driving repeating market moves. Inside, you gain a privileged look at the media content that moves investors, along with time-tested techniques to make the smart moves—even when it doesn’t feel right. This book digs underneath technicals and fundamentals to explain the primary mover of market prices - the global information flow and how investors react to it. It provides the expert guidance you need to develop a competitive edge, manage risk, and overcome our sometimes-flawed human nature. Learn how traders are using sentiment analysis and statistical tools to extract value from media data in order to: Foresee important price moves using an understanding of how investors process news. Make more profitable investment decisions by identifying when prices are trending, when trends are turning, and when sharp market moves are likely to reverse. Use media sentiment to improve value and momentum investing returns. Avoid the pitfalls of unique price patterns found in commodities, currencies, and during speculative bubbles Trading on Sentiment deepens your understanding of markets and supplies you with the tools and techniques to beat global markets— whether they’re going up, down, or sideways.
Download or read book Media Sentiment and International Asset Prices written by Samuel P. Fraiberger and published by International Monetary Fund. This book was released on 2018-12-10 with total page 33 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Finance for Normal People written by Meir Statman and published by Oxford University Press. This book was released on 2017 with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt: Finance for Normal People teaches behavioral finance to people like you and me - normal people, neither rational nor irrational. We are consumers, savers, investors, and managers - corporate managers, money managers, financial advisers, and all other financial professionals. The book guides us to know our wants-including hope for riches, protection from poverty, caring for family, sincere social responsibility and high social status. It teaches financial facts and human behavior, including making cognitive and emotional shortcuts and avoiding cognitive and emotional errors such as overconfidence, hindsight, exaggerated fear, and unrealistic hope. And it guides us to banish ignorance, gain knowledge, and increase the ratio of smart to foolish behavior on our way to what we want. These lessons of behavioral finance draw on what we know about us-normal people-including our wants, cognition, and emotions. And they draw on the roles of these factors in saving and spending, portfolio construction, returns we can expect from our investments, and whether we can hope to beat the market. Meir Statman, a founder of behavioral finance, draws on his extensive research and the research of many others to build a unified structure of behavioral finance. Its foundation blocks include normal behavior, behavioral portfolio theory, behavioral life-cycle theory, behavioral asset pricing theory, and behavioral market efficiency.
Download or read book Data Mining written by Yue Xu and published by Springer Nature. This book was released on 2021-12-08 with total page 245 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 19th Australasian Conference on Data Mining, AusDM 2021, held in Brisbane, Queensland, Australia, in December 2021.* The 16 revised full papers presented were carefully reviewed and selected from 32 submissions. The papers are organized in sections on research track and application track. *Due to the COVID-19 pandemic the conference was held online.
Download or read book News Sentiment to Market Impact and Its Feedback Effect written by Sheung Yin Mo and published by . This book was released on 2015 with total page 12 pages. Available in PDF, EPUB and Kindle. Book excerpt: Digitization of news articles and the advancement of computational intelligence applications have led to a growing influence of news sentiment over financial markets in recent years. News sentiment has often been used as a proxy for gauging investor's sentiment and reflecting the aggregate confidence of the society toward future market. Previous studies have primarily focused on elucidating the unidirectional impact of news sentiment on market returns and not vice versa. In this study, we document the presence of a significant feedback effect between news sentiment and market returns across the major indices in the U.S. financial market. We find that news sentiment exhibits a lag-4 effect on market returns and conversely market returns elicit consistent lag-1 and lag-2 effects on news sentiment. This aligns well with our intuition that news sentiment drives trading activity and investment decisions. In turn, heightened investment activity further stimulates involuntary responses, which manifest in the form of more news coverage and publications. The evidence presented highlights the strong correlation between news sentiment and market returns, and demonstrates the potential benefits of advancing knowledge in sentiment modeling and its interaction with market movement.
Download or read book A Behavioral Approach to Asset Pricing written by Hersh Shefrin and published by Elsevier. This book was released on 2008-05-19 with total page 636 pages. Available in PDF, EPUB and Kindle. Book excerpt: Behavioral finance is the study of how psychology affects financial decision making and financial markets. It is increasingly becoming the common way of understanding investor behavior and stock market activity. Incorporating the latest research and theory, Shefrin offers both a strong theory and efficient empirical tools that address derivatives, fixed income securities, mean-variance efficient portfolios, and the market portfolio. The book provides a series of examples to illustrate the theory. The second edition continues the tradition of the first edition by being the one and only book to focus completely on how behavioral finance principles affect asset pricing, now with its theory deepened and enriched by a plethora of research since the first edition
Download or read book Stock Return Predictability and Investor Sentiment written by Licheng Sun and published by . This book was released on 2016 with total page 58 pages. Available in PDF, EPUB and Kindle. Book excerpt: We explore the predictive relation between high-frequency investor sentiment and stock market returns. Our results are based on a proprietary dataset of high-frequency investor sentiment, which is computed based on a comprehensive textual analysis of sources from news wires, internet news sources, and social media. We find substantial evidence that intraday S&P 500 index returns are predictable using lagged half-hour investor sentiment. The predictability is evident based on both in-sample and out-of-sample statistical metrics. We document that this sentiment effect is independent of the intraday momentum effect, which is based on lagged half-hour returns. While the intraday momentum effect only exists in the last half hour, the sentiment effect persists in at least the last two hours of a trading day. From an investment perspective, high-frequency investor sentiment also appears to have significant economic value when evaluated with market timing trading strategies.
Download or read book Seeing Through the Spin written by Stine Louise Daetz and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The sentiment of news predicts the short-term stock market performance of individual companies. We find that this association is solely due to the idiosyncratic informational content of an article. We transparently quantify the association between news sentiment and stock market performance of S&P 500 companies, using articles written by Reuters between 2000 and 2018. First, we isolate the effect of sentiment independently of idiosyncratic informational content by exploiting a topicbased shift-share instrument. Second, we show that exogenous variation in article sentiment isolated through our topic-based shiftshare instrument, while strongly related to article sentiment, is unrelated to abnormal returns in the stock market.
Download or read book Machine Learning Sentiment Analysis Covid 19 News and Stock Market Reactions written by Michele Costola and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The possibility to investigate the impact of news on stock prices has observed a strong evolution thanks to the recent use of natural language processing (NLP) in finance and economics. In this paper, we investigate COVID-19 news, elaborated with the "Natural Language Toolkit" that uses machine learning models to extract the news' sentiment. We consider the period from January till June 2020 and analyze 203,886 online articles that deal with the pandemic and that were published on three platforms: MarketWatch.com, Reuters.com and NYtimes.com. Our findings show that there is a significant and positive relationship between sentiment score and market returns. This result indicates that an increase (decrease) in the sentiment score implies a rise in positive (negative) news and corresponds to positive (negative) market returns. We also find that the variance of the sentiments and the volume of the news sources for Reuters and MarketWatch, respectively, are negatively associated to market returns indicating that an increase of the uncertainty of the sentiment and an increase in the arrival of news have an adverse impact on the stock market.
