Using a unique data set consisting of more than 36.5 million submitted retail investor orders over the course of five years, Matthias Burghardt constructs an innovative retail investor sentiment index. He shows that retail investors’ trading decisions are correlated, that retail investors are contrarians, and that a profitable trading strategy can be based on these aggregated sentiment measures.

In 'Unlocking the Equity Market: Understanding Retail Investor Behavior, Biases, and Their Market-Wide Impacts, ' readers embark on a fascinating exploration of the intricate world of retail investing. This insightful work delves into the psychology and behavior of retail investors, unraveling the biases and decisionmaking processes that shape the equity market. The narrative unfolds as a deep dive into the minds of retail investors, dissecting their behavior and exploring the psychological biases that influence their market interactions. Through comprehensive research and real-world examples, the book illuminates the complexities of investor sentiment, shedding light on how emotions, cognitive biases, and social factors impact trading decisions. Readers are guided through the various cognitive biases that often lead to irrational market behavior, from overconfidence and loss aversion to herding and anchoring. The book emphasizes the profound impact of these biases not only on individual investors but also on market-wide trends, showcasing how collective retail investor behavior can influence stock prices and market volatility. 'Unlocking the Equity Market' serves as a valuable resource for both novice and experienced investors, offering insights into the underlying factors that drive market fluctuations. It equips readers with a deep understanding of retail investor behavior, enabling them to navigate the equity market with a more informed and analytical perspective. As readers delve into the complexities of investor biases, they gain valuable insights that can help them make more rational and strategic investment decisions, unlocking the potential for success in the ever-changing world of equity trading.

The first paper investigates the predictive power of investors' sentiment and attention for the stock returns' volatility. We introduce a novel and extensive dataset that combines information from social media platforms, news articles, search engine data, and information consumption. Applying a state-of-the-art sentiment classification technique, we construct measures of investors' sentiment and attention for 18 U.S. stocks and the financial market in general. We identify investors' attention, as measured by the number of Google searches on financial keywords (e.g. «financial market» and «stock market»), and the daily volume of company-specific short messages posted on the social media platform StockTwits to be the most relevant variables. The second paper investigates a potential driver of the predictive power documented in the first paper. We focus on news releases of 360 U.S. companies from the S&P 500 universe and analyze how investors' attention affects the speed at which new information is incorporated in stock prices. Our results show that higher investors' attention around news releases is related to higher contemporaneous volatility. Further, retail investor attention increases the post-announcement volatility, whereas institutional investor attention has a small but negative impact on volatility on days following news releases. The third paper extends the analysis of the first paper to the multivariate stock return volatility. Building on the theoretical and empirical evidence that links the price comovements with retail investors' behavior, we analyze the predictive power of retail investors' sentiment and attention for the realized correlation matrix of 35 Dow Jones stocks. We propose a new model of realized covariances that allows exogenous predictors to influence the correlation dynamics while ensuring the predicted matrices' positive definiteness. Using this model, we find retail investors' attention to have predictive power for return correlations, especially for longer forecasting horizons and during the COVID-19 pandemic. The last paper analyzes in more detail the time-series properties of the daily online investor sentiment measures used in the first two papers. We detect structural breaks in the sentiment series for most of the 360 U.S. companies considered in this paper. We illustrate the economic significance of this finding with a return prediction exercise.

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.

Dorsey, a publisher of market commentary since 1985, explains market semiotics, his market research philosophy based on the logic of behavioral finance. His proprietary market diagnosis techniques have been described as market expectations theory, behavioral finance, and contrary opinion analysis. Annotation ♭2004 Book News, Inc., Portland, OR (booknews.com).

Using a unique data set with 18.1 million transactions in bank-issued warrants from the European Warrant Exchange, we compute a retail investor sentiment index. We show that retail investors are contrarian, that retail investor sentiment is an important part of the equity pricing process and that we have a good measure of the sentiment. Moreover, our measure is better than existing measures for our sample period between January 2004 and December 2007. In addition, we show evidence that this data may be used for trading strategies that generate excess returns. As a whole our findings further support a role for retail investor sentiment in the equity pricing process.

In recent decades, the financial markets have experienced various crises, shocks and disruptive events, driving high levels of volatility. This volatility is too strong to be fully justified simply by changes in fundamentals. This volume discusses these highly relevant issues with special focus on asset pricing and behavioral finance. Financial price assets of the 2020s appear to be driven by various attractors in addition to fundamentals, and there is no doubt that investor emotions, market sentiment, the news, and external factors such as uncertainty all play a key role. This has been clearly observed in recent years, especially during the ongoing coronavirus pandemic that has changed the common perception of the way financial markets work.