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Author: Melk Bucher
Publisher:
ISBN:
Category :
Languages : en
Pages : 88
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Book Description
Are stocks' varying sensitivies to changing investor attention and sentiment priced? Employing internet search-based proxies for both, I find novel results that are consistent with theory. Stocks that co-vary negatively with increased investor attention to the stock market outperform in the following months in a behavior consistent with a risk premium. The pricing of co-variation with investor sentiment depends on aggregate mispricing (Baker-Wurgler index), behaving like a risk premium when mispricing is low and like an anomaly when mispricing is high. Sensitivity to both sentiment and attention is strongly related to idiosyncratic volatility and limits to arbitrage: High absolute attention/sentiment loadings are associated with higher volatility, smaller size and other limits to arbitrage. However, the priced attention and sentiment components are clearly distinct from the idiosyncratic risk puzzle and stay significant when controlling for relevant pricing factors and company characteristics. Investor attention is both very robust and highly powerful in pricing a broad variety of test assets. On the other hand, investor sentiment's effect on performance is strongly related to return reversal/momentum and does not add much information on its own.
Author: Melk Bucher
Publisher:
ISBN:
Category :
Languages : en
Pages : 88
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Book Description
Are stocks' varying sensitivies to changing investor attention and sentiment priced? Employing internet search-based proxies for both, I find novel results that are consistent with theory. Stocks that co-vary negatively with increased investor attention to the stock market outperform in the following months in a behavior consistent with a risk premium. The pricing of co-variation with investor sentiment depends on aggregate mispricing (Baker-Wurgler index), behaving like a risk premium when mispricing is low and like an anomaly when mispricing is high. Sensitivity to both sentiment and attention is strongly related to idiosyncratic volatility and limits to arbitrage: High absolute attention/sentiment loadings are associated with higher volatility, smaller size and other limits to arbitrage. However, the priced attention and sentiment components are clearly distinct from the idiosyncratic risk puzzle and stay significant when controlling for relevant pricing factors and company characteristics. Investor attention is both very robust and highly powerful in pricing a broad variety of test assets. On the other hand, investor sentiment's effect on performance is strongly related to return reversal/momentum and does not add much information on its own.
Author: Daniele Ballinari
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
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.
Author: Jessica Yichun Wang
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Christian Wey
Publisher:
ISBN: 9783428132577
Category : Germany
Languages : en
Pages : 113
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Book Description
Author: Richard L. Peterson
Publisher: John Wiley & Sons
ISBN: 1119163757
Category : Business & Economics
Languages : en
Pages : 317
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Book Description
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.
Author: Paweł Maryniak
Publisher:
ISBN:
Category :
Languages : en
Pages : 51
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Book Description
Paper analyzes the relationship between the profitability of currency momentum strategy and its potential sources - investor sentiment and investor attention. Evidence supporting the existence of relationship between investor sentiment and currency momentum is presented. It seems that this relationship is different than for equity momentum. Investor sentiment seems to affect in the opposite way long and short leg of currency momentum strategy. It seems that adjusting currency momentum for this relationship can magnify its profitability. Investor attention also seems to have an impact on the profitability of currency momentum which seems to be the most profitable for low attention currencies.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
The aim of the thesis is to create a volatility trading strategy, which relies on investors' attention as a trading signal. In the first part of the thesis its approach and general ideas will be introduced to the reader followed by a detailed overview of existing theories and studies. The main focus of the literature selected is to point out the limited ability of traders to process information and the key factors that influence their attention. Subsequently, a foundation to an own model will be laid by describing how a time series of trend data related to the Google Search Volume Index can approximate investor's sentiment and be used as the first foundation of the study. Option volatility information extracted from the OptionMetrics database will serve as the second data pillar. Specifically, the implied and realized volatility of the NASDAQ and S & P 500 indices will serve as subject of analysis. In a bottom line, the two above data sources will be set in comparison to one another by the means of appropriate statistical tools. The analysis section will lead to the main outcome of the study, namely the development of volatility trading strategy. Finally, I will test my trading strategy as well as check the performance results for robustness.
Author: Larry Harris
Publisher: OUP USA
ISBN: 9780195144703
Category : Business & Economics
Languages : en
Pages : 664
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Book Description
Focusing on market microstructure, Harris (chief economist, U.S. Securities and Exchange Commission) introduces the practices and regulations governing stock trading markets. Writing to be understandable to the lay reader, he examines the structure of trading, puts forward an economic theory of trading, discusses speculative trading strategies, explores liquidity and volatility, and considers the evaluation of trader performance. Annotation (c)2003 Book News, Inc., Portland, OR (booknews.com).
Author: David Bourghelle
Publisher: Springer Nature
ISBN: 3031244869
Category : Business & Economics
Languages : en
Pages : 228
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Book Description
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.
Author: Pedro Piccoli
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
Individual investors are believed to trade on noise. Based on this assumption, this paper investigates whether noisy variables, such as price trends and market sentiment, attract more attention from these investors than value-related information such as the price-earnings ratio. The results suggest that price-earnings dynamics are more important in explaining changes in attention than noisy variables. Moreover, the negative sign exhibited by the value-attention relationship indicates that individual investors are more (less) attentive to stocks when they become cheaper (more expensive). I also demonstrate that this association is more representative during down markets but absent during positive periods, contradicting the stylized fact that retail traders are a driving force of bubbles. Furthermore, I find that these patterns are observable in all G7 countries. Overall, the results do not show that individual investors are consistent proxies for noise traders.
