When Can Social Media Lead Financial Markets?

Zheludev, Ilya; Smith, Robert E.; Aste, Tomaso

doi:10.1038/srep04213

Cited by 106 publications

(85 citation statements)

References 21 publications

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“…The same can be said for [3,4] even if they used different sentiment behaviors that are based on the emotion presented in tweets content. Finally, our results conform with some of the results presented in [17,18] .…”

Section: Resultssupporting

confidence: 81%

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On the Use of Arabic Tweets to Predict Stock Market Changes in the Arab World

Alkhatib¹,

Rabab’ah²,

Al‐Ayyoub³

et al. 2016

ijacsa

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Abstract-Social media users nowadays express their opinions and feelings about many event occurring in their lives. For certain users, some of the most important events are the ones related to the financial markets. An interesting research field emerged over the past decade to study the possible relationship between the fluctuation in the financial markets and the online social media. In this research we present a comprehensive study to identify the relation between Arabic financial-related tweets and the change in stock markets using a set of the most active Arab stock indices. The results show that there is a Granger Causality relation between the volume and sentiment of Arabic tweets and the change in some of the stock markets.

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Section: Resultssupporting

confidence: 81%

“…Zheuldev et al [17] studied the effect of the sentiments presented in Twitter content of the future stock prices of the S&P 500 index. They studied both tweets volume and sentiment presented in tweets at hourly resolution, and related them to hourly price returns of 28 financial companies collected over a period of three months.…”

Section: B Related Workmentioning

confidence: 99%

On the Use of Arabic Tweets to Predict Stock Market Changes in the Arab World

Alkhatib¹,

Rabab’ah²,

Al‐Ayyoub³

et al. 2016

ijacsa

View full text Add to dashboard Cite

show abstract

“…For example some have investigated whether the daily number of tweets predicts SP 500 stock prices [38,39]. A textual analysis approach to Twitter data can be found in other works [15,[40][41][42][43] where the authors find clear relations between mood indicators and Dow Jones Industrial Average. Some other authors have used news, Wikipedia data or search trends to predict market movements [26,[44][45][46].…”

Section: Sentiment Analysismentioning

confidence: 99%

Coupling News Sentiment with Web Browsing Data Improves Prediction of Intra-Day Price Dynamics

et al. 2015

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The new digital revolution of big data is deeply changing our capability of understanding society and forecasting the outcome of many social and economic systems. Unfortunately, information can be very heterogeneous in the importance, relevance, and surprise it conveys, affecting severely the predictive power of semantic and statistical methods. Here we show that the aggregation of web users' behavior can be elicited to overcome this problem in a hard to predict complex system, namely the financial market. Specifically, our in-sample analysis shows that the combined use of sentiment analysis of news and browsing activity of users of Yahoo! Finance greatly helps forecasting intra-day and daily price changes of a set of 100 highly capitalized US stocks traded in the period 2012-2013. Sentiment analysis or browsing activity when taken alone have very small or no predictive power. Conversely, when considering a news signal where in a given time interval we compute the average sentiment of the clicked news, weighted by the number of clicks, we show that for nearly 50% of the companies such signal Granger-causes hourly price returns. Our result indicates a "wisdom-of-the-crowd" effect that allows to exploit users' activity to identify and weigh properly the relevant and surprising news, enhancing considerably the forecasting power of the news sentiment.

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“…This resulted in a series of papers aiming to ascertain whether the content of Twitter -the most relevant social network for such studies -can move the stock market. This stream of research is represented by such works as Sprenger and Wulpe (2010), Ruiz et al (2012), and Zheludev et al (2014). Bollen et al (2010) point out the fact that sentiment has many dimensions and only some of them have predictive power for stock returns.…”

Section: Sentiment Analysis Literaturementioning

confidence: 99%

Can Social Media Content Increase Financial Market Returns? Survey Results from Poland

Cwynar

Pater

2017

Organizacija

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Background and Purpose:In recent years classic financial market theory based on decision makers' rationality has been challenged by repeated anomalies that became a 'new normal'. As a result, what we witness today is a considerable turn to behavioral concepts that can shed a new light on choices made by market participants. The astonishing development of social media accelerated scientific validation of such concepts, since the media opened new and capacious 'laboratory space' for testing behavioral hypotheses. The main purpose of the article is to examine whether financial market professionals believe that social media content can be useful in achieving additional financial market returns and to investigate the factors behind this belief. Design/Methodology/Approach: We surveyed a sample of over 400 financial market professionals at institutions operating in Poland, and analyzed the results using logit regression models. Results: We established that almost 60% of the surveyed finance professionals recognized the potential of social media for achieving additional returns. We also found out that the differences in respondents' perception of this potential could be explained mainly by heterogeneity of their job experience and, to a lesser degree, by their job position. Interestingly, more experienced individuals were less likely to recognize this potential. Firm-specific factors did not have a significant effect on the dependent variable. Conclusion: The opinions of financial market professionals regarding the link between social media and additional returns are mixed, which is consistent with the current body of evidence brought by sentiment-based research. Our findings confirm the key role of previous experience in explaining attitudes towards novelties and innovations (such as social media), a phenomenon known from other fields and everyday experience.

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When Can Social Media Lead Financial Markets?

Cited by 106 publications

References 21 publications

On the Use of Arabic Tweets to Predict Stock Market Changes in the Arab World

On the Use of Arabic Tweets to Predict Stock Market Changes in the Arab World

Coupling News Sentiment with Web Browsing Data Improves Prediction of Intra-Day Price Dynamics

Can Social Media Content Increase Financial Market Returns? Survey Results from Poland

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