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  • Can tweets about the stock market be ignored as random noise, generated by

  • self-proclaimed trading gurus?

  • A study by a team of researchers at Rotterdam School of Management, Erasmus University

  • now shows that tweets contain useful information that can be used

  • to predict stock market developments in the short and long term.

  • This discovery may eventually help investors make better decisions.

  • Back to around 2014, The Associated Press Twitter account got hacked

  • and a fake tweet sent out, to say, well, Barack Obama was injured.

  • As a result of this fake tweet the stock market went down for 1% for Dow Jones index.

  • How much is that? More than 100 billion US dollars got swept out.

  • The focal point of this study is actually to find out whether

  • there is additional information we can extract out of social media

  • in order to better predict stock market performance.

  • Perhaps we can extract information that goes

  • above and beyond what has been captured within the public news.

  • At the very beginning we collected about 21 weeks of tweet data and extracted all the

  • information in all the tweets that mentioned a top S&P 100 firm.

  • We had to determine the sentiment being expressed in those tweets:

  • positive, neutral and negative, indicating that some investor

  • wants to buy, keep or sell stocks that they hold for a given company.

  • What we demonstrated is, indeed, based on that Twitter information, with the value extracted out of

  • this tweet information, expressed in sentiment, you can make smarter and

  • better trading strategies and earn excess returns.

  • Even when we take into account the transaction costs, as well as the fixed costs for running this exercise,

  • we can see that there's still excess returns, compared to the market performance.

  • The implication goes way beyond just being in financial industry.

  • A lot of what we do and what we say, both in online and offline environment,

  • has been digitised. We can learn from this digitised human behavior

  • how individuals make their decisions, and also firms can learn from

  • this to make better decisions that can target and also personalise

  • their services and product at the individual level

  • in order to achieve better performance.

Can tweets about the stock market be ignored as random noise, generated by


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B2 中上級

ツイートのビッグデータ分析による株式市場の予測 (Predicting the stock market with big-data analysis of tweets)

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    jenny に公開 2021 年 01 月 14 日