"Twitter makes money either through ads or selling information about what people are doing and looking at. However, if Musk successfully makes that case - a big if - he could conceivably persuade a judge to let him walk out of the deal. Musk will have to demonstrate either that Twitter deliberately lied about how many bots it had or that executives suspected they had a bot issue but chose to ignore it, said Shapiro, who predicted that it will be an exceedingly difficult bar to meet. Musk's efforts to pull out hinge on the question of how many bots and fake accounts are on the platform.
"As a basic premise, the Delaware court will want to enforce that merger agreement, and that will be their starting place." Battle over bots "Once you're into the world where you already have the agreement, it's rare for people to try to pull out," said Mathieu Shapiro, managing partner at Obermayer, who specializes in business litigation. Generally, acquisition agreements are exceeedingly difficult to get out of. The social media platform then vowed to challenge Musk in court to uphold the agreement, and has hired powerhouse law firm Wachtell, Lipton, Rosen & Katz in preparation for filing a lawsuit this week in Delaware Court of Chancery, according to Bloomberg.
Translated from the French by Leighton Walter Kille.In announcing he was dropping the deal on Friday, Musk claimed that Twitter refused to provide enough information about the number of fake accounts it has and that Musk's advisors determined the true incidence of bots on the platform is "wildly higher" than Twitter claims. Many methodological and theoretical questions remain unanswered, such as: how can we improve the accuracy of the analysis of the “feeling” of tweets? Is it better to adjust the value assigned to a tweet based on who the sender is? How can we test the “informational” theory using high-frequency data? To decrease the number of “false alarms,” should Twitter signals be combined with other sources of data, such as traditional media or search volumes on Google?įor the moment, however, as the Tweets and Trades study indicates, “picking the right tweets remains just as difficult as making the right trades.”
#Twitter ticker free
Research on this subject is still in its infancy, however, partly because of the lack of free historical data and the technical skills required to extract and analyze this kind of unstructured data. In other words, Twitter is not a crystal ball that can predict markets, but rather a mirror reflecting the current situation. Two recent papers, Tweets and Trades: The Information Content of Stock Microblogs and The Effects of Twitter Sentiment on Stock Price Returns, arrive at essentially the same conclusion: there is a correlation between the “social feeling” for a particular stock and the evolution of financial markets, but not causality. Anthony Quintano/Flickr, CC BY Mixed resultsįor now, as for all research on predicting changes in the price of financial assets by using data from the internet and social networks, the results are rather mixed ( here is a comprehensive review of the literature). The next step is to search for any causal link between the “social feeling” and the evolution of an asset’s prices, correcting for the level of risk.Ī Twitter poster covers the front of the New York Stock Exchange in 2013.
The standard methodology is to extract all tweets containing the name or ticker symbol of a listed company, then algorithmically assign to each message a “feeling” – positive, neutral or negative.Īn aggregate rating is then created using the average of the values assigned to the tweets. A matter of ‘feeling’Īcademic research is currently focused on the second line of research, using Twitter as a proxy for investor sentiment. But there is a profound difference between after-the-fact analysis of a few anecdotal events and the creation of a real-time, profit-generating trading strategy based on Twitter.ĭepending primarily on the number of false alarms generated by a “Twitter strategy” and the speed with which prices are adjusted to reflect new information, the correlation between Twitter and the financial markets can quickly become unusable.
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