Earlier this year, Elon Musk tweeted that the Tesla stock price is too high. His twitter account had a reach of 33.4 million followers (41 million as of this writing). The immediate impact on Tesla’s stock price was a midday trading deficit of 9% compared to the closing stock price of the previous day. Tesla’s company valuation suffered an estimated loss of $14 billion. The episode triggered concerns over a potential violation of his 2018 settlement with the Securities and Exchange Commission after misleading tweets implying to have raised sufficient capital to take Tesla private. Presumably this time it was in response to California’s restrictive shelter-in-place lockdown measures to tackle the coronavirus pandemic. Maybe Elon Musk felt the weight of his responsibilities weigh twice as much during these challenging times. In any case, as an investor, his actions made me think of the power of social media at the hands of a social media influencer (i.e. stock promoter). Moreover, it made me think about content policies tailored to protect economic value while safeguarding information integrity. This empirical study conducted by researchers of the Pantheon-Sorbonne University discusses effects of illegal price manipulation by way of information operations on social media, specifically Twitter.
tl;dr
Social media can help investors gather and share information about stock markets. However, it also presents opportunities for fraudsters to spread false or misleading statements in the marketplace. Analyzing millions of messages sent on the social media platform Twitter about small capitalization firms, we find that an abnormally high number of messages on social media is associated with a large price increase on the event day and followed by a sharp price reversal over the next trading week. Examining users’ characteristics, and controlling for lagged abnormal returns, press releases, tweets sentiment and firms’ characteristics, we find that the price reversal pattern is stronger when the events are generated by the tweeting activity of stock promoters or by the tweeting activity of accounts dedicated to tracking pump-and-dump schemes. Overall, our findings are consistent with the patterns of a pump-and-dump scheme, where fraudsters/promoters use social media to temporarily inflate the price of small capitalization stocks.
Make sure to read the full paper titled Market Manipulation and Suspicious Stock Recommendations on Social Media by Thomas Renault at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3010850
Social media platforms are an accepted corporate communication channel nowadays closely monitored by investors and financial analysts. As an investor, social media offers swarm intelligence on trading the company’s stock, access to real-time information about the company, product updates and other financially relevant information. Large and small-cap companies usually maintain a presence on social media. Although in particular small-cap companies with low liquidity are vulnerable to stock price manipulations by way of information operations on social media. According to researchers of the Pantheon-Sorbonne University an information-based manipulation involves rumors, misleading or false press releases, stock analysis or price targets, etc. that is disseminated in a short, time-sensitive period. Nearly 50% of this disinformation is spread by an influencer. The investment terminology calls this pump-and-dump scheme:
“Pump-and-dump schemes involve touting a company’s stock through false or misleading statements in the marketplace in order to artificially inflate (pump) the price of a stock. Once fraudsters stop hyping the stock and sell their shares (dump), the price typically falls.”
The empirical study collected tweets containing the cashtag ticker symbol of more than 5000 small-cap companies. Over an eleven-month period 248,748 distinct Twitter users posted 7,196,307 financially relevant tweets. They adjusted the data for overoptimistic noise traders and financially relevant news reporting. They found a spike in volume of tweets concerning a company’s stock on social media correlates with a spike in trading of the company’s stock from two days before peak activity on social media up to five days after it. Some content concerned positive financial signals advocating to buy the stock. Other content concerned disinformation about the company’s performance. It was spread to a large, unsophisticated Twitter audience by influencer in concert with a network of inauthentic accounts and bots. This was then followed by a price reversal over the ensuing trading days. In the aftermath, the actors part of the scheme went into hibernation or ceased social media activity altogether.
Risk And Opportunity For Social Media Platforms
Information operations to manipulate stock price are quite common on social media. Albeit hard to detect only few are investigated and successfully prosecuted. Consumers exposed to stock disinformation that fell victim tend to exit the stock market altogether. Moreover a consumer might reduce their footprint on social media after experiencing real-world financial harm. Depending on the severity of the loss incurred, this might even lead to litigation against social media platforms. The tools leveraged by bad actors undermine the integrity efforts of social media platforms, which in some cases or in conjunction with class-action litigation can lead to greater scrutiny by financial watchdogs pushing for tighter regulations.
To tackle these risks social media platforms must continue to expand enforcement of inauthentic coordinated behavior to eliminate botnetworks used to spread stock disinformation. Developing an account verification system that is dedicated to financial professionals, analysts and influencers will support and ease enforcement. Social media platforms should also ease onboarding of publicly traded companies to maintain a presence on social media. This decreases the effects of collateral price reversals. In order to mitigate stock disinformation social media platforms must develop content policies tailored to balance freedom of expression including price speculation with the inherent risk of market-making comments. The latter will hinge on reach and engagement metrics but also on detailed definitions of financial advice and time and location of the content. Here, a close working-relationship with watchdogs will improve operations. Added friction, for example an interstitial outlining the regulatory requirements before posting or a delayed time of posting or certain labels informing the consumer of the financial risks associated with acting on the information in the posting. There are obviously more measures that come to mind. This only serves as a start of a conversation.
So, was Elon Musk’s tweet “Tesla stock price too high imo” an information-based market manipulation, a market-making comment or just an exercise of his free speech?
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