In March, we introduced a statistic to enhance our StockTwits S-Score signal called the Bayesian...
In the financial world, the biggest trending topic over the past few days has been the unexpected resurgence of the famed Reddit trading influencer, "Roaring Kitty." Known for his pivotal role in the 2021 GameStop stock saga, Roaring Kitty once again captured the internet's attention. Back then, he led a vast online community to buy these stocks, causing their prices to skyrocket in a dramatic move against hedge funds that were shorting them. On Sunday Night, Roaring Kitty posted again, sparking a similar chain reaction.
In this blog, we delve into how Twitter sentiment data from Context Analytics anticipated this movement before the significant price surges in GameStop and AMC. We'll explore the mechanics of our proprietary tools—S-Score and S-Volume—and demonstrate their predictive power through minute-by-minute analysis.
Our analysis begins with GameStop. By overlaying our patented S-Score, S-Volume, and the GameStop price, we created an intricate view of the market's sentiment and behavior in real-time.
- Sunday Night, May 12th, 11:32 PM: Our S-Score crossed the >2 threshold, indicating a very positive sentiment on Twitter. This occurs a few hours after Roaring Kitty’s post. S-Volume increased from 36 to 227 from the time of his post to the time GME’s S-Score crossed above 2.
- Monday Morning, May 13th, 9:26 AM: The S-Score then crossed the >4 threshold, signaling an extremely positive sentiment. GME price was at $26.37 and S-Volume increased to 855.
These thresholds were breached well before the notable price movements. As evidenced in our data, GameStop saw a price increase of over 40% during this period. The chart below illustrates how the S-Score and S-Volume, which measures the number of tweets about the stock, aligned with the stock price.
AMC exhibited a similar pattern.
- Monday Morning, 7:19 AM: Our S-Score surpassed the >2 threshold, marking the beginning of a positive sentiment spike.
- Monday Morning, 11:09 AM: The S-Score then spiked past 4, reflecting extremely positive sentiment.
Interestingly, during a minor price drop between 6-7 AM, our S-Score continued to rise. This persistent positive sentiment foreshadowed the significant price increases that followed.
This case study underscores the predictive power of our social sentiment analytics. By leveraging alerts and tracking longer-term sentiment trends, we can stay ahead of mass influencer movements. As social media continues to grow, these market-shifting events will become more frequent. At Context Analytics, we lead the way in harnessing the power of social sentiment. For more information, click the button below or email us at ContactUs@ContextAnalytics-ai.com .
