Deconstructing the Reddit’s Meme Stocks Phenomenon
by Vasudha Rajgarhia
Reddit’s WallStreetBets page is infamous for its role in the meteoric price rise of a select basket of the so-called “meme” stocks during the first few months of 2021. Many of these stocks (such as GameStop, AMC, and Blackberry) were known for their distressed financials, deteriorating performances in the market, and incredibly high levels of short interest from large hedge funds who foresaw bankruptcy. However, many retail investors — catalyzed by large stimulus checks, additional time on their hands, and decreasing trading fees from e-brokerages — took advantage of the situation by quickly buying large amounts of shares and options in these select companies, ultimately culminating in a short squeeze.
In response to the incredible turn of events that transpired on WallStreetBets, I was curious about whether Reddit could actually be traced to the multi-billion dollar impact on the stock market. Thus, some of the questions that I attempted to answer through this study are:
1) What do people who search for WallStreetBets also search for?
2) How has sentiment on WallStreetBets developed over 2021?
3) What does the community engagement on Reddit’s WallStreetBets look like? What makes a comment popular versus what makes a comment emotionally charged (and are they the same)?
4) What is the impact of posts and comments on the trading volumes and stock prices of certain meme stocks? And, are they statistically significant?
Community Engagement in Reddit Posts
While the excitement around the meme stocks was originally contained within WallStreetBets, it has now extended well beyond the subreddit to become an object of public inquiry. The graphs below show spikes in Google Search hits for the terms “WallStreetBets” and “GameStop”, with notable surges between January through March of 2021. Though this particular subreddit shot to fame alongside the public’s speculation surrounding GameStop, AMC, and Nokia, the top-20 related topics on Google Trends shows that “WallStreetBets” is increasingly being linked with other popular topics among retail investors, such as “Bitcoin”, “Tesla”, and “Dogecoin” as well. This suggests a externality on the larger financial markets and on non-traditional investments.
High Engagement on Keith Gill’s Reddit Posts
By taking a deeper dive into the content within WallStreetBets, we can see that there is a high level of discussion amongst its members, especially on specific posts by prominent Redditors. For example, Keith Gill, known as “DeepF***nValue” on Reddit, was perhaps the original proponent of the potential GameStop short squeeze — and his posts foster lots of discussion between members. The diagram below displays the Reddit user network surrounding one of Gill’s recent posts, where each dot represents a user who has commented on the post (and in some cases users comment multiple times). The comment highlighted below seems to reassure other users about a company’s stock performance and encourages them to hold on it. The community support — despite some of the negativity — on WallStreetBets could be especially powerful as the certain posts can circulate to reach millions of users on the page.
Sentiment Analysis on Comments of “GameStop,” “AMC,” and “Nokia”
To gauge the intensity and direction of user sentiment on WSB, I conducted a sentiment analysis on posts that mentioned either “GameStop,” “AMC,” or “Nokia.” The intensity of these sentiments is reflected in the minimum and maximum values of the sentiment scores, that range from a low of -20 to a high of approximately 60, while the median and the mean seem to be between 0 to 1.
Based on the graph below, between 28th January 2021 and 29th April 2021, the general user sentiment for these Reddit posts had a clear upward trend with higher variance in the positive direction. The impact of stronger, positive sentiment is amplified if there is an increase in the number of comments as well.
Analyzing Post Content
The rising positive trends in post sentiment on WallStreetBets raise the question of what seems to be the driving force behind the sentiments as well as the number of comments on each post. An analysis of the top 40 words in these posts, in terms of correlation with positive sentiment and number of comments respectively, highlights an interesting dichotomy.
The word-cloud on the left, includes words that had the highest correlation with the most positive posts (i.e. these words represent the content of the most positive posts for GameStop). It highlights words like “services”, “products”, “technology”, and “revenue”, which suggest a favorable viewpoint based on an analysis of the company’s underlying fundamentals. This would indicate that the positive sentiments — at least in part — were based on a proper analysis of the company and its financials and weren’t just the result of community driven excitement for the stock. It also highlights a certain level of sophistication in analysis, which goes against the image of “reddit traders” being whimsical investors.
However, it is important to distinguish between the posts with the highest positive sentiment scores, and posts with the greatest number of comments.
While the most positive posts suggested a depth of analysis, the most commented posts seem to be based on the norms and views of fellow Redditors. Words like “thread”, “post”, “shares”, “discussion”, “yolo”, and “wallstreetbets” stand out in the word-cloud focusing on posts with unusually high number of comments. This seems to suggest that posts with less technical analysis are more engaging in the community. While these posts may not be the most effective in providing a clear investment thesis for GameStop, they are important in making the stock a popular topic for discussion.
Relationships between Total Comments and Stock Price for Nokia
One question I was particularly interested in was to what degree is community engagement on Reddit’s WallStreetBets (among other subreddit pages) responsible for daily change in price in the selected meme stocks. I wanted to see if there was some level of continued correlation between the amount that the stock was discussed on WallStreetBets and the number of shares that were traded on the public markets.
Taking a deep dive into this question, I chose Nokia ($NOK) as the stock I wanted to look into for a few reasons. First, Nokia is listed as a depository stock, which means it is originally listed in Finland but has shares on the NYSE (New York Stock Exchange). This means that — in general — it is slightly harder to trade and therefore the data might be cleaner with regards to market issues like high-frequency trading, large institutional orders, and hedge fund manipulations. Second, Nokia is a large company, with a market capitalization of approximately $20B before the large price fluctuation. By nature, larger companies should be less volatile than smaller companies, and GameStop and AMC were approximately less than $1B each in market capitalization before the Reddit saga.
The graphs above chart the Nokia stock price (USD) as well as the total daily comments for Nokia on WallStreetBets for the same time period. It is interesting to note, that the spike in Nokia’s stock price around late January clearly coincides with the spike in the total daily comments on WSB. Though, this alone doesn’t imply a causal effect, it does suggest a strong connection between the stock price and the amount WSB activity that we can analyze further.
Parsing Effect of Covid and WallStreetBets on Company Performance
Though the stock prices for GameStop, AMC, and Nokia seemed to coincide with activity on WSB, I also factored for the impact of Covid-19 on broader financials market. The pandemic and the resulting lockdowns across the globe led to a dramatic fall in stock prices in March 2020, as economic prospects at the time looked uncertain. However, as the government quickly initiated stimulus plans and employed quantitative easing measures, the market quickly rebounded with almost a “v — shaped” recovery. In order to distinguish between the impact of the WSB forum and that of the pandemic, I charted the stock performance for the largest S&P 500 ETF, “SPY” alongside that of GameStop, AMC, and Nokia for the same time period.
While the SPY ETF seems to have a general upward trend post March 2020, the meme stocks have a weak recovery with a sudden spike around March 2021. Thus, even if the general rise in the meme stock prices can be attributed to general market performance, the spike in early 2021 cannot. Moreover, the spike present in each of the meme stock values, is notably missing from that of the SPY stock performance.
Correlation Analysis
To analyze the statistical impact of WSB posts on a company’s stock performance and daily trading volume, I first established correlation between different variables for GameStop by looking factors like the adjusted daily stock performance and trading volume. In particular, trading volume represents the level of engagement with its stock which is especially crucial for a company like GameStop which was not as actively traded before 2021. In terms of the Reddit variables, the number of comments and the score (equivalent of upvotes) indicates user engagement with the post while the sentiment indicates the direction and intensity of emotion conveyed in the post.
In the correlation plot above, three red asterisks indicate significant correlation at a 0.001 level while a single asterisk indicates significance at the 0.05 level. According to these metrics, both the adjusted stock price and the daily trading volume for GameStop seem to be significantly correlated with variables like the post sentiment, score, and number of comments. Interestingly, the adjusted stock performance and the trading volume have a negative correlation of -0.15 and -0.17 respectively with the post sentiment, this could potentially result from a surge of positive, reinforcing posts when the trading volume or stock price for the stock wavers.
Multiple Regression Analysis
Additionally, I conducted a multiple linear regression on the adjusted stock performance and daily trading volume for GameStop, using the same variables as the correlation. Here I used log of the trading volume to reflect the difference in scale for the values since the volume was represented by much larger numbers as compared to the predicting variables and stock price. Furthermore, to calculate the error rate using the residual standard error I utilized the equation — { sigma(fit)/mean(Y-var)}.
Y-var: Log (Volume)
The first regression analysis, on the left uses log of the trading volume as the predicted variable. Based on this analysis, all three variables of score, number of comments, and sentiment have p-values less than 0.05 indicating they are statistically significant predictors of trading volume. The residual standard error of 0.48 further implies a low error rate of 2.7%. However, the adjusted R-squared value is fairly low at 0.065, meaning the x — variables only explain 6.5% of the variance in GME’s trading volume.
Y-var: Adjusted Price
The second regression analysis used GME’s adjusted stock price as the predicted variable. Here, only the sentiment and score for the posts were statistically significant in predicting GME’s adjusted stock price. The number of comments did not have a statistically significant impact. At the same time, the error rate implied by the residual standard error was fairly high at 55% and its adjusted R-squared value fairly low at 0.028. This would suggest that even though the sentiment and score had favorable p — values less than 0.05, the x-variables don’t account for much of the variance seen in the company’s stock performance.
Also, by studying the linear regression of post sentiment with the adjusted stock price and trading volume, we can further confirm the negative correlation that was seen earlier. This would be an interesting topic for analysis, especially in terms of the causal relationship and how that may impact the stock price in the long term.
A Few Concluding Thoughts
While the WallStreetBets posts seem to have a statistically significant impact on the performance and trading activity of meme stocks like Nokia and GameStop in particular, the extent of their applicability for other stocks and the larger market is still questionable. What is key here is that this community of retail investors has had a significant influence on the financial markets and remains an influential forum of discussion for all investors alike.
Data Sources Used:
1. Kaggle → https://www.kaggle.com/gpreda/reddit-wallstreetsbets-posts
2. Wharton Research Data Services → https://wrds-www.wharton.upenn.edu/query-manager/query/4141266/
