Site icon R-bloggers

Analyzing SPAC Mergers

[This article was first published on R | Data Science Blog, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

(Image taken with license from unsplash, created by Maxim Hopman)

Introduction

In 2020, the stock market welcomed a rise of new retail investors as many found themselves quarantined at home with user-friendly brokerage apps at their fingertips. The recent GameStop short squeeze phenomenon exemplified the growing presence of retail investors and their willingness to gain an edge over the large, institutional funds. An equalizer that achieved mainstream popularity in 2020 was the resurgence of Special-Purpose Acquisition Companies that have cumulatively raised over $80 billion dollars. As a small investor myself, I wanted to research the SPAC market and provide insight for potential investors with everyday retail investors in mind. Through the use of R Shiny, I was able to provide exploratory data analysis and visualization on my ShinyApp.

What is a SPAC?

SPAC is an acronym for a Special-Purpose Acquisition Company. You can think of a SPAC as an empty “shell company” without a business of its own, that exists only to:
  1. Raise money through an Initial Public Offering (IPO)
  2. Find a private, target company
  3. Acquire or merge with the target company to provide them a means to enter the public equity market without the target company going through a traditional IPO themselves
Most Special-Purpose Acquisition Companies IPO with common shares offered at $10 a share. Once the deal is completed with the target company and the acquisition is successful, SPAC shareholders become shareholders of the acquired target company. This provides a golden opportunity for retail investors, as this early opportunity is almost always reserved exclusively for larger, private investors and institutions. For comparison, recent traditional IPOs for Snowflake and Airbnb were priced at $120 and $68 respectively, but began trading at $245 and $146 respectively for the mass market. While the opportunity to be an early investor is a benefit, it also comes with risks for the investors. The target company is unknown, leaving investors at the mercy of the SPAC managers and their ability to find and successfully negotiate with a favorable target company. Time is a factor to consider as well, as most SPACs have a 2-year window to complete its acquisition before being forced to dissolve and return the funds back to its shareholders, or voting to extend the deadline to complete an acquisition. For the target companies, SPACs provide a means to access public equity markets without having to go through an expensive and tedious IPO process. They are also guaranteed the full fund raised by SPAC investors–hundreds of millions, if not billions of dollars–upon the merger, thus eliminating the concern of being unable to raise money from a lackluster IPO.

The Data

I analyzed 71 SPACs and their target companies that completed mergers between January 2020 and January 2021. The list was sourced from spactrack.net, and daily closing prices for each company as well as the market indices used in my comparative analysis were available through Yahoo Finance. The IPO date of the SPACs date range between June 2017 and June 2020.

Data Analysis and Visualization

Historically, SPACs had a stigma as a scam “backdoor IPO.” However, notable companies such as DraftKings and Virgin Galactic have used it as a means to go public in 2020. In analyzing the enterprise valuation of target companies, the average valuation was $2.6 billion dollars, with MultiPlan Corporation receiving the highest valuation at $11 billion. The data disproves the notion that only small companies worthy of investor skepticism need SPAC acquisitions, but that larger, reputable companies are using SPACs to go public as well. The popularity of these SPACs is quantified by the daily trading volume of these 71 companies since their IPO. With each point on the plot representing a daily trade volume amount for each company, you can see the surge in trading volume beginning in the year 2020. Using a word cloud, I was able to visualize the popularity of industries in which SPAC managers were identifying target companies. Tech and fintech were the two most popular industries, with healthcare, financial services, and energy being amongst the other popular industries. While the SPAC managers announced these to be the target industries, the data does not indicate whether their ultimate target company did, in fact, come from said industries. On the ‘Price by Ticker’ tab, the user is able to visualize price movement for a specific company by selecting its ticker symbol. Through this graph, as shown below, you can analyze the stock’s overall movement, as well as compare its pre-merger and post-merger price action highlighted by the different colors.

Example: Danimer Scientific, Inc. (DNMR)

 I wanted to showcase the potential difference because the merger is seen as a monumental day for the stock. Not only does the ticker symbol change to the new target company, but the risk of a failed merger disappears along with the “safety net” of the option for an investor to receive his/her money back at the original IPO price of about $10.  To further visualize the comparison of pre- and post-merger prices, I graphed the average stock price of the 71 companies by the number of days into their pre- and post-merger statuses. I selected day rather than date as a better comparison value. Through this method, we are able to gauge trends of stock movements based on its journey pre-post merger, rather than a specific date which would not provide any insight on how a stock may move on a given day on its SPAC timeline. While pre-merger price consistently stays over the $10 “safety net” option for investors to receive his/her money back at its IPO price, the graph showed the volatility even through the pre-merger stage. At these low prices, a movement of even a dollar or two is very significant, as it can be a double-digit percentage move to either side. The biggest price movement happened around day 190, where the average price drops from $17 to $10. The sharp -40% price movement may indicate a change in investor sentiment on companies that take over 190 days to complete its merger. Post-merger data shows a vast difference in price movement. QuantumScape (QS) was the best-performing stock, with its all-time high at $131.67 a share for 1216% gain from its IPO price. The worst-performing stock was Hall Of Fame Resort & Entertainment (HOFV), with its share price falling to $1.15 a share–an 89% decline from its IPO price. While the median price of $10.09 indicates that stocks generally stay around the IPO price, an investor can see drastic changes to both sides in a short amount of time after the merger.

My SPAC Index

I created my own SPAC index based on these 71 companies beginning in late June, when the last of these 71 companies completed its IPO. My goal here was to compare the performance of this hypothetical SPAC index to the major market indices. Due to the vastly different prices of the indices, I rescaled the stock price range using the min-max normalization process, to scale price movements between a fixed range between 0 and 1, relative to the min and max of each index. When comparing the price movement of the indices, the graph displays a general correlation between the indices to varying degrees. However, I cannot conclude that the movement of the SPAC index is a direct result of the price movements in the other indices. While the SPAC index maintained a positive trend, it has underperformed compared to the rest of the market for the majority of its length. But recently, positive price movement in January 2021 has the SPAC index near its all-time highs and competitive with the other market indices.

Conclusion

Here are key takeaways from my SPAC analysis:
Disclaimer: I am not a financial advisor, and any research provided here should not be construed as personal investment advice. Please conduct your own due diligence before making any investment decisions. Happy investing!
 

Thank you for taking the time to read my research! Please feel free to use the links below to check out my ShinyApp or explore my code on GitHub.

ShinyApp | GitHub

The post Analyzing SPAC Mergers first appeared on Data Science Blog.

To leave a comment for the author, please follow the link and comment on their blog: R | Data Science Blog.

R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.