As already mentioned, we have data on 180 venture-backed IPOs, dating back to 2011.
The companies raised a median of $111.2 million in their offerings, and raised $140.0 million in pre-IPO funding. The median age of the companies when they filed for IPO was 10.9 years, 22.8% of the companies in the dataset were profitable the year before their IPO, and 31.1% were tech companies. Table 4.1 displays annual averages of these metrics, where average offer sizes and pre-IPO funding amounts are adjusted for inflation.
There are no clear historical trends, perhaps with the exception of profitability the year before IPO, although the lowest observations are in the middle of the time frame. This is likely as a result of the narrow time frame in scope, as previous research has shown that companies going public today are in general older, larger and to a lesser extent profitable compared to companies that went public a few decades ago (Ritter, 2018).
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Table 4.1: Descriptive Statistics, by Year
Year Number
2011 7 152.4 366.5 12.3 42.9% 42.9%
2012 7 82.0 133.2 7.6 57.1% 28.6%
2013 33 112.6 147.5 8.4 36.4% 18.2%
2014 45 106.1 113.4 9.3 22.4% 31.1%
2015 21 107.9 112.3 9.5 4.8% 33.3%
2016 12 95.0 146.3 8.4 8.3% 25.0%
2017 22 111.3 122.4 10.7 22.7% 45.5%
2018 18 177.3 174.5 8.5 11.1% 33.3%
2019 15 175.8 1 166.2 9.3 13.3% 33.3%
Total 180 111.2 140.0 10.0 22.8% 31.1%
With regards to potential selection bias, these figures are roughly in line with previous statistics. Ritter (2018) examined 834 VC-backed IPOs from between 2011 and 2017 and found the median age to be between 10 and 12 for each of these years. Similarly to our dataset, he also found the percentage of companies that were profitable when going public to vary significantly, ranging from 16% to 64%. A likely explanation for why his numbers are higher than ours is that Ritter measured profitability the year of IPO rather than the year before, giving the companies more time to achieve profitability. Concerning offering size, Renaissance Capital3, a company providing pre-IPO institutional research, reported in 2018 annual median offer sizes of US IPOs to be slightly lower than those in our dataset.
Contrary to us, however, Renaissance Capital do not single out VC-backed IPOs. Before removing non-backed IPOs from our dataset, we saw that they were on average smaller than backed IPOs. For tech status and pre-IPO funding, we have not found any data that could be used to validate our dataset against selection bias. Considering that the other attributes are aligned with comparable datasets, there is nonetheless reason to believe that our dataset is free of selection bias.
3Not to be confused with Renaissance Technologies, the hedge fund
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Returns
Calculated from the offer price, the median return for the IPOs in the dataset (table 4.2) was 17.7% on the first day of trading, and 29.7% after three months. However, when the first day of trading is excluded, the median return is lower, 7.4%. Although weak, the trend seems to be that average first-day return has increased over the observed period.
Table 4.2: Average Simple Returns
Year 1 Day 3 Months, Including
First Day of Trading 3 Months, Excluding First Day of Trading
Figure 4.1 shows the distribution of first-day trading gains of the IPOs in our dataset. It is evident that most companies filing for IPO experience an appreciation in their share price compared to the offer price of the IPO. This is in line with the phenomenon of underpricing, as discussed in the literature review. On the negative end, the most extreme observation in the dataset is Chegg Inc., who experienced a share price decline of 23% on their first day of trading. On the positive of the scale is Beyond Meat, the producer of plant-based meat substitutes whose share price rose by 163% on their first day of trading in May 2019. This was the best first-day performance of a US IPO larger than $200 million since the dot-com boom (Murphy, 2019).
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Figure 4.1: Distribution of First-Day Simple Returns
When looking at the three-month horizon, the distribution is more spread out across the axis, as illustrated in figure 4.2. Also here, Beyond Meat is on the far right. Even after their remarkable price increase at the day of IPO, the Beyond Meat stock continued to rise, tripling in value over the next three months of trading - totalling a value increase of 686.0% from their offer price. At the other end of the axis is Castlight Health, a San Francisco-based healthcare navigation company who experienced a stock price depreciation of 57.6% in the three months following their IPO in March 2014.
Figure 4.2: Distribution of Simple Returns Three Months After IPO
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Industries
By using the EU industry standards classification system (NACE) code of each company, we can investigate whether there are patterns to be found when dividing companies by industry. NACE divides companies into 21 broad sections. The top three most represented sections in our dataset are Manufacturing (65 IPOs), Information and Communication (56 IPOs), and Professional Scientific and Technical Activities (33 IPOs), leaving 26 IPOs
in other sections. This distribution is visualized in figure 4.3.
Figure 4.3: Distribution of Dataset
Within the Manufacturing section, 32 out of 65 companies are manufacturers of pharmaceutical preparations (NACE code 21.20), 11 are manufacturers of medical and dental instruments and supplies (code 32.50), and 9 are manufacturers of electronic components (code 26.11).
Within the Information and Communication section, 33 out of 56 companies are classified as “publishers of other software” (code 58.29), 11 belong to “Other information technology and computer service activities” (code 62.09), and 9 belong to “Computer programming activities” (code 62.01). This section includes heavily funded companies such as Uber, Snap, Facebook, Pinterest and Twitter, all among the top 10 most funded IPOs in our dataset. For the sake of convenience, companies belonging to the Informantion and Communication section will be referred to as “tech companies”, and other companies will be referred to as“non-tech companies”.
Within the Professional Scientific and Technical Activities section, 28 out of 33 companies operate within research and experimental development on biotechnology (code 72.11).
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Figure 4.4: Average Simple Returns, by ISIN Industry Section
Figure 4.4 shows average returns for the three sections described above, as well as for the 26 companies in other sections. Apart from Manufacturing companies, average return is higher on the first day of trading than in the following three months for all industrys. Tech companies experience the highest first-day returns, and nearly the lowest returns in the following three months, only “beaten” by Professional Scientific and Technical activities.
Despite their slow start, manufacturing companies’ high returns in the following months make them outperform the other industries when looking at three-month return.