Want to Know Where a Stock Is Likely to Trade Post-IPO? Start with Where It Was Already Trading.
Pricing in private company secondary markets is increasingly driven by sophisticated institutions, and, as a result, pre-IPO trading levels now predict subsequent public market activity with surprising precision. That said, private secondary data can be noisy if small ticket trading by unsophisticated investors is not removed from the data set.
Private markets used to fund companies from inception until they became viable IPO candidates, and not a moment longer. Public markets were unquestionably the best and cheapest way to raise large amounts of capital, so companies listed as soon as they reasonably could.
Public markets were also the only reliable source of secondary market liquidity. Private market secondaries were rare, one-off transactions done by a few specialist investors that purchased securities at substantial discounts from distressed holders whose immediate need for cash overwhelmed their price sensitivity. As a result, pricing was more a gauge of a seller’s distress than of the underlying company’s performance.
Over the past two decades, a steady rise in private capital availability has reduced the cost of funding companies via private placements, while changes in public market regulation have materially raised the costs, regulations, and liabilities associated with being public. ¹
In response to these changes, companies began using private markets to fund growth through much later stages of their corporate lifecycles. As they did, and as their valuations appreciated, secondary markets developed to help shareholders manage portfolios of large positions with extended and uncertain timelines to exit.
Today, trading platforms like ZX provide scaled liquidity options to private company shareholders. Once trading markets matured and became a mainstream way for investors to access exposure and liquidity, secondary trading levels became a reliable indicator of equity value. This stands to reason — the deeper the markets for a security and the more sophisticated the players participating, the more likely that clearing prices efficiently reflect supply and demand for the underlying company.
The predictive power of private trading data today is especially strong and relevant in the months leading up to an IPO. Several factors make this so. First, private and public market investing used to be separate and distinct disciplines, but today major institutional participants commonly cross over and play in both markets. If many of the same investors are analyzing and investing in companies pre- and post-listing, it stands to reason that valuations would converge. Second, trading volume tends to increase during pre-IPO trading, so liquidity discounts shrink. Capital markets desks have long held that private securities carry an approximately 30% illiquidity discount to their public market counterparts. Many investment banks traditionally used this rule of thumb, assuming a 15% increase increase from private market value to IPO pricing and expecting the shares to settle a further 15% higher in public market trading than the IPO pricing. Yet a review of private secondary data suggests that this long-established illiquidity discount isn’t a set percentage. Rather, as the name suggests, it’s proportional to the liquidity profile of the particular company, almost disappearing entirely when deep private secondary markets exist. As a result of these factors, the predictive power of private trading has grown, and investment banks are increasingly weighing private market trading data when pricing IPOs.
Comparing pre-listing to post-listing trading levels for Spotify’s direct listing confirms the thesis that private markets today are an increasingly reliable indicator of public market levels. Approximately $1.8bn of Spotify shares traded hands privately in the year prior to its direct listing.² In April 2018, Spotify used these secondary trading levels to set the reference price of $132.50 for its direct listing on the NYSE. Pricing IPOs is often described as being more of an art than a science, yet Spotify hired no underwriters. While many industry participants were skeptical of the approach, a review of Spotify’s first month of trading shows that the reference price proved to be robust. Spotify closed its first day of trading at $149.01 per share, 12.5% higher than the reference price. It then bounced off intraday lows at $135.51 and $141.25 on the next two days of trading (2.3% and 6.6% above the reference price, respectively), and again found intraday support at $142.74, 7.7% above the reference price, on its 10th trading day before moving higher.
Apart from the special case of direct listings, traditionally underwritten IPOs also support this thesis. In the three months prior to its IPO, Lyft saw more than $500mn traded between institutional investors. ZX data suggests that most transactions occurred in a price range of $51.00 to $52.50 per share, with bids moving up to $55.00 in the final weeks of trading. While Lyft priced its IPO at $72.00 on March 29th, 2019, in its first month of trading Lyft’s stock found support several times at the top end of its pre-IPO trading range, bouncing off of $55.56, $55.62, and $54.32 on April 15th, 17th, and 26th, respectively.
Valuing companies based on their trading levels is of course the de facto standard in any market that surpasses some hard-to-define minimum liquidity threshold. The fact that data support this in private markets is more indicative of the dramatic maturation of the private market segment than any novel insight on the value of trading data.
Yet despite the valuable insights that can be derived from private trading levels, one must detect the signal through the noise in the dataset. Most importantly, trading in smaller tickets, often between non-institutional participants who don’t have the sophistication to value their shares, creates noise in the markets and tends to be less reflective of broader market pricing. These trades have become quite common since it’s standard for venture-stage companies to offer employees equity as part of their overall compensation package, and many of these employees need to sell stock to fund life events such as purchasing a first home.
Once noisy data has been filtered out, private company trading levels can be a powerful tool in predicting post-listing public market trading levels. Going forward, the predictive power of private trading data will only strengthen as private market liquidity continues to deepen and the private market attracts increasingly more institutional participation.
Co-Founder & CEO, Zanbato
This communication shall not constitute an offer or solicitation to buy or sell any securities in any jurisdiction nor does it constitute investment advice. Private securities are generally illiquid and there is no guarantee that a secondary market will develop for any private security. All securities transactions are effected through Zanbato Securities LLC, member FINRA / SIPC and authorized to operate ZX, an Alternative Trading System filed with the SEC.
- The Order-Handling Rule, Regulation ATS, and Decimalization contributed to compressing trading spreads to broker-dealers that supported liquidity in smaller issuers, while Reg FD, Sarb-Ox, and Dodd-Frank increased the cost and liability associated with being a public company.
- Calculated using the midpoint of the per period price range as disclosed on Page 175 of Spotify’s F1-A Filing