Introduction

To IPO or not to IPO?  that is the question. Whether it is more profitable to risk the slings and arrows of a placing or to wait and see how the market receives it?  These days  I tend to ignore the barrages of  broker emails and don’t get carried away by FOMO: I prefer to give a placing some time  in the market before taking a position. Intuitively this feels right but I decided to go beyond heuristics and take a deeper look at the data to see if being more systematic was of merit. Does it make sense to get in early at the placing price?  How do IPOs tend to behave post the placing and in their formative years? The initial results surprised me so I did a bit more digging before drawing any firm conclusions. This article is the first in a series looking to unpack some of the insights and devise actionable trading and investing strategies.

Being more of a trader than an investor these days, I increasingly use historical price action to inform my decisions: clearly as initial public offerings, IPOs don’t have that. Some time in the quoted markets is useful to get a handle on volume at price not to mention post flotation shocks, wholesale offloading of pre IPO shares as well as any issues with the placing, book building and very early stag profit taking (during Facebook’s first  couple of weeks on the markets in 2012, the price dropped 27% below the IPO price amid frantic trading) .    I also have an aversion to prospectus documents with their Byzantine appendices and turgid, overlong bulk. Finally, there is a good body of academic publications to evidence that IPOs tend to underperform typically by -8 to -23% (1-3).

Background to the  Study

With the above in mind I went through the London Stock Exchange list of new issues  and abstracted data from a set of over 3000 IPOs and placings. I wanted to avoid the GFC and the extreme volatility in its aftershock so ruled out listings before end 2010. I  was also keen to look at more recent placings in the “new” ultra-low interest environment. The final set was a list of over 530 companies in the period 2011 to 2019. This was further whittled down by another 130 or so which didn’t appear in the datamining: the bulk of which seem to have delisted (some may have changed name). This article takes a quantitative look at the performance of the 408 remaining IPOs placed between 2011 to 2019. It is worth mentioning that there are some screaming frauds in those 133 that delisted (and others that were profitably bought-out): it might be worth returning to them at a later date as they will likely skew the numbers.

Let me be clear from the get-go, this is a quantitative study based on a total universe of the good, the bad and the sometimes downright ugly. It doesn't have the qualitative lens used by good fundamental analysis coupled with sector and domain expertise used when focusing on individual placings.  Nor does it approach IPO placings by trying to understand the motivation behind the listing given cost, complexity and disruption to the business this causes (4). There is a lot of data here but hopefully the visualisations help tease out the value and enable some actionable observations and some compelling conclusions. My initial views and preconceptions were challenged by the data and my own conclusions unexpected. I’ve appended notes below on assumptions and omissions including not comparing to the underlying market.  I also accept that this analysis would be more robust if 408 non IPO companies were chosen from the same period and the analyses compared but this task would then be in danger of becoming Sisyphean.

Some observations and So what?

• Winners generally kept winning with 31% of winners winning really big (up to almost 3000%)
• Many of the losers  went on to lose a lot  with 38% of losers losing really big (>75%)
• A stop loss of 25% would have kept 143 of the 166 winners in play and only stopped-out 7 of the 51 multibaggers while removing 215 of the 230 losers.
• Given the number of highs in the first year, there is very good evidence of flipping in Year 1 possibly by both institutions and private investors.
• Taking a  position in an IPO looks to be more of a traders’ game than an investors’ one (with all the caveats on quality of fundamental analysis)

Rabbits and Assassins

This suggest some potential strategies around IPO placing that help to mitigate risk and look to capture the multibaggers (and try not to let them go) while releasing the dogs early before being thoroughly savaged.

The numbers suggest that allowing the price action post-placing to dictate one’s strategy seems to make sense i.e.  assume taking a position in an IPO issue is a trade until price proves it to be an investment. Then let execution strategy and risk management navigate the price trajectory post-placing. This of course pretty much true for any trade or investment but what may be peculiar with IPOs is that once forged in the fire of price discovery, public markets rapidly resolves the good from the bad: the multibaggers from the dogs even as  large holders of the original issued equity play out their hands. That the initial perceived value, the issue price, is a discrete price and not a range may give a very defined selling point. This may well skew behaviours and exaggerate price performance as most participants anchor to the same price point at least in the early years.

This study shows that a stop loss of 25% retains 86% of the winners and more importantly almost 90% of the multibaggers. Given the sample size and duration of the study these seem like a sensible parameter to use in trade execution. Building positions by adding to winners and letting go of losers (defined at least by a stop loss) concentrates capital in the best performers.

To invoke Lee Freeman-Shor’s investing behavioural types (4), one needs to be an assassin and  not a rabbit with IPOs - executing losers remorselessly. Again this is all good discipline and trade execution but the lack of historical data with IPOs adds additional uncertainty compared to long standing  publicly quoted companies  with years or even decades of published accounts. That risk can bring the huge rewards evidenced by AB Dynamics (+2922%) or Blue Prism (+1538%)  which convert pre IPO promise into real growth and momentum or alternatively can  lead to wipe-outs like Maistro or Block Commodities (both -99.8%)

Given the number of highs in Year 1, flipping is also a viable trading strategy with different risk parameters and expected returns.

 Appendix: A note on Sectors, Countries

The total universe of 408 was analysed by sector country and market as were the winners and losers to examine sector and country over/under-performance. Junior oilers and miner are fairly notorious for overpromising and under-delivering with sometimes spectacular losses.  Many investors will shun companies from some countries owing to track records of frauds and limitations on prosecution in the event of fraud.

Figure 8 shows that  more of the winners came from Financial Services, Support Services  with an even more pronounced concentration of Support Services and Software companies in the multibaggers.  Mining and oil and gas producer did concentrate in the losers with the ratio of mining doubling from 6% in the total universe to 12% in the dogs;

Figure 9 shows a similar segmentation by country, I suspect that this would change further if the 130 delisted companies were included since it contains several from Israel and China which have proven to be frauds. The plot shows a doubling (albeit from a low base ) of Israeli and BVI companies in the dogs : the percentage of UK companies increased from 81% in the total universe to 87% in the winners and decreased to 73% in the dogs. This does seem to confirm the bias against companies from these countries.

Notes

1. There are 133 companies that listed in that period and subsequently delisted in the intervening years: many of these have been acquired (Poundland, Jimmy Choo, TSB)  while many more  ( Naibu, MySquar, Patisserie Valeria)  were frauds. I've excluded that list from this analysis but may revisit later to update the data set although that needs much qualitative analysis
2. the performance of the placings have NOT been corrected relative to the underlying markets – so at the time of this analysis,  from  2011 to 2019 the FTSE All-Share has risen 31.6% while the AIM All-Share is up just 1% and the FTSE 100 up 15%. Given the different timescale of the placings, the relative corrections to underlying markets would have been pretty time consuming.
3. Relative performances have been derived using time from IPO date: this will be skewed to some extent by more recent data: 30% of the total sample were placed in the last 3 years (removing these drops the median return to -24% for the total universe )

Notes

1. There are 133 companies that listed in that period and subsequently delisted in the intervening years: many of these have been acquired (Poundland, Jimmy Choo, TSB)  while many more  ( Naibu, MySquar, Patisserie Valeria)  were frauds. I've excluded that list from this analysis but may revisit later to update the data set although that needs much qualitative analysis
2. the performance of the placings have NOT been corrected relative to the underlying markets – so at the time of this analysis,  from  2011 to 2019 the FTSE All-Share has risen 31.6% while the AIM All-Share is up just 1% and the FTSE 100 up 15%. Given the different timescale of the placings, the relative corrections to underlying markets would have been pretty time consuming.
3. Relative performances have been derived using time from IPO date: this will be skewed to some extent by more recent data: 30% of the total sample were placed in the last 3 years (removing these drops the median return to -24% for the total universe )