IPO Analysis: Part 1 - Assassins and Rabbits; Multibaggers and Dogs

Update July 2019: Part 2 of this Series is now available covering the addtional 133 IPO placings

Topline

 408 IPOs from 2011 to 2019 were analysed quantitatively: the median return was -17% with a 60:40 split of losers to winners over the time period. This fits with published academic studies of IPO performance of -8 to -23% . A deeper analysis of the numbers gives more insight on opportunities and the role of stop losses in converting trades into very profitable investments some which yielded several thousand percent returns. A furhter 133 placings were not excluded as they were nto amenable to the datamingin processes used. These are dealt with separately in Part 2 of this series which should be read in sequence.

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 (I've had a few knocks in the past)  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. The full version of this article with an interactive report of the data allowing DYOR analysis is published on runprofits.com. ( Stockopedia data is only  included in this summary article and not elsewhere )

Background to the Study

• 530 companies in the period 2011 to 2019 abstracted from a London Stock Exchange list off over 3000 IPOs and placings
• avoided the GFC and the extreme volatility in its aftershock so ruled out listings before end 2010. 
•  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 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)
•   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.
• References, assumptions and notes are appended to the full runprofits.com article to kept this version brief(er)
• not corrected for underlying markets but skew owing to IPO timings considered (see full article) 
• Placings were analysed by country of incorporation, sector and market as was the segmentation and concentration in losers and winners
• “multibagger” is any share that has more than doubled and a  “dog” is any share that has more than halved in value

The Topline Results

Data mining techniques were used to derive highs and lows from the dataset, avoiding a lot of chart gazing and human error. The below summarises these results and contextualises them in terms of profit and losses.

Of those 408 companies studied there were 166 gainers and 242 losers : a 40:60 ratio of winners to losers.

The 166 gainers had a median return of 60% with 51 multibaggers  with a median return of 190% , 23 of which made more than 200%.

Of the 166 winners , 71 never made a low below their offer price and only 35 made price lows lower than 25% below their offering price.

The 242 losers had a median return of -57% with 139 dogs  losing over 50% and 45 with over 90% loses

216 of the 408 made their price highs in Year 1 after the placing, with 78 in Year 2, 44 Year 3 and  31 in  Year 4.

 Only 10 of those 216 highs in Year 1  made a high below the IPO placing price, the rest were in-profit.

241 made price highs greater than 50% of the issue price  at some point over  the total duration studied

Conversely 171 made lows in Year 1, 64 in Year 2 with 52 in Year 3 and 27 in Year 4.

335 made lows lower than the placing price over the total duration with 183 making lows lower than 50% of the placing price.

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) 
• Multibaggers tended to have good Stockopedia Quality and Momentum : 36 of the 51 had both  Q and M greater than 50   while dogs had  the opposite (126 of the 139 had Q below 50)

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.

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

This study shows that a stop loss of 25% retains 86% of the winners and 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, 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 at least supporting sentiment)  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.

The Voting and Weighing Machines

This comes back to the original question; should I take a stake in an IPO placing and is there really a danger of missing out?  Only a few of the multibaggers ever got cheaper than their initial placing IPO price but all of them went on to make most of their returns several years after their placing dates. Relative to the rewards offered later on, the difference between the issue price and prices in early years suggest it might make more sense to wait for performance in the market rather than buying in the placing .  Indeed. a number of IPOs which did go on to be multibaggers went through periods of underperformance in the initial years and did offer better buying opportunities (BOO, BLOW, LTG, WAND). This echoes Ben Graham’s observation that in the short-term markets tend to be voting machines while in the longer term they are weighing machines. While charts are always easier to read from right to left  risk management using a stop-loss should work with the majority of nascent multibaggers

The concentration of highs in Year 1 is may have multiple sources. Institutional  and private investor flipping may account for much of it. It is often difficult to predict  the  intentions of large private equity backers/major shareholders beyond lock-in periods but these can have major impacts on price performance. This is particularly true when liquidity is low owing to initial large institutional  holdings. Equally price discovery in the market and changes in market sentiment may greatly impact early performance (especially when pre IPO hype gives way to even mild disappointment post-placing). An increase in the number of IPOs issued is often used to infer periods of exuberance of the overall market  with  potential pseudo-market timing effects (1).  Finally, IPOs predicated on inflated/invented financials and sometimes overt fraud can be difficult to detect but are precipitous once discovered.

While none of the above is rocket science, the numbers do suggest that taking a position  in an IPO is better viewed as a trade  while  an investment may be better made post IPO when the initial  few years of flipping, disappointments and price discovery have played out. These conclusions are made within the obvious caveats that more rigorous analysis of individual placings should enhance success and root out the more obvious dogs though I am not sure it will necessary identify some of the less obvious multibaggers to-be.

Would you rather be right or make money?

May the odds be ever in your favour is very relevant in the Hunger Games when the outcome is so binary: life or death. Not so in trading or investing where it is how  right or wrong that you are that really matters. 

Rather than focus on the 60:40 win:loss ratio it is important to calculate the outcomes in the context of the amounts lost or gained as a result of those odds (expected values) . By using a stop-loss, one controls the loss - in this case 25% while the gains are a matter of trade management.

For example, if one took a £100 position in every one of the 408 placings. 

Capital at risk is 408*100 = £40800

60% are losers  = £24480 but stop loss is 25% so net loss is £6120

40% are gainers = £16320 with a median return of 60% so net gain is £26112

Total return is £26112 + (£24480-£6120)  = £44472

Clearly you can be wrong more than you are right and still make money  through trade execution and risk management.

Conclusion.

What is very clear from the data is that there are good chances of making profits from trading an IPO position bought at the placing by selling in Year 1: timing really does work...

 BUT...

 The real rewards come from allowing good trades to become better investments , trade management and the use of stop losses will support that and prevent the converse which is too often the case when holding on to, or even adding to, losers: stop losses really do work.

My opinion on IPOs has changed, from now on I’ll take an informed position but trade it until it proves otherwise.

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