According to Greek mythology - Sisyphus, the king of Corinth was infamous for his wicked intelligence. His greatest feat was to cheat death - not once, but twice. For such trickery Zeus dealt him the eternal punishment of forever rolling a boulder up a hill in the depths of Hades.
Funnily enough, the analogy can be applied to current times as well. Much like Sisyphus, we forever keep building and pushing financial bubbles up the hill, as if it was the punishment for our trickery in finance- that is until we meet a chasm.
True, many aren’t able to pass through the chasm and the bubble bursts - but as a system, we almost always pass through and those that survive the chasm start pushing that bubble uphill again until the whole cycle is repeated.
It’s almost as if there is a pattern to this!
I had written this piece in October last year around Halloween which also coincided with the 50th anniversary of the Great Depression, but did not publish it for fear of it being a bit technical.
Considering the current times, I think it’s all the more relevant. I hope it helps you find the same perspective towards technological and financial bubbles as it helped me build. For more such pieces, consider subscribing to the Turnaround newsletter.
Here it goes..
Last week was Halloween, which is really but a public excuse for eerie adult wackiness. Guess what was the favourite costume among analysts this season?
Screenshots from different sources (Instagram, Twitter)
I think the jury is split between a Unicorn and an Adam Neumann costume.
Meanwhile, what was not lost on me as I kept looking at picture after another of crazy tech-valuation inspired costumes was that last week was also the anniversary of the Wall Street Crash of 1929 (Oct 24-29) that marked the start of the Great Depression.
With all the news around inversion of the yield curve, overvalued unicorns and historical nostalgia, I got myself thinking on the nature of technology and financial bubbles itself.
While we’ll leave the exercise in bubble prediction to the Raghuram Rajan(s) of the world (a reference to his 2005 Jackson Hole paper), there is value in remembering history to benefit our thinking. A good place to start is with the Carlota Perez Framework.
One of my absolute favourite authors, whom I remember reading in a course on innovation theory back in the day, Carlota Perez is a neo-Schumpeterian economist presently based out of UCL and most famous for her work in understanding the link between innovation and financial dynamics.
She studied all the major technological revolutions in the last 250 years and proposed that whenever a new paradigm technology is introduced to the world, it usually goes through 5 stages in a ‘S’ shaped curve.
Source: Screenshot of the S shaped Carlota Perez Framework as published in The Economist, 2003
The first phase that ensues upon the introduction of the new technology is the ‘Irruption phase’. During this period, there is an intense funding of innovation in the application of the technology. Usually, fresh clusters of revolutionary inventions begin to appear while new industries and infrastructure (both soft and hard) is established that underlies the technology.
This is followed by the ‘Frenzy phase’. Increased speculation and financialization leads to a decoupling between financial capital and production capital. In her own words, “Soon there is more capital wanting a piece of the action than projects looking for funds”. This leads to various forms of financial innovation, and “asset inflation takes off when the actors in the financial markets clearly switch from seeking dividends to pursuing capital gains, which results in the paper economy decoupling from the real one”. This is when finance begins moving faster than the technology is evolving and asset bubbles are inflated.
Because the real economy has not moved as quickly as the capital pouring in, dividends are not realised on the money deployed and asset bubbles tend to burst. Though, this is not necessarily a bad thing, because what the frenzy leaves behind is an up-gradation of the engineering and production pool of talent and resources within the ecosystem, to be utilised in the next phase. But note that this up gradation in skills is usually not that equitably distributed. These two phases usually mark the end of the Installation period of the new technology. Next begins the deployment period.
In the deployment period, the first phase is the ‘Synergy phase’. This is characterised by the growing inequality and political unrest caused by the the need for better financial regulation and filling gaps in skills (source for production capital). This is when the governments kick in, and the link between financial capital and production capital is repaired.
The final phase is the ‘Maturity phase’. By now, in terms of the key market players, the chaff has been separated from the grain – that is to say that, the best technology firms have survived and are leading the deployment of the mature technology. As this happens, opportunities for new investments decrease and the idle financial capital begins its movement towards new sectors and regions where it may lay the foundation for the next great surge.
Explaining with example:
The best way to absorb the mental model above is to take a jog down the memory lane and think of the developments that followed when blockchain appeared to the fore. At its irruption, it was heralded as the next big technology to reshape our world, leading to a frenzied amount of capital pouring in. Financial innovation ensued in the form of Initial Coin Offerings and money started pouring in faster than the pace of adoption of that technology into the real economy. As a small asset bubble ensued, governments took notice and introduced regulatory shifts. Then, as the non-productive companies phased out, those that survived the bubble and regulatory change, are now best placed to deploying that technology for real uses in the maturity phase.
While such frameworks and mental models don’t necessarily work in a plug and play fashion, they are incredibly helpful in contextualising and framing. Here is an attempt to understand what has happened in the last decade that is leading to the discussion around a mini-tech bubble.
The story begins, as best contemporary corporate tales now do, with the Lehman Brother crash and the financial crisis of 2008.
Tomasz Tunguz, a VC at Redpoint, has this graph on his website that shows the relationship between the Fed’s interest rates and the total startup fundraising (in billion USD) amount during various periods. Starting from the dot com bubble burst, until the financial crisis, the interest rates and net startup fundraising used to parallel each other.
But after the Lehman crash, what followed was a period of quantitative easing and interest rates were brought down to almost zero in many parts of the world. As that happened, institutional investors, rich family houses, pension funds and others began seeking returns outside the low/no yield environments. This fuelled VC fundraising as VC funds were now more attractive to LPs compared to alternative asset classes (e.g. bonds). A more comprehensive research on the relationship between interest rates and venture capital supply and demand can be found here. For those who prefer podcasts, the Equity Mates investing podcast also taken a shot at explaining this, albeit in a less academic fashion.
This was also a time when a new scalable technology came to the foray – which was mobile first and lead by the growing internet and faster processing speeds. A paradigm shift in mobile technology fuelled new business models in terms of sharing, platform and gig economies. The mass creation of data led to a new industrial revolution. At the irruption phase (think post launch of the first IPhone in 2007 and the follow up introduction of Android by Google), new clusters of innovation began to appear. Airbnb launched in 2008. Uber did a beta launch in May 2010. Several new companies were launched claiming themselves to be an Uber for X. In fact, The Atlantic compiled a spreadsheet of 105 Uber for X companies that entered the market and their fate. As the publication noted:
“Of this group, four—DoorDash, Grubhub, Instacart, and Postmates—are unicorns, start-ups valued at more than $1 billion. (Notably, all are in the delivery business.) Forty-seven are gone—28 simply closed down; 19 were acquired. But 53 are neither unicorn nor roadkill.”
What happened was, that as the tech moved from the irruption phase to the frenzy phase, financial capital began moving in faster than the speed at which the underlying technology and newer forms of business model could develop. Backed by the low cost of capital, everyone wanted to back the next Uber for X.
Since 2009, the number of mega deals that value companies above $100mn (post round valuations) have steadily increased over time and deal sizes have also continued to increase, with companies raising bigger and bigger rounds instead of inching towards an IPO (if you didn’t listen to the episode on the Use Case podcast with Karthik Reddy of Blume Ventures on why don’t more Indian start-ups IPO, check it out here).
Data source: S&P Capital IQ
At this point, as underwhelming IPOs dominate headlines (some shared at the end of the newsletter), a frenzy phase seems to be fuelling claims of a tech bubble, where the realisation is that the venture capital space has itself created this situation. For example, the rate at which AI based startups have raised capital has increased faster than the developments have taken place in business application of AI (capital inflow> growth in real production capital).
The bigger point to note here is that the bubble largely seems to be concentrated within the world of private and venture capital because of the exogenous factors ensuing the last decade. Corporations, and investors who traditionally participated in public markets moved into late stage venture investing, leading to bigger deal sizes and lower price sensitivity (well, until now when the frenzy made news).
With the benefit of hindsight, it so appears that the ‘animal instincts’ from the world of private capital, enamoured by the returns from a new technology/ business model, bet strong on capital gains exits rather the underlying dividends. Note, that this is also true for the public markets. The graph by Morgan Stanley below shows how tech stock prices have been priced far higher than their fundamentals. But there are other possible reasons for this such as tech firms pushing their stock prices up through buybacks, high R&D costs and showing lower profits for tax avoidance.
Source: Morgan Stanley report
The term ‘Unciron’ was coined by the venture capitalist Aileen Lee as a mythical animal to represent the rarity of the startups valued above $1bn. But if Halloween costumes are any sign of contemporary trends, that rarity seems to be vanishing now. If you ask a startup founder what their goal is, they are more likely to say “become a unicorn” than “get an IPO”.
What happens to the bubble and the frenzy phase that has now been highlighted, is beyond our ability to answer but the story that unfolded is something worth noting. Here are some other recommended readings on the topic that might peak your interest:
Note: To the list above, I also want to add a more current piece, “Start-Ups Are Pummelled in The Great Unwinding” by Erin Griffith in the New York Times, April 1, 2020.
If you would be interested in reading a book, here are two suggestions: A more academic “Technological Revolutions and Financial Capital: The Dynamics of Bubbles and Golden Ages” by Carlota Perez and the more fun “Disrupted: My Misadventure in the Start-Up Bubble” by Dan Lyons, the former senior editor at Forbes who started working for marketing software company HubSpot in 2013.