Can Prospect Theory Explain High Start-up Valuations?

Human beings are not particularly good at thinking about probabilities. The last several decades of research in psychology and behavioral economics have unearthed an array of cognitive biases in how we reason about uncertain events. For example, we are prone to misinterpret the results of diagnostic tests, by failing to account for the base rate of a disease in the population. This has enormous implications in the medical field, and may be leading us to over-diagnose and over-prescribe treatments for a variety of illnesses.

One of the foundational theories in behavioral economics is prospect theory, formulated by Daniel Kahneman and Amos Tversky. This theory is most well known for the observation that humans interpret losses as more consequential than gains of the same magnitude. Thus, simply changing the framing of a decision from a ‘gain frame’ to a ‘loss frame’ can make people much more averse to taking risks. In this blog post I want to focus on another prong of prospect theory: the over-weighting of rare events.

Prospect theory suggests—and experimental evidence supports—the idea that people ‘filter’ probabilities: we act as though very low probability events are more likely than they really are (and as though high probability events are less likely than they really are). This helps explain why people fret so much over low probability dangers such as shark attacks and ignore more mundane risks such as accidental falls. It also helps explain why people gamble money on lotteries even when the odds of winning are very slim, and the expected return is negative.

What has this got to do with valuing a start-up? The conventional way to value a company is to make a forecast of its future cash flows, then discount these back to find the ‘net present value’ of its future income. Alternatively, as a heuristic we can apply a multiplier to its earnings based on accepted valuations of other companies. Neither of these works for an emerging venture with a novel business proposition (i.e. your typical Silicon Valley start-up). The future prospects of such a company are shrouded in uncertainty.

Instead of trying to establish the likely path of a given venture’s future cash flows, investors—usually venture capitalists—take a portfolio approach. They pick companies they think will have a chance at becoming massively successful, but realize that many will fail to do so. Each investment is a bit like a lottery ticket. In the classical VC portfolio model, roughly one investment in ten would need to exit at a blockbuster valuation for the overall fund to make a decent return on investment.

In the present wave of technology venture activity, three key things are being done differently to the past. First, the definition of a ‘massively successful exit’ has inflated: ventures now aspire to be ‘unicorns’ with a billion-dollar valuation. Second, investors are spreading their money out, investing in a larger number of ventures. This is most visibly true in accelerator programs, which provide large numbers of nascent ventures with seed funding and mentoring in return for a small equity stake: they explicitly rely on a scattershot approach. Instead of a VC picking ten investments and hoping for two or three large exits, the accelerator approach is to invest in a hundred startup teams and hope for one unicorn. Third, more ventures are staying private for longer, rather than go public through an IPO. As described in this FT article, this allows them to effectively manage their headline valuation figure by giving new investors guaranteed financial returns (risking, in the process, the equity of preceding investors). This prevents negative opinions of the venture’s prospects from being incorporated in its valuation.

And so we have a perfect storm in which valuations are based on someone’s estimate that a given venture will become a unicorn, and—according to prospect theory—they are biased to overestimate how likely this is. For every thousand startups, maybe one of them will be hugely successful, but all of them might be valued as if they have a one-in-a-hundred chance of this success. This is a problem. More fundamentally, we are dealing with such small probabilities that we can easily get them very wrong.

Earlier in the year I considered a few possible mechanisms by which a hypothetical technology bubble might burst. Here, I’ve described one psychological factor that might be behind high startup valuations in the first place. It’s also worth noting that prospect theory can explain rapid changes in investor sentiment. If prices start falling—for example if a bubble shows signs of bursting—investors can switch from a gain mindset to a loss mindset, and immediately become much more risk averse. I hope this doesn’t happen, because the present wave of entrepreneurial activity is generating a lot of innovation. But a wise investor or entrepreneur should be aware that the tide might turn in the near future, and plan accordingly—or risk getting swept away when it does.

How Might the Tech Bubble Burst?

Tech company valuations are through the roof right now, and many people have been questioning whether we are presently living through a tech bubble. In this blog post I set to one side the thorny question of whether we are in a bubble or not. Instead, I go through a thought experiment: I assume that we are in bubble, and play out a few scenarios for ways in which it might burst. Here are my top three:

Scenario 1: A Rising Star Falls
Present tech valuations are only warranted if you believe in the fundamental quality of their management teams. A high level of future growth is already priced into current valuations. This will only be attainable if they can expand their horizons, for example by expanding internationally. Such expansion puts a lot of pressure on organizational infrastructure. It is hard for a Silicon Valley-based headquarters to ensure that every local subsidiary maintains the quality standards they aspire to globally. Businesses who scale up slowly often have problems; those doing it at an accelerated pace (such as Uber) are even more likely to trip up. If too many local scandals mount, the managerial quality of the whole enterprise will get called into question, as will its valuation. The bold, fresh-faced management team will suddenly look hapless and inexperienced, flailing in the midst of a crisis, or riven by internal politics.

We only need look at Enron to see the risks that free-wheeling growth can expose an organization to. Now I am categorically not saying that every tech start-up is an Enron.  waiting to happen. What I am saying is that it could take just one high-tech corporate implosion to cast doubt on all the others. And once investors start to doubt the fundamental managerial quality of these tech ventures the game is up for the whole pack. Let me be totally clear: this line of argument is about perceptions. In the context of venture capital investments ‘risk’ is highly subjective, in other words it is a matter of perceptions. One dramatic fallen star could change the perceptions of investors about the risk of all the other stars, leading to the tech bubble deflating.


Scenario 2: The Advertising Pyramid Collapses
Many tech ventures rely on advertising as their main (or sole) source of revenue. Advertising is the bedrock of the tech sector, worth an estimated $43bn in 2013. It has allowed the industry to evolve in such a way that consumers expect services to be free. Take it away and those apps and websites suddenly don’t look like such appealing investments anymore.

Where do the pressure points lie when it comes to advertising? I see two potential sources of strain. First is the question of the proportion of advertising accounted for by tech companies and websites themselves. Apps tend to display adverts for other apps; websites display adverts for other websites. Webmasters buy ads to drive eyeballs to their site, where they hope people will click on ads. When this kind of behavior occurs, the online sector is feeding on itself – it is autophagous. Here we are in classic bubble or pyramid territory. The pyramid is sustained as long as it draws more people in to play the game, but once it is revealed to be hollow, it vanishes at once. I don’t have data on how much advertising is of this nature – so I can’t truly judge the extent to which this is a problem. However, just from my personal experience of browsing the web it appears that a lot of advertising is of this autophagous nature.

The second pressure point is the difficulty of measuring the return on investment (ROI) of online advertising. Web-based advertising platforms throw off a lot of data. The funnel from views-to-clicks-to-purchases can be tracked, so in principle a marketing manager can attribute a given online sale to a given online advert. However, things are far from simple. A customer who clicked through a pay-per-click advert may have still made exactly the same purchase even if the advert hadn’t been there. And a lot of online advertising is bought primarily to promote offline sales (think of, e.g., car adverts). However the effects on offline sales are much harder to track. Interestingly, while online advertising opens up the possibility of using randomized experiments to measure the effect of adverts, research so far has found that the effect size is so small it is hard to reliably measure from a statistical standpoint.

The upshot of this: the online advertising industry, while huge, is not yet in a long-term, stable equilibrium, and it’s not clear whether the stable market size will be larger or smaller than the market that exists now.


Scenario 3: Silicon Valley Disrupts Itself
To disrupt an industry is the bold aim of many of Silicon Valley’s start ups. It typically entails finding a way to deliver the same service the industry presently delivers but at a fraction of the cost or at a step-change improvement in quality or convenience.* It is often said that to disrupt you need to offer something 10x better than what presently exists, in order to overcome people’s inertia and lock-in with present systems.

The industries targeted for disruption are typically of the staid, old-school variety, perhaps dominated by some entrenched rentiers – think of Uber disrupting the taxi / car industry, or TransferWise disrupting the foreign remittance industry. The narrative of disruption underlies the massive valuations these companies receive. To take Uber, for example, in debates about its valuation have moved from comparisons with the entire global market for taxi services to discussion about how it might act as a subtitute for car ownership.

But there's no particular reason only old industries are vulnerable to disruption. It is perfectly conceivable that one of the current tech giants itself gets disrupted. People appear pretty locked-in to social media platforms such as Facebook, but if a company were to come along with an offer 10x better than one of these, it is easy to see customers switching. And, in fact, many already did: in the last few years plenty of people switched from Facebook to Twitter or Instagram as their primary social media feed, and in future something even better than either of these may come along. Well aware of this fact, Facebook paid a billion dollars for Instagram and $22bn for WhatsApp primarily because of the threat that these businesses posed to its dominance.

I can’t predict what a social media platform 10x better than Facebook would look like, but then neither could I have predicted Facebook’s creation before it existed. And, as with Scenario 1, it only takes one giant to fall asunder for many of the others to lose their appeal to investors.
 

So, there we have it, three scenarios for how the tech bubble might burst. Which do you find the most plausible? What other scenarios sounds realistic? Answers in the comments below! 

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*Note: this is a fairly colloquial definition of disruption. It is a somewhat warped version of its original academic usage by Clay Christensen, which referred to creation of new performance dimensions for emerging market sub-segments that eventually become large markets in their own right. Here, the colloquial meaning is the one I intend.

What Ai Weiwei can tell us about the valuation of Facebook

When Goldman Sachs purchased a c.1% stake in Facebook for $500m, the figure that hit the headlines was the $50bn valuation for the whole of Facebook that the sale implies. But is the company really worth that much? Is it really fair to extrapolate from the valuation of a small stake to the fair value of an entire company?

Interestingly, the art world can shed some light on this. There is currently an installation in the Tate Modern by the Chinese artist Ai Weiwei made up of 100 million handmade pottery sunflower seeds. It is an imposing sight, with a mixture of possible symbolic meanings. It could be a commentary on China’s powers of mass production, or the scale of its population and relative insignificance of the individual. It might be a reflection on the power of nature or the beauty of simplicity. It’s probably about something else entirely. Luckily the symbolic meaning of the art is tangential to its relationship with Facebook.

When it was first opened the installation could be walked on by the public. It was later closed off, ostensibly for safety reasons. But with tightened security, it meant it was no longer possible to walk off with a pocket full of pottery sunflower seeds. Given the high profile nature of the installation it was clear that the seeds would become collectors items – and unsurprisingly there have been several seeds changing hands on Ebay. It was reported in the press that a single sunflower seed had been sold at auction for £28. This is where the link to Facebook comes in: If we apply the same valuation calculation to Ai Weiwei’s artwork, the whole work would be worth £2.8 billion, making it the most valuable artwork ever created*.

This valuation is clearly absurd! What it shows, though, is that the laws of supply and demand operate not just for commodities, but for fractional ownership stakes in a larger whole. Where demand to own a stake is high and the supply of stakes for sale is low, the price is naturally bid upwards. In my opinion it is this effect that lead to the high price for a small stake in Facebook. If the whole company were to be sold, for example in an IPO, I would expect a lower valuation than the $50bn+ reported in the press. But while its stock is privately held, the demand for it is so high that it will change hands for inflated prices. Fractional sales are a good way to create the illusion of a high valuation (see also Zynga, Twitter) - but as Ai Weiwei’s sunflower seeds demonstrate, this can’t be taken at ‘Face’ value.

Note
*In an auction at Sotheby’s on 15th February, a pile of 100,000 seeds was sold for £350k. Based on this unit value of £3.50 per seed, the whole work is worth £350 million, still a record breaking valuation.