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Nomura Unveils The ‘4 Triggers’ That Will ‘Burst The Data Bubble’

Nomura Unveils The ‘4 Triggers’ That Will ‘Burst The Data Bubble’

One of the narratives that is quickly becoming a driver of markets is the idea that a confluence of factors have conspired against market darlings like Facebook and Google.

Not the least of these factors is politics. As we noted first thing this morning and as we detailed extensively over the weekend both here and elsewhere, the political environment is extremely charged right now, and the details around the Cambridge Analytica story suggest that Facebook is going to get thrown right back into the fray at a time when lawmakers are at their wits’ end.

It’s entirely possible that between the Facebook drama, the Uber fiasco, and the focus on cryptocurrency regulation, the tech sector might be headed for a multi-pronged regulatory crackdown that could reverberate through markets thanks to the fact that, as Bloomberg’s Mark Cudmore wrote on Tuesday, “much of the rally of the last few years for global equities has hinged on the technology sector [and if you] damage this pillar then earnings, valuations, supply chains, trade and innovation all suffer.”

Well picking up on this theme is Nomura, who is out with a pretty damn interesting note on Tuesday provocatively entitled “The bubble you didn’t know about could be bursting without you knowing.”

They begin by pointing out something that will please our good buddy Kevin Muir (of Macro Tourist fame) – namely that “one of the challenges of identifying bubbles is that too often we use the playbook of the previous bubble.”

The propensity to suppose that the next crisis will resemble the last leads us not only to look in the wrong places for catalysts and proverbial coal mine canaries, but also to hedge incorrectly.

For their part, Nomura thinks everyone has until recently been blind to what they’re calling the “data bubble.”

The bank thinks it’s possible that “data” is improperly conceived by analysts and investors. Specifically, they note the obvious, which is that “assets are things that can generate recurring income, and thanks to the revenues of many social media and tech companies we know that is the case.”

Next, Nomura suggests that traditional accounting is probably leading to a scenario where the book value (and thus the price-to-book ratios) of certain companies doesn’t  reflect what it should. That, in turn, means that “all the comments about the lack of investment in developed economies may be misplaced [as] there may well have been lots of investment, but it has not been accounted for correctly in official statistics.”

Ok, so with that out of the way, they get to the “good” part – a section called “the four triggers for the data bubble to burst.” Here they are, trimmed for conciseness:

  1. The cab-driver is talking data/platforms Returning to market valuations of these intangible assets, they have been surging in recent years. Investors are assigning more and more value to data and platforms (Figure 1). The number of books, articles and non-tech corporates talking about big data, AI and blockchain is also reflective of this. Even cab-drivers (or should I say Uber drivers) are talking about some of these trends. A classic sign of the late stages of a boom is when non-specialists start to become the most vocal advocates for the boom.
  2. databubble
  3. Politics is turning against the sector The more fundamental trigger of the bursting of this “bubble” is the shift in politics on the data/platform industry, especially in the US. It is notable that whenever President Trump talks about the US trade deficit, he focuses on the goods balance, rather than trade in services or invisibles. Part of the reason for this is the fruits of the data/platform revolution has not been shared across the economy – if anything, it has seen income inequality widen as intangible asset-intensive industries tend to create winner-takes-all-dynamics. The thrust of US policy is therefore moving back towards tangible asset industries, such as manufacturing, and away from intangible asset industries, like data/platform companies.
  4. The perception of the accuracy and use of the data are being questioned Part of the explosion in the use of these platforms was the disruption of the conventional distribution and verification of information. Before social media, information was distributed and verified by particular institutions such as press/media companies, universities and government bodies. Today thanks to the increasing concerns that platforms and data-holders have been “gamed” by corporations and foreign governments to manipulate consumers and voters, there is a growing backlash from individuals and governments on how these platforms can operate.
  5. A move away from global towards regional standards Finally, there is a move to regionalise standards on big data/AI/platforms rather than globalise. The big three regions are the US, China and EU. China has a clear policy of a state-centric data/platform model, where Chinese data have to be held in China with oversight from the authorities. The EU is increasingly flexing its muscles on the rights of the consumer in relation to data/platform owners. That leaves the pioneering US companies with the most to lose as they have to retrench from these markets.

Nomura’s takeaway from all of this is similar to our own. In short, the political backdrop and, somewhat ironically given that the hijacking of these platforms was in part undertaken in the service of bolstering populist candidates, the desire to paint these companies in a negative light to the extent that advances the anti-globalist message, bodes ill.

“The bottom line is that trade wars, populism, income inequality can be looked at in isolation, but together they all point to a reaction against the growth of fluid intangible-intensive industries such as the data/platform companies,” Nomura concludes.

Whether that’s a good or bad thing for society is an open question and largely depends on how regulatory action is justified and who it is that’s doing the regulating.


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