Market Epistemology
Prices and trends in prices of securities feel like objective data but it just isn’t. It is just as fallible as any other form of human cognition, indeed more so when you consider how complex the determination of prices can be.
In following the buzz surrounding AI you notice a lot of tropes. Most are tropes about how AI will change everything, like comparing it to the industrial revolution, or insistence that the fact that AI has progressed rapidly until now is a reliable indicator that it will continue to improve at the current pace or faster. As I’ve detailed ad nauseum on the blog I don’t buy these tropes, and find most discussions where they pop up exhausting as the people speaking often don’t realise how the premise of the discussion is dictated by vested interests in the AI and VC industries. But the trope I find most worrying is the suggestion that financial markets value AI companies highly, so that must mean that the technology is the real deal.
The idea that market prices are reputable sources is not limited to AI however, it crops up in all manner of discussions, like energy and even politics. It is a phenomenon I call ‘Market Epistemology’. For a typical example, consider this comment on The Rest is Politics from June 9th:
[20:55-21:00] Rory Stewart: "I'm afraid she is almost certainly entirely wrong, certainly the entire global markets are betting against her"
Stewart was disagreeing with an AI critic, and marshalling the markets' convictions as evidence supporting his pro-AI argument. I’m not singling out Rory Stewart to make a cheap point at The Rest is Politics’ expense, I’m making the point that even well-educated and otherwise rational people make the mistake of conflating prices with evidence.
Of course, the idea that markets are expert witnesses whose cold calculating rationality can help us understand the world outside financial markets is humbug. The history of finance is literally littered with examples of prices going amok and the values of companies, houses, and even flowers disconnecting from reality. Which brings me to my first point: that markets may be rational over the long term, but any given day, month, or even year, they could be completely wrong.
The Great Recession is a good example. In the years leading up to 2008 Mortgage Backed Securities (MBS) were safe as houses, and the prices indicated that not only were these bonds safe, but by extension that a house in America was not only a safe purchase but one which would continue to grow in value. As we now know however, MBS were always risky and worth little, and as Michael Lewis showed in The Big Short this was not a revelation when it all collapsed, it was known to experts before the crash. This is a key point, that it was not new information which triggered the crash, it was a change in perceptions, people in the know always knew what the markets eventually discovered.
2008 was not an isolated incident either, every financial crisis is at its core a story about mispricing, of markets being too excited and pricing something far higher than they ought to, only to realise and lose a lot of people a lot of money. Tulips, the South Sea Company, railways, internet companies, the Japanese economy in the 1980’s, and the metaverse, just to name a few bubbles of the top of my head. These were all bubbles where markets were wrong about a concept, if you add all the times markets wildly overvalued a company like Gamestop, Theranos, or FTX we could be here all week.
So if a cursory glance at the history of finance comprehensively disproves Market Epistemology, why do people still subscribe to it? Well there are two reasons. Firstly, there are few professions as highly esteemed in Western society as financiers, and the fact that the competition to get a job in hallowed halls at the heart of capitalism is so fierce, and that proxies for social status like pay, and the deference from journalists bankers and portfolio managers tend to get indicate to the layman that these people know what they’re on about. If these people with their fancy university degrees whose job it is to understand and value companies tell me that AI is the next big thing, who am I to question them?
Secondly, we have to look at what is taught at those fancy universities. As anyone who has taken introduction to finance knows, the widespread view in academia is that markets are efficient. Now what that means is a bit complicated, and we will get into that, but first it is worth simply stating the fact that the way financial economics is taught is premised on the idea that markets are efficient. So what does that actually mean? Well it means that the price of a security reflects all available known information about that security. There are different versions of the idea of efficient markets, but the important thing about this thesis is less the theory itself than the assumptions it is built on.
Academics and financiers alike acknowledge that the efficient market hypothesis is not strictly true; otherwise equity analysts and other alpha chasers would be completely superfluous. But the idea that people with different views put real money on the line is a good way to get at the wisdom of crowds which underpins the efficient markets hypothesis is widely accepted in Western society. This in turn makes the markets seem a good judge of companies, industries, and technologies.
The problems with this view are manifold, but let’s start with the most obvious one: that the market is blind to intentions. If I buy Nvidia shares in the cynical belief that the AI industry is a massive bubble, but I am sure that there are greater fools out there I can profit from, it raises the price of Nvidia. If I buy Nvidia shares in the sincere belief that AI is sure to cure cancer and lead to a celestial utopia of unimaginable wealth for everyone, it raises the price of Nvidia. The result of both of these actions looks the same to you on the other side of the Bloomberg terminal.
This is an underappreciated but key insight on markets, that a price going up or down has far more causes than the underlying business’ performance. Interest rates, the number of shares outstanding, the performance of rivals, and regulatory changes can all impact a company’s share price without necessarily having any meaningful impact on the company itself. And valuation, the central function financial markets serve, can itself be the impetus for a share’s rise or fall, in a very recursive and counterintuitive way.
Furthermore, there is a very tangential relationship between the truth and valuation, and as market participants are primarily profit seeking rather than truth seeking, there is no guarantee that an accurate valuation is a reflection of the truth. As such, even if we accept the premise that markets can and do find the truth (a dubious proposition, in my view), their truth production is a side effect of their real function of pricing securities; any truth found is an externality.
For a more concrete example of the tangential relationship between truth and valuation, consider the way the financial industry uses probabilities and scenarios in determining the value of a security. A low probability of a very high impact scenario – such as AI changing literally everything forever – can justify astronomical valuations. In addition, markets are reflexive, and as such the fact that someone else values a security highly can influence your own view in a recursive loop driving valuations higher. Or the opposite, where a persistent pressure of selling can lead to others changing their views and adding to the gloom.
Perhaps the main reason why the idea that markets are good at finding out the truth is untrue is psychological. The markets produce a single price, whereas analysts, theorists, pundits, and experts produce long texts. $47 looks more authoritative and certain than a long text with hedges and acknowledgements. This seeming objectivity, this instinctive trust in systems over people is the same reason why people in line at Burger King tend to place more value in the order numbers on the screen than the human shouting out which order is ready.
The illusion is most clearly seen when contrasted with the sort of hard sciences finance seeks to emulate with its focus on maths and numbers. Important numbers in disciplines like chemistry and engineering are constant; a mole is always 6.02214076 × 1023. But the price of Nvidia is anything from $18 to $215 depending on when you looked. Naturally, the value of a company shifts as its prospects change, but the key insight here is that valuations are not discovered or invented objectively, but determined socially.
Prices and trends in prices of securities feel like objective data but it just isn’t. It is just as fallible as any other form of human cognition, indeed more so when you consider how complex the determination of prices can be. As such any argument which marshals support from the financial market’s whims should be suspect. Financial markets are useful tools, but the mythology which has been built up around them since the market revolution in the eighties leads people astray. Price signals are important and useful, but narrowly so. Generalising from a source as one-dimensional as a price quoted for a security is highly dubious. At the end of the day, prices are a type of tea leaf you read, not an objective signal about the truth. Prices may well be more accurate than horoscopes, but they are neither scientifically nor philosophically rigorous as a source of truth.
If you liked this post you can read a previous post arguing the US has financial Dutch Disease here or the rest of my writings here. I also have a section for longer reads I call essays here, I particularly recommend my series called The Bird & The Technoking exploring Elon Musk's takeover of Twitter, and its political and cultural implications. It'd mean a lot to me if you recommended the blog to a friend or coworker. Come back next Monday for a new post!
I've always been interested in politics, economics, and the interplay between. The blog is a place for me to explore different ideas and concepts relating to economics or politics, be that national or international. The goal for the blog is to make you think; to provide new perspectives.
Written by Karl Johansson
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Cover photo by Ruben Boekeloo from Pexels, edited by Karl Johansson
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