Market inefficiency reconsidered

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Michael Mauboussin on market inefficiency

Whenever Michael Mauboussin releases a new paper I read it at once. The Morgan Stanley analyst and Columbia Business School professor is better than just about anybody at weaving together the various threads of finance research. His latest, “Who Is On The Other Side” is on market inefficiency. 

The central argument is about the shifting burden of proof for active investors. In the hunt for opportunities to outperform the market, we often assume the key is seeing things as they are: that we have the relevant information, are free of bias, have made reasonable estimates of future cash flows, and so on. Mauboussin’s broad argument is that you can’t make money by just being right. You have to understand why the people “on the other side” of your trade are wrong. What bias, factual error, analytical mistake, or structural market trap they have fallen into. You must be able to “articulate why an inefficiency exists and how it will be extinguished.” It’s not enough to build a net present value model that spits out a number higher than the current price. 

This is hardly a revolutionary point, but it doesn’t get pushed into the foreground as much as it should. Warren Buffett is, of course, the great exploiter of “the other side”. One of his great insights is that the market systematically misunderstands and undervalues companies with high short-term earnings/price volatility and high capital intensity. He bought businesses with those characteristics that also had rich reinvestment opportunities, and built a compounding machine. 

Two other, more specific points Mauboussin makes also bear repeating. 

First, the prevalence of market inefficiencies — where value and price diverge in an exploitable way — waxes and wanes cyclically. Here is his chart of the gross value added yield (per cent outperformance divided by assets under management) of active mutual funds investing in US stocks: 

“The trend is generally down since the Great Recession (2007-2009), which coincides with an acceleration of flows into index funds,” Mauboussin notes. Fair enough, but I wonder if hedge funds are also responsible for the downward trend, or if it might just be noise. I’m in the camp that says passive funds must ultimately create opportunities for active managers, but that those opportunities will take longer to ripen than in a market with less passive buyers. 

Mauboussin argues convincingly that the tendency of groups to converge on a single way of thinking is the uber-inefficiency, the “most significant recurring behavioural opportunity.” He frames this in terms of the transition from the wisdom of crowds to the madness of crowds. The wisdom comes from diversity and averaging:

Individual errors, however widespread, are rarely relevant in determining market efficiency. The interaction of investors with little information or rationality can yield prices with surprising efficiency. The essential conditions [for a wise crowd] include investors with heterogeneous views and decision rules, as well as an effective way to aggregate the information

But the diversity condition is unstable 

Markets lose efficiency when investors lose diversity . . . One of the challenges in dealing with diversity breakdowns is that their effect tends to be non-linear. In other words, you can lose diversity consistently for some time and the asset price will not react. Then a small change on the margin leads to a large change in the price.

Low belief diversity markets are subject to violent changes because they are illiquid. When almost everyone has the same view, who is there to sell to when things go wrong?

Of course — though Mauboussin does not lean into this point — the discussion of diversity breakdowns brings the AI boom to mind. Is there sufficient diversity of views on AI to prevent market brittleness? The recent weakness in some AI-linked names (Oracle, Meta, Broadcom) suggests there might be. But “Who Is On The Other Side” alerted me to literature showing that market bubbles, as opposed to benign and sustainable leaps in share prices, tend to be associated with big increases in corporate investment. And the AI boom has that in spades.

Immigration and the labour market, continued

Over the weekend, Unhedged briefly wrote about how Trump’s immigration policies may be working to the detriment of native-born workforce and pose an inflationary risk. We think some of these points warrant a deeper look:

  • Counteracting population ageing: Immigration has helped to partially buffer the effects of an ageing US population. According to the Economic Policy Institute, the US labour force as a whole averaged just a 0.5 to 0.6 per cent annual increase in the last two business cycles since 2007. Notably, the figure was just half of that for the US-born group. 

  • A hit to broader economic output: This is likely considering the double hit from decreased consumer demand and a reduced labour supply. While parsing consumption by immigration status is difficult, the broader economic impact is clearer. When forecasting the impacts of a four-year unauthorised immigrants deportation policy, average wages are expected to fall by 0.5 per cent and slash GDP by 1 per cent by 2034, according to the Penn Wharton Budget Lab.

  • AI cannot offset the negative labour supply shock: The speed of AI implementation is open to debate. But as of now, the industries in which generative AI is forecast to optimise and improve efficiency in STEM fields, the legal industry, and education training to name a few. Meanwhile, as Tarnell Brown at Econlib pointed out, “Unauthorised workers are concentrated in labour‑intensive, hard‑to‑automate industries; the lost output is not easily offset by capital deepening or native labour”. 

Of course, much of the current economic data doesn’t reflect the other costs of the immigration crackdown, including the reduced attractiveness of the US for higher-skilled immigrants. What we’re seeing unfold with immigration policy ultimately is very likely to come at the expense of American growth.

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