I have been half-joking for a year and a half that maybe index funds should be illegal, but here is an almost entirely serious claim from Sanford C. Bernstein & Co. that they are worse than communism:
In a note titled “The Silent Road to Serfdom: Why Passive Investing is Worse Than Marxism,” a team led by Head of Global Quantitative and European Equity Strategy Inigo Fraser-Jenkins, says that politicians and regulators need to be cognizant of the social case for active management in the investment industry.
“A supposedly capitalist economy where the only investment is passive is worse than either a centrally planned economy or an economy with active market led capital management,” they write.
The basic idea is straightforward.1 The function of the capital markets is to allocate capital. Good companies’ stock prices should go up, so they can raise money and expand. Bad companies should go bankrupt, so that their resources can be re-allocated to more productive purposes. Analysts should be constantly thinking about whether companies are over- or underpriced, so that they can buy the underpriced ones and sell the overpriced ones and keep capital flowing to its best possible uses.
But when those thoughtful active analysts are replaced with passive index funds, the market stops serving that function. Whatever the biggest company is today will remain the biggest company tomorrow, and capital will never be allocated from bad uses to good ones. Indexing is cheaper, yes, but that’s because active management has positive externalities, and if no one will pay for it, those benefits will disappear.2
There is a lot of debate over whether this is actually how it works. For one thing, public stock markets are not really a mechanism for raising capital any more.3 But more fundamentally, there is an alternative view that the rise of passive investing will improve capital allocation, because bad active investors will be driven out but good ones will remain.4 The passive investors can’t influence relative prices, since they just buy the market portfolio, meaning that the fewer but better active investors will continue to make the capital allocation decisions. On this view, lower returns to active management are a sign that prices are more efficient and capital allocation is getting better.5
Fraser-Jenkins et al. don’t buy it.6 Their worry is that the growth in passive and quasi-passive products — not just true index funds but “smart beta” funds that invest based on historically predictive factors – has caused markets to become more correlated, as all the passive funds buy all the same stocks for the same reasons. They are not alone here; I like to quote Nevsky Capital’s final investor letter:
In such a world dominated by index and algorithmic funds historically logical correlations between different asset classes can remain in place long after they have ceased to be logical.
“By definition,” write Fraser-Jenkins et al., “passive flows of capital, given that they seek to emulate or replicate what has already occurred must be backward looking.” And a market that is more correlated, they argue, will do a worse job of allocating capital.7
Anyway it is a fascinating and delightful note but now let’s talk about something slightly different.
Imagine you are in charge of the economy. You decide how much of everything people should produce, and what the prices should be. It is hard! It’s hard to find out how much of the different things people want, and how much everything costs to make, and how to motivate people to make things, and so forth.
There are three basic approaches that you can take8:
- You can be bad at it. You can just announce prices and quantities, and get them wrong, and there will be shortages and bread lines and corruption.
- You can be good at it. But I just said it was hard, so being good at it probably requires you to have a really fancy computer that takes lots of data and crunches it to decide on prices and quantities and so forth.9
- You can have a market. You can just think of a market as a giant distributed computer for balancing supply and demand; each person’s preferences are data, and their interaction is the algorithm that creates prices and quantities.10
Choice 1 is more or less actually existing communism.11 Choice 3 is more or less capitalism.12 Choice 2 is more or less a fantasy, but the problem of figuring out how the computer would work is sometimes called the “socialist calculation problem,” and there is a shockingly wonderful novel about it, Francis Spufford’s “Red Plenty.”
The capital allocation problem is a subset of that more general resource allocation problem, and has similar answer choices: You can have clunky central planning, or you can have a market where investors compete to buy securities and thus set prices, or you can have an ideal but as-yet-undiscovered computer do the allocating. Or I guess13 pure indexing — everyone passively throws money at everything that there is, with no judgment at all — is an imaginable fourth answer, and is strictly worse than the others.14
But the Bernstein note isn’t really about pure passive indexing, just buying and holding the market-cap-weighted portfolio of global financial assets. Not many people do that anyway. Instead they buy a S&P 500 index fund, say, which is a market-cap-weighted portfolio of large-cap U.S. stocks — itself a capital-allocation decision. Or they buy a smart beta fund, which is a portfolio of stocks chosen and weighted based on some set of factors that have historically determined performance. Fraser-Jenkins et al. note ”the bizarre situation that there are more indices than there are large cap stocks.” They can’t all just be throwing money at every stock with no judgment. There is something a bit more going on there.
One way to think about them is that they are all crude algorithms for picking the best companies to allocate capital to. True, diversified, market-cap-weighted index funds are the crudest algorithm. They essentially assume that the companies that were good yesterday will probably be good tomorrow. This is not entirely true, of course, but it’s true enough to be useful, or at least to outperform most human money managers most of the time.
But there is no need to stick with such a crude algorithm. You might notice that, historically, some factors have been associated with outperformance. Companies with low price-to-book ratios might have outperformed companies with high price-to-book ratios, most of the time. So you might invest in a smart-beta value fund that focuses on buying stocks with low price-to-book ratios. If you do that, you are making a capital-allocation decision; you are giving money to companies that you think the market undervalues, whose fundamental performance should justify higher prices.
Even that is pretty crude, though. You could get more nuanced, and invest in a fancy quantitative hedge fund that digs through mountains of data to find signals that have historically predicted stock prices, and then applies those signals to future prices.
As these algorithms get more complicated, they also get more expensive to implement. S&P 500 indexing is basically free. Smart beta is more expensive, but everyone expects the price of smart beta to eventually fall to, basically, free.15 Fancy algorithmic hedge funds are expensive, but they are perhaps being disrupted by hobbyist sites that let random data scientists build algorithms to predict future stock prices, and then allocate money to the best-performing ones.
In Fraser-Jenkins’s taxonomy, all of these algorithms more or less count as “passive,” because they all look at historical correlations to predict future returns, as opposed to an “active” style that attempts to predict future returns based on a fundamental analysis of real economic factors.16 But that distinction is not particularly clean. A smart-beta fund focused on the value factor is in a sense doing very crude fundamental analysis: It looks at a company’s financial statements, compares them to its stock price, and buys stocks that seem to be mispriced based on their fundamentals. My Bloomberg View colleague Noah Smith wrote today about two financial economists who published a more sophisticated fundamental-investing algorithm — one that uses 28 items from financial statements — that seems to outperform the market. You could implement that algorithm “passively,” as it were, but it seems to be making investing decisions based on where it sees fundamental mispricing, not just on past stock prices.
And of course any human active investor is mostly relying on historical correlations and pattern-matching to make predictions of future fair value. You invest in Twitter because you think it will be the next Facebook, or you don’t invest in Twitter because you think it will be the next MySpace; you go long oil companies because real-economy conditions remind you of the last time oil rallied, or you go short because those conditions remind you of the last time oil tanked. Human investors reason by this sort of informal empiricism; robot investors just formalize it.
One broadly plausible thing to expect is that, in the long run, the robots will be better at this than the humans.17 Another broadly plausible thing to expect is that, in the long run, the robots will keep getting better at it.
What does it mean to say that the robots will keep getting better at it? Surely it means that robots will become more accurate at allocating capital to businesses that will perform best in the future. They will make those decisions partly by looking at the prices of financial assets (correlations among stock prices), and partly by looking at fundamental financial data (correlations between companies’ stock prices and their financial statements), and partly by looking at operational data (correlations between retail-industry stock prices and satellite pictures of retailers’ parking lots), and partly by looking at macroeconomic data (correlations between stock prices and interest rates or oil prices), and partly by looking at whatever else is handy and might somehow predict stock prices (correlations between stock prices and sunspots, or Twitter sentiment). And as more data is available and analytical techniques improve, they will get better and better at all of this. Along the way, there will be missteps and spurious correlations and herding into bad ideas, but in the very long run you’d expect the robots to constantly improve their capital-allocation decisions.
I mean, I would, though I don’t assert it as a law of economics or computer science. It’s more of an aesthetic sense about the possibilities for technology.
One other thing to consider is that eventually the best robot will predictably and repeatedly outperform the second-best robot, so why would you invest with the second-best robot? (This is, to some extent, what it means when people say that returns to algorithmic investing are declining.) Modern investment management supports a diversity of investing styles and products in part because people have truly different preferences about risk and where they want to invest, but also in part because it is hard to tell which style will perform better in the future. But as the Best Capital Allocating Robot gets better and better at allocating capital, it will be harder to justify investing in the Concentrated Mid-Cap Ultra Value Fund or whatever. Just invest in the Best Capital Allocating Robot!18 He’s the best.
So the logical/whimsical end point is, if you want to invest in U.S. business, you give your money to the Best Capital Allocating Robot (U.S. Division), and that robot — whose prowess has been proven over time in fierce competition — applies the best algorithms to the best data set to make the best possible capital-allocation decisions, and you get the best returns, and the economy gets the best capital allocation.
Obviously this is all nonsense. I mean! Obviously! The robots will always be imperfect, and random chance will always intrude, and decisions based on past data will never perfectly predict the future, and investing preferences will always differ, and you’ll never be able to scientifically identify the best algorithm, and competition and diversity will always be important, and all of this is silly.
But isn’t it fun? I have joked, a couple of times, about modern financial capitalism solving the socialist calculation problem. One of those times was about Uber, which is apparently working on an algorithm to allocate cars based on data in the world, without the intermediation of a price system. There will just … magically …be more Ubers when demand is high, and fewer when demand is low, and that won’t be because the invisible hand of the market pulls more self-interested drivers onto the streets as more passengers bid up the price of their service, but just because Uber has a computer program that is really smart at telling cars where to go. The Best Capital Allocating Robot will be like that, only for financial capital instead of cars.
That is: The market is the best algorithm ever developed for allocating capital. So far! But it also creates incentives for someone to build a better algorithm.
Again: I know this is silly. But as a wild extrapolation of the far future of financial capitalism, I submit to you that it is less silly than the ”Silent Road to Serfdom” thesis. That thesis is that, in the long run, financial markets will tend toward mindlessness, a sort of central planning — by an index fund – that is worse than 1950s communism because it’s not even trying to make the right decisions.
The alternative view is that, in the long run, financial markets will tend toward perfect knowledge, a sort of central planning — by the Best Capital Allocating Robot — that is better than Marxism because it is perfectly informed and ideally rational. And once you have that, you can shut down the market: The game is over, and the Best Capital Allocating Robot won. The Fraser-Jenkins thesis is that algorithmic investing runs the risk of destroying capitalism by abandoning the pursuit of knowledge. But the really fun alternative is that it runs the risk of destroying capitalism by perfecting that pursuit: Once you have solved the socialist calculation problem, what do you need markets for?19
1. I’ve sort of argued something similar in the past, though my views have mellowed over time.
2. From the Bernstein note:
Some would suggest that because the average net-of-fee return from active management is less than that for passive that the fee paid for active management is a net drain on society. This is a non sequitur. A given investment in active may or may not be the best decision for an individual particular investor but for the system overall there is a benefit in the efficient allocation of capital. This can come directly through the provision of equity capital or in forcing the dissemination of information that is crucial for the raising of capital through lending or credit markets.
3. Fraser-Jenkins et al. acknowledge this, but point out the secondary effects of equity markets on other forms of capital raising:
However for mining, and indeed for other capital intensive sectors of the economy, it is no longer in the requirement to source equity for initial capital investment that the efficient functioning of the capital markets is important. Very few of the major mining companies actually raise significant amounts of cash directly through the equity markets. However it is the market value of the companies that determines the level of indebtedness that they can support and thus their overall spending plans and investment rate. So if anything this role requires a more rather than less efficient functioning of the equity markets.
I’d add that efficient public equity markets probably make it easier for private companies to raise money with an eye on an eventual IPO exit.
I’m going to argue that the trend towards passive management is not only sustainable, but that it actually increases the accuracy of market prices. It does so by preferentially removing lower-skilled investors from the market fray, thus increasing the average skill level of those investors that remain. It also makes economies more efficient, because it reduces the labor and capital input used in the process of price discovery, without appreciably impairing the price signal.
5. There is a Grossman-Stiglitz problem here but, you know, not yet.
6. In particular, they don’t buy the skill argument:
It is notoriously hard to identify outperforming managers ex ante and many frictional inefficiencies in the allocation towards managers also suggest that in practice it is unlikely that it is always the worst manager who loses assets in any marginal allocation to passive. If, as is more likely, it is a manager with a random level of skill who loses out then this argument would not hold and in fact there would be a reduction in the AUM of potentially skilled asset allocation.
Nor do they think that the problem is necessarily self-correcting:
We are often asked whether we reach a point at which the market becomes so inefficient that the opportunities for active management become unstoppable in forcing an active recovery. So do we ever reach this “active nirvana?” maybe not. Phenomena that only become evident long after the event do not easily lend themselves to quick mean-reversion and individual participants would seem to have little power to bring to bear on the point. Moreover, there might not be any natural mean- reversion because the commercial imperative of passive and active asset management is very different when it comes to scale. These businesses have a different natural size. Passive management requires scale in order to cut the fees charged to the levels that we see today and this pressure will always be there. Active management, by contrast, will always have a capacity constraint. The size of that constraint will be different for a concentrated 15 stock equity fund versus a multiasset index fund, but both of those strategies have constraints nonetheless. Thus the industry might not have a self-correcting equilibrium process between active and passive given these different forces at work in terms of natural scale.
7. The note actually argues, not that passive investing has led to higher correlations, but that it has led to higher spikes in correlations:
Consider a market that undergoes an increase in the proportion of assets managed passively from one period to the next. In the second period more securities will be trading in line with a macro view (ie how they are priced with regard to an index or ETF product, say) rather than with respect to “fundamentals”. Therefore, over the course of the transition from period 1 to period 2 the average pairwise correlation of the securities would have increased. But that means that in period 2 there will always be a small group of active managers who will spot the mis-pricing of securities and put trades that will eventually nudge the securities back to their fundamental level accordingly. The result of all this would be a spike in correlation that eventually mean-reverts. It would imply that when such a spike occurs that it is larger if the passive asset share of that market is larger.
Is there any evidence of this happening in practice? We think that there is.
I am actually not sure why that would be so bad?
8. Obviously you can mix the approaches, etc.; here we are being very schematic indeed
9. A famous paper is by Oskar Lange.
11. Incidentally the Fraser-Jenkins note has a long discussion of Marx’s theory of use-value that strikes me as inessential to all this; you could have central planning of the economy without Marxism, and in fact it seems to me that autocratic rulers with centralized economic power predate Marx.
12. I mean, “capitalism” and “market economies” are not strictly synonymous, but let’s not get into that now.
13. Actually the Fraser-Jenkins note derives a model of capital allocation in a society without a financial sector — where entrepreneurs just reinvest their earnings in growing their business, without borrowing or equity issuance — but we do not need to get into that.
14. As Bloomberg’s Luke Kawa puts it:
Seen through this lens, passive management is somewhat tantamount to a nihilistic approach to capital allocation.
To adapt a line from a Coen brothers classic: Say what you will about the tenets of Marxism, Dude, at least it’s a formal attempt to direct capital to achieve a desired end.
15. Including Fraser-Jenkins et al.: “Yes, we accept that the cap-weighted index is in a sense the only true passive index as it is the only index that all investors can buy, but declining costs of smart beta mean that it will soon be possible to buy smart beta for the same fee as traditional passive.”
16. The note explains the difference:
By having an understanding of where the “fair value” level ought to be it is possible to seek to profit from this through investing capital (or withdrawing it) in proportion to the extent that the prevailing price level departs from that “fair value level” at any point in time. This requires an investment philosophy that is “active” in so far as it is forward looking and grounds its investment decisions in an effort to understand the dynamics of the real economy.
We would say that the “passive” style of investment is paradigmatically opposed to this approach. Rather than looking at the real economy and seeking to understand its future development, passive asset allocation self referentially looks to the financial economy to inform its asset allocations choices. It is necessarily backward looking rather than forward looking and invests based on information gathered from how other financial agents have invested over some historic horizon. Based on this, it does not seek to discover “fair value” itself but simply seeks to allocate more capital to those sectors which appear to be out or underperforming based on the recent past.
17. Broadly plausible! Not inevitable. “No man is better than a machine, and no machine is better than a man with a machine,” says Paul Tudor Jones, which is one hypothesis.
18. And, like, lever him up to move along the efficient frontier, or whatever.
19. Yes, I know, the answer is “freedom,” but we are dealing in some pretty silly abstractions here, cut me some slack.