The Wisdom (???) of Crowds

The notion that markets aggregate the opinions of many and thereby make superior estimations of value has a very long history. It's certainly at the root of the infamous Efficient Markets Hypothesis, which claims that markets gather and process information so efficiently that price movements have no predictable patterns and prices of financial instruments always reflect something very close to the true fundamental value of the assets in question. More recently, The Wisdom of Crowds has been the driving force behind prediction markets. One one way or another, this notion lurks behind the slippery and insidious idea that "markets know best" and that pretty much everything from water distribution to higher education should be organized as a market. 

But in his bestselling book on the topic, James Surowiecki was somewhat careful at the outset to acknowledge that the idea only works in some rather special situations (not that readers paid much attention). A crowd estimating the number of marbles in a jar or the correct price of a stock will only get superior results -- superior in accuracy to the guess of any one individual, and even of experts -- if the people are on average unbiased in their estimates; it won't work if they tend systematically to estimate too high or low. Moreover, the people have to make their estimates independently of one another. Any kind of social influence, one person copying or even being slightly swayed by the actions of another, also spoils the result. Wise crowds very quickly become dumb herds.

For an idea of such broad influence, it's surprising how few experiments have been done to probe in detail around the boundaries where wise crowds become unwise, how it happens and which are the key effects. This has been rectified by an impressive set of experiments carried out by Jan Lorenz and colleagues from ETH-Zurich, and published recently in PNAS. Their idea was to use a crowd of 144 student volunteers and have them perform estimation experiments in a range of conditions. They gave the participants monetary incentives to estimate accurately, and chose questions (on things like geography and crime statistics) for which the true answers are known. Then, in some trials, participants made their estimates on their own, without having any idea about the estimations of others, and in other trials, they were either informed in complete detail of what others had estimated or given at least average information on the others' estimates. The idea was to compare how well the crowd made estimates in the absence and presence of social influence.

What the results show is that social influence totally undermines the wisdom of crowds effect, and does so in three specific ways. It's interesting to consider these in some detail to see just how this whole "wise crowd" illusion falls apart in the face of a little social influence:

1. In what the researchers call the “social influence effect,” the mere act of listening to the judgements of others led to a marked decrease in the diversity of the participants estimates. That is, the estimates of the various people become more like one another -- people adjust their views to fit more closely with others -- but this does very little to improve the collective accuracy of the crowd. In effect, people think they are sharing information, but little information actually gets shared. The figure below illustrates what happens: in successive trials, a measure of the group's opinion diversity decreases dramatically if people hear either full or average information on the estimates of others, meanwhile the collective error decreases only marginally.

2. A second and even more interesting effect is what the researchers call the “range reduction effect.” Imagine that a government tries to use the wisdom of crowds, assembling a group and surveying their opinions, hoping to get a range of views and some idea of how much consensus there is on some topic. You would hope that, if the crowd's estimate was NOT accurate, this lack of accuracy would be reflected in a wide range of estimates from the individuals -- the wide range would signal a lack unanimity and confidence. A truly bad outcome would be a crowd that at once gives a very inaccurate estimate and does so with a narrow range of opinion differences, signalling apparent strong certainty in the result. But this is precisely what the research found -- in the social influence conditions, the individuals' estimates didn't "bracket" the true answer, with some being higher and others lower. Rather, the group narrowed the range of their views so strongly that the truth tended to reside outside of the group's range -- they were both inaccurate and apparently confident at the same time.

3. Finally, and worse still, is the “confidence effect”. The researchers interviewed the participants in the different conditions, asking them how confident they were in the accuracy of the group's final consensus estimate. Social influence, while it didn't make the crowd's estimate any more accurate, did fill the participants with strong confidence and belief in improved accuracy. Think 2005, housing bubble, mortgages with no income and no assets, etc. As hard as it is to imagine that people could have believed the market could not fail to go up further, most did. And they did in large part because they saw others apparently believing the same thing.

Altogether, this careful study points more toward the idiocy of crowds than their wisdom. Social influence is hard to eradicate. Even in markets, supposedly driven by anonymous individuals making their own estimates, lots of people are reading the newspapers and news feeds and listening to analysts, and, even when not, looking to price movements and using them to infer whether someone else may know something they don't. In these experiments, social influence makes everyone think and do much the same thing, makes it likely that the consensus view aims well wide of the actual truth, and, perversely, makes everyone involved increasingly confident that the group knows what it's doing. Some kind of Wisdom.

How to erase memories

I'm not sure how much relevance this new bit of research has for finance and economics -- quite a lot, I suspect, given the social nature of interpersonal influences, which certainly affect economic outcomes -- but its conclusion is quite striking regardless. Our memories: they can be easily erased or manipulated by social influence, by people around us simply telling us outright lies (or their own false recollections).

Most of us, often, suffer from the illusion that our memories are fairly accurate, especially of things we've experienced first hand. Remember that huge football or baseball game your favourite team won or lost 10 years ago? Remember who made the biggest play? Our memories of these things aren't nearly as good as we think. Countless studies have shown that eyewitnesses are notoriously poor at remembering key facts accurately. A few years ago I got hold of an old recording of a Washington Redskins Superbowl victory from 20 years ago -- the details of which I thought were etched with prefect accuracy in my brain. I was stunned on watching to find out that I had mis-remembered who had made big plays, where they were on the field, when in the game the plays happened, and so on.

What happens in remembering sporting events happens in remembering the rest of our lives too, I'm afraid, and this new set of experiments shows just how easily our memories can be altered by the social influence of people around us. The paper is very well written and doesn't need much explanation. Micah Edelson and colleagues from the Weizmann Institute of Science in Israel had volunteers watch an eyewitness documentary, and then several days later tested their ability to recall facts without any interference, or after being presented with memories as recounted by some other individuals. From their abstract:

We examined how socially induced memory errors are generated in the brain by studying the memory of individuals exposed to recollections of others. Participants exhibited a strong tendency to conform to erroneous recollections of the group, producing both long-lasting and temporary errors, even when their initial memory was strong and accurate.

More profoundly, the study went on, using functional brain imaging, to look at the sites in the brain where these memory changes took place. The volunteers weren't merely reporting something they didn't actually remember just to fit in; their brains actually changed under social pressure, so they remembered something different.

This reminds me of another fascinating result from a few years ago in experiments run by a team led by Gregory Berns of Emory University, who re-examined the famous 1950s experiments on social conformity of Solomon Asch. Berns and colleagues did the experiment in such a way that they could tell that conforming volunteers -- who were effectively discarding their own observations in favor of those reported by others -- weren't just trying to fit in. Social pressure actually made them see the world differently, and specific mechanisms in the brain made it happen.   

As Edelson and colleagues note, this new effect has long been discussed in the social psychology literature and is known as "memory conformity" -- our memories, like other aspects of our behaviour, conform to social pressure. As I said, I don't know immediately how this fits into economics and finance, but it must have some pretty important consequences. Conformity is certainly one mechanism by which all manner of social trends get started, amplified and perpetuated.

As a British friend of mine told me in 2005 -- having just taken out a mortgage on a third speculative property purchase -- "housing prices never go down".  I don't think he had done any independent research to establish this as fact. But he had been reading and listening to the prevailing atmosphere of ideas -- and his brain had been physically altered as a result.

How derivatives make markets unstable: Part I

I posted a while back on some of the dirty secrets of the derivatives industry. I promised then to give a little more discussion at some point of two terrifically important pieces of research -- still not widely known, especially in mainstream finance -- which show how adding more derivatives to a market can make it less stable, not more stable. This goes directly against the received wisdom of economic (equilibrium) theory which claims that markets become more efficient as they become more complete, i.e. as it becomes possible to take essentially any kind of market position by virtue of a dense spectrum of financial instruments.

One of the papers I had in mind was this landmark study from several years ago in which William Brock, Cars Hommes and Florian Wagener considered the question of whether, in the run up to the recent crisis, "... highly leveraged positions using complex financial instruments may have amplified market volatility." The answer to which their analysis leads is -- yes, quite probably. More generally, they illustrate how more derivatives in general should make markets more unstable, increasing volatility.

Their paper is a little technical, but worth a read. I'll outline the gist of their argument, which starts with several straightforward observations and moves to a not-so-obvious conclusion:

Observation 1: They start by noting that people aren't the hyper-rational automatons of Milton Friedman's (or other neo-classical economists') favorite fantasies. Rather, people in the real world form their expectations and craft their behaviour in an adaptive way -- that is, they learn from experience.

Observation 2: They also note that people aren't identical. We not only learn, but our brains are different and we've all had different experiences in the past, so, at any moment, we've probably learned different things and have slightly different expectations (heterogeneous expectations, in economic lingo) about the future.

Observation 3: People are generally risk averse -- if they're willing to bet $100 on a gamble that could pay off, but involves risks, they'll be willing to bet more than $100 in the same gamble if you reduce the risks. In other words, people shy away from gambles more the riskier they are. This is basic empirical psychology.

Starting from these observations, Brock and colleagues then consider an "intertemporal" asset market (economist-speak meaning a market in which time exists) in which a lot of people look to past prices and try to predict future prices, buying and selling as they see fit. This market contains both risky and non-risky things to invest in -- stocks and risk-free bonds (which are guaranteed to increase in value by a factor R>1 over each interval of time). Stocks might rise more, but are less certain and hence riskier. In addition, the people can buy derivatives -- instruments which act like pure bets and give a pay off in certain circumstances.

What this all amounts to is that people in this market can 1) play it safe by buying bonds, 2) gamble more by buying stocks, and also 3) buy derivatives if they want which (in this model) have no effect except to offset some of the risks involved in buying stocks.

What Brock and colleagues then show is that the combination of the derivatives, the risk aversion of investors, and their tendency to learn by "reinforcement" -- to be more likely to follow strategies which have paid off in the past -- leads directly to trouble. I'll describe how in a moment, but one final thing before I do: the strength of reinforcement learning in the model (how quickly people shift to use better performing strategies) is controlled by one parameter β; bigger β means faster switching. In previous work, Brock and Hommes have shown that in an asset market in which people learn by the reinforcement process, there is a natural "tipping point" -- at a certain critical value of β -- where the market goes from being stable to being unstable. Intuitively, when people switch too quickly, taking even scanty short term evidence as proof of a strategy's superiority, fluctuations in the market become much stronger.

OK, so what happens in this market when you currently have, say, 15 possible derivatives covering lots of different possible outcomes, and now add a 16th derivative to cover other outcomes (i.e. we have derivatives on stocks and commodities, and suddenly invent some new ones to cover mortgage bonds)? Brock and colleagues show that the addition of this one new derivative makes the market go unstable more quickly, i.e. at a lower value of β. The mechanism involves a simple interplay of reduced risk and human confidence. This new derivative, by making it possible for investors to lower the risks associated with investments, leads them to invest more money. They take bigger bets. These bigger bets naturally amplify how quickly the bets that turn out to be correct amass profits. So, there are bigger differences in the payoffs to recent winning and losing strategies, which draws more followers to the winners more quickly (even if the fundamental switching rate of people haven't changed).

In brief: by the very act of reducing the risk of some strategies, the derivative invites more vigorous gambling on that strategy, leading to faster flows of people from one strategy to another. The extra derivative makes the market more volatile.

This model doesn't involve many questionable assumptions. It's a very basic model of the most central facts of any market, respecting some realities of human psychology. It suggests that derivatives hold inherent dangers. Yet as far as I can see, the ongoing discussion of regulating derivatives isn't taking this perspective into account. As Satyajit Das notes, the drive toward greater returns that is an essential part of the dynamics in the Brock, Hommes and Wagener model is a very real force in today's derivatives markets:

Investors searching for return drive speculation. Concerned about stagnant real incomes and inadequate retirement savings, individual investors seek out higher yielding investment structures, often based on derivatives. Pension funds and other institutional investors use derivatives to enhance returns to fully fund and meet their contracted liabilities. In an environment of diminishing returns and fierce competition for attractive investments, fund managers use derivative strategies to enhance returns through readily accessible leverage and capacity to create risk “cocktails”.

Facing increased pressure on earnings, corporations have increasingly “financialised”, resorting to speculative derivative trading to meet profit expectations. ... [Such] seculative activity amplifies rather than reduces volatility and systemic risks. Perversely, this may impede capital formation and also increase the cost of capital for companies.

What happens in the real world backs up the lesson of this simple model. Derivatives reduce risks only in a very narrow and restricted sense, while undermining the functioning of markets more generally. Of course, there's lots of money to be made by the people selling derivatives, so don't expect them to admit (or care about) any of this.

Bank runs begin in Greece and Ireland

Gavyn Davies refers to the image below, which presents a rather disturbing trend in bank deposits in Greece and Ireland. Notably, banks in these two countries in the past year or two have experienced a sharp increase in withdrawals of retail deposits:

Davies suggests they've lost 15% of their deposits, but it could be significantly worse than that -- note that the data in the figure only goes up to around December 2010. Extrapolate the trend through to today and I'm guessing the loss is approaching 30-35%.

Fully one third of the retails deposits in these two nations have been pulled out?! Yikes. Not a good sign. As Davies comments:

As the UK government found in the case of Northern Rock, the appearance of queues outside banks is one of the worst nightmares which a central bank can face. It has not happened in Europe – yet.