Who is smarter - the individual or the crowd? This is a fundamental question in finance because free market forces are nothing if not the aggregation of the financial interactions of the more than 7 billion people presently inhabiting the planet and it is this "crowd" that individual investors are seeking to outsmart with every trade or investment.
When asked to choose between the two, in keeping with the old adage that "two heads are better than one" most people pick the crowd. In support of this notion James Surowiecki's 2004 book The Wisdom of Crowds used the famous (at least in some circles) anecdote where people attending a country fair were asked to guess the weight of an ox. It turned out that the simple average of all the individual estimates generated a far superior prediction relative to almost all the individuals who participated in the competition - a result that has been replicated on subsequent occasions.
The underlying rationale is that each individual is likely to make an estimation error: some will overestimate the animal's weight while others will underestimate it. But, when aggregated over a large enough sample, these errors cancel out such that the crowd estimate constitutes the most accurate prediction, i.e. the crowd is smartest.
However, the correct answer to the question is that it depends.
Although Surowiecki's book contains many examples highlighting the smartness of the crowd over the individual, he acknowledges this predictive outperformance - the ability to tap the collective wisdom if you like - requires the following four conditions be met:
- Cognitive diversity
Failure to satisfy these four criteria jeopardises the crowd's ability to generate the best estimate or devise the best solution to a problem; often resulting in spectacular fails. As evidenced by numerous asset price bubbles observed over the centuries, a great deal of these fails have occurred in finance, so it is hard not to concur with Surowiecki's conclusion that financial markets are not well suited to exploiting the wisdom of crowds.
But why is that the case?
Going down the list, it is readily apparent that finance satisfies the first two conditions with relative ease: it is a highly globalized industry and the price discovery mechanism itself constitutes the aggregation process. The problem arises with the last two conditions.
Independence and cognitive diversity requires that for the crowd to be smarter not only are the opinions held by individuals in the crowd unaffected by the opinions held by those around them, but that there is a high degree of heterogeneity in how information is processed such that whatever private information is at an investor's disposal (even if it subsequently proves to be faulty) gets incorporated into the market price.
In theory there is scope to increase the smartness of a financial crowd by encouraging greater cognitive diversity amongst investors. That said, our sense (one shared by many others) is that we are heading in the wrong direction given the increasing standardization of financial education and the focus on shorter and shorter investment time horizons, both of which encourage more, not less, investor homogeneity.
The insurmountable problem, however, is that it is simply impossible for investors to be fully independent of each other for reasons we have outlined in previous blog posts. In the ox anecdote, for example, the answer or outcome is not influenced by the guesses of the individual members of the crowd - the ox will weigh 1,198lb regardless of what the crowd thinks.
The same does not hold true in finance because investment success depends not only upon the outcome, but on how much it differs from what was originally expected or anticipated. That is to say, investors must necessarily take on board the opinions of other investors in order to be successful.
The invalidation of the conditions required for crowds to outperform individuals in finance should be welcomed by investors because it allows for the possibility to outperform the market, even in the long-run. The question then becomes how best to exploit the failure of crowds in finance.
One approach is to try and make crowds smarter by identifying key influencers, or individuals with superior track records, and to focus attention on them. The premise being that such individuals have more valuable insights - for example, Albert Einstein and Stephen Hawking without doubt were/are more knowledgeable about theoretical physics than a random collection of people plucked from a shopping mall and hence should be better placed to give superior answers on the subject. This certainly an interesting approach but it requires these individuals be correctly identified - not so easy especially as expertise can be quite topic specific - and remain at the top of their game; both potentially big asks.
A more robust approach, in our view, is simply to accept that crowd failures in finance happen and to seek to exploit those occasions when the probability of such failure is high. To identify potential opportunities we look for occasions when the heterogeneity of investor views is low, which is another way of saying that the correlation of views is high. This is something that can be ascertained from the sentiment indicators we track at Amareos.
By way of an example consider the following exhibit, which plots crowd sentiment towards the S&P 500 index over the past two years. During the sharp sell-off witnessed at the start of the year sentiment towards US equities fell to its lowest level in the post Great Recession period. Investors were all strongly in agreement that the outlook was bearish; a distinct lack of diversity, which flagged a potential crowd fail and hence by extension the prospect of a market rebound. Interestingly, despite the strength of the subsequent rally, crowd sentiment towards US stocks still remains below its long-run average; an interesting observation that we discussed in last week's blog post.
Exhibit 1. S&P 500 - Price vs. Sentiment
Similarly, last December we observed that sentiment towards Brazil plummeted to all-time lows as the country was engulfed in a political scandal that has resulted in President Dilma facing trial for impeachment. Despite the continuation of negative news flow, Brazilian equity markets are up more than 30% year-to-date: one of the strongest gainers in 2016. Again highlighting that when sentiment is strongly skewed - in this example also negatively - it provides a very useful contrarian market signal.
Exhibit 2. IBOV - Price vs. Sentiment
Looking at the sentiment indicators today, the financial asset with one of the most extreme readings is GBP. Like its value on the foreign exchange market, crowd sentiment towards the British currency has slumped in the wake of the Brexit vote (see exhibit below).
Exhibit 3. Sterling: Price vs. Sentiment
Only by knowing what the crowd is thinking in relation to a given asset, and hence being able to monitor the type of conditions where failure is likely to occur, can investors hope to outsmart the crowd - a necessary condition for alpha-generation. Indeed, in our experience the most profitable trades turned out to be the ones with the least initial buy-in (low popularity).
Right now, GBP longs fit right in that camp.
*Sentiment Analytics are based on Thomson Reuters MarketPsych indices.
 Excluding themselves as the individual, of course, to remove the overconfidence bias well-documented in behavioural finance.
 Guessing the number of sweets in a jar is sometimes used instead of the ox example but the implication is the same.
 See: Edward Chancellor's excellent book Devil Take The Hindmost for a comprehensive review of asset price bubbles see: https://www.amazon.co.uk/Devil-Take-Hindmost-Financial-Speculation/dp/0452281806
 The wisdom of crowds theory and the efficient market hypothesis, which states that asset markets incorporate all relevant (including private) information, share some degree of connectedness as they both generate the same conclusion; namely, the impossibility of individuals beating the market over the long-run.
 This was the very point Keynes was making with his famous beauty contest. He pointed out that success required competition entrants not to choose the contestant they considered most likely to win, but to choose the one who they considered others would consider as most likely to win - something he labelled second-degree thinking. Keynes considered the possibility that even second-degree thinking would prove inadequate, as there would seem to be an advantage in engaging in even higher order thinking to outsmart the second-degree thinkers; a process that can be extended ad infinitum resulting in indeterminacy. Fortunately, it transpires that second-degree thinking is more than sufficient because there is evidence from behavioural finance that most investors engage in 1.3-degrees of thinking, meaning that knowing how others (the crowd) are thinking is sufficient information to give investors an edge. The experiment that gave rise to this result can be found in Montier (2007) Behavioural Finance: A Practitioners Guide to Applying Behavioural Finance - see: https://www.amazon.com/Behavioural-Investing-Practitioners-Applying-Finance/dp/0470516704
 Conversely it is a bad news for policymakers because it implies that it is impossible to avoid the periodic booms and busts witnessed in financial markets as their underlying source is deeply woven into the fabric of the investment process; they simply cannot be regulated out of existence.
 As detailed in the following essay these approaches are seeking to exploit "metaknowledge" - see: https://aeon.co/essays/a-mathematical-bs-detector-can-boost-the-wisdom-of-crowds
 To avoid suspicion of only being wise after the fact we articulated this view in a blog post published on January 20 - see: https://amareos.com/blog/just-one-thing-you-need-to-know/
 Again, we discussed this in a blog post at the time - see: https://amareos.com/blog/time-to-buy-beleaguered-brazil/
 The price shown is the BoE calculated nominal trade-weighted exchange rate not a traded rate.
 It is also is important for risk mitigation because understanding the crowd not helps with market timing but also position sizing - a much overlooked, but critical, element in any investment process.