Luck and Skill in Financial Markets and Beyond

In the heat of the financial crisis Philip Falcone, billionaire hedge fund manager, testified in front of Congress. He said:

“I take great pride in my upbringing, and it is important for the committee and the public to know that not everyone who runs a hedge fund was born on Fifth Avenue. That is the beauty of America and the beauty of the potential in our industry… Through hard work and perhaps a little bit of luck, Harbinger Capital Partners has been able to generate substantial returns for our investors since 2001.”

In Falcone’s view the strong performance of his fund up until that time was attributable to hard work, and perhaps a little bit of luck. Daniel Kahneman, Nobel prize-winning psychologist, has a different view. In his book, Thinking Fast and Slow, he writes:

“A major industry appears to be built largely on an illusion of skill …Professional investors, including fund managers, fail a basic test of skill: persistent achievement… the evidence from more than fifty years of research is conclusive: for a large majority of fund managers, the selection of stocks is more like rolling dice than like playing poker… The successful funds in any given year are mostly lucky; they have a good roll of the dice.”

So which is it – luck or skill?

Luck rears its head within many professions – sport, business, politics, even science. But there are few areas outside financial markets where the debate is as loud. In some of those other areas that’s because luck plays a relatively minor part. Such is the case in jobs that harness skill to conduct repetitive tasks in a highly predictable environment, like dentistry, as Nassim Taleb might point out. In other areas luck plays such a dominant role that people are scared to confront it for want of giving up perceived control. In those areas – politics for example – participants construct a narrative to fit the facts, more often than not discounting luck completely.

Financial markets sit somewhere in between. They are special because outcomes can be perfectly quantified to an extent they can’t in other areas. Yet the correlation between the payoff on a trade and the skill incurred in developing it is not straightforward:

There are cases where a trade predicated on a low level of skill – a hunch if you will – pays off dramatically. Bloomberg recently highlighted the story of one man, trader Steve Oliverez who “working with a data set of one” made a call on US government policy that allowed him to turn a US$100,000 trade into a US$2.5m profit.

There are cases where a well-developed thesis doesn’t pan out according to plan. The example of Volkswagen springs to mind. In September and into October 2008 ordinary shares of the German carmaker ramped higher and higher, against the backdrop of weakening fundamentals that were affecting the wider market, all other carmakers and even Volkswagen’s class of preference shares. Many hedge funds including Greenlight Capital and Viking Global sold the stock short on the rationale that fundamentals would reassert themselves and the stock would go lower. But it didn’t. For highly technical reasons the shares ramped even higher, at one point irrationally making Volkswagen the largest company by market capitalisation in the world. The hedge funds lost around €1.2bn.

And there are cases where a thesis turns out to be entirely wrong, but the trade turns out OK regardless. This is what happened to Dan Loeb, another billionaire hedge fund manager, in 2017. Halfway through the year he said:

“I guess [it’s] a case of better lucky than right. We expected the market to go up but for different reasons… So, I’m happy with the outcome. It was different from what we anticipated, but we’ll take it.”

Right for the wrong reasons; wrong for the right reasons

These cases are variations of right for the wrong reasons and wrong for the right reasons. They illustrate that rather than representing a single pursuit, financial markets actually consist of no fewer than three distinct games. The first involves developing a fundamental insight, the second involves navigating market psychology, and the third involves sizing the resultant trade appropriately. Keynes’ beauty contest analogy captures well how the first two of these come together. Some investors focus more on the first game – those in venture capital and private equity, for example. Some focus more on the second – day traders and trend followers. The very best investors focus on both. Warren Buffett, on business fundamentals, has said “It’s far better to buy a wonderful company at a fair price than a fair company at a wonderful price” and on market psychology has said “be fearful when others are greedy and greedy when others are fearful”. The third of these games is probably the most underated of the three, even among practitioners.

The complexity engendered when these three games overlap blows out the range of outcomes that can be observed. Unlike in the dentistry profession where the variance of outcome is fairly tight, in financial markets the variance can be extremely wide relative to the measure of skill that goes into executing a specific trade.

Which is why there is so much introspection around the role of luck. On the one side there’s Kahneman saying it’s all luck; on the other side there’s Falcone saying it’s all hard work, and perhaps a little bit of luck.

The problem is that the actual split between luck and skill is difficult to extract. Nobel prize-winning economist Robert Shiller once told writer Morgan Housel that the thing he most wants to know about investing that he can’t is “the exact role of luck in successful outcomes.”

It takes time

The difficulty comes from the long-tailed nature of investment decisions, with feedback coming long after the initial trading decision has been executed. This ‘feedback lag’ is described by Eric Beinhocker in The Origin of Wealth. He writes that “learning the information ratio of a strategy takes time. If one assumes that returns are normally distributed (a bell curve) then the laws of statistics mean that it would take four years of data to be 95% confident that a trader’s strategy had an information ratio of 1… If the returns have fat tails (as data shows they do) then it takes even longer. Thus the rule of thumb, common among traders, that it takes five years of performance to know whether a strategy is any good or not is probably about right. This timescale is further lengthened by the ‘millionth monkey’ problem. If enough traders are trading, then the odds are high that one of them will have a good five year run just by pure luck, further lengthening the time to confidently identify abnormally profitable strategies.”

In a recent analysis, Newfound Research suggests that the time required to parse luck from skill could be longer. The author calculates that it takes 27 years of data in order to establish whether a portfolio manager has what it takes to beat a 2% hurdle rate with the same 95% degree of confidence. The problem here is that few fund managers stick around for anything close to 27 years. Data from Citywire reveals that only around 1% of UK-based fund managers have more than 20 years’ experience, with only 17% having more than 10 years.

Even where there is sufficient historic data to make a case, it is still difficult to draw conclusions. That’s because skill, or hard work, may be transient. Managers could lose their edge as market conditions shift; they could lose motivation or become susceptible to overconfidence; they could reduce risk in order to protect their reputation or their fees. The longer it takes to build up a time series of data, the more exposed the manager is to falling foul of one of these conditions. Consequently, an analysis of persistent achievement over time may not capture all of the skilled managers in its net (yet it would capture all the lucky false positives).

Recognising the role of luck

Fortunately, and perhaps unsurprisingly given how much resource is expended doing it, there is evidence that skill makes a difference in financial markets. Although the average fund manager may not outperform, a significant minority of managers do. A paper published in Financial Analysts Journal in 2011 sifts through all the literature. It shows that after adjusting for various factors, superior fund managers can be identified by analysing past performance. It also highlights several other tools for assessing the propensity for fund managers to outperform, notably macroeconomic correlations, manager characteristics and analyses of fund holdings. Indeed, given the opportunity cost incurred waiting for past performance data to roll up these other tools may be more useful.

Precisely how much is skill and how much is luck is a source of continued debate that is not likely to diminish any time soon. The very best investors at least recognise the role of luck in their performance – and they’re not just being humble. Howard Marks, Founder of Oaktree Capital Management, wrote a memo in January 2014 entitled Getting Lucky in which he concludes “skill and luck will both continue to play very important roles.” Jim O’Shaughnessy, Founder of O’Shaughnessy Asset Management, tweeted last year: “I know I don’t know exactly how much of my success is due to luck and how much is due to skill. I do know that luck definitely played, and will continue to play, a fairly substantial role.”

It’s likely no coincidence that superior fund managers pay homage to luck. Psychological research written up as long ago as 1971 demonstrates that “whether a person believes the outcomes of [their] decision are dependent upon skill or chance influences the riskiness of their choices.” A manager lacking respect for luck may be disposed to taking excessive risks.

The increasing influence of luck in business

Such respect for luck could usefully be employed in fields outside of financial services. While the preponderance of data fuels the debate within markets, the influence of luck is no less relevant elsewhere. It’s easy to see why luck is often ignored. Denying it bolsters people’s sense of control and can even be seen as adaptive if it promotes greater effort. Which parent wants to instil in their child the idea that hard work may not pay off? But discounting luck completely fails to reflect reality. In fact, not only is luck’s influence on events underappreciated, in some fields that influence may actually be increasing.

One of those fields is business, where the impact of luck is growing as winner-take-all markets gain dominance. Economist Robert Frank addresses this theme in his book Success and Luck. He argues that historic reductions in shipping costs have created more competitive markets and more concentrated production across a range of industries. Technology is accelerating that trend. In many industries an increasing share of a product’s value is accounted for by the ideas embedded in it. In industries such as sport, entertainment and technology itself, feedback loops have the capacity to catapult some players, and often a single player, into a market-leading position. The trigger for those feedback loops can be sheer luck; small random events can be magnified to tip one competitor into a winning position. As Uber gets ready to go public, who remembers Sidecar, one of the pioneers in ridesharing, backed by Richard Branson, Google Ventures and others? Like in financial markets, the payoff on attaining the winning position can be disproportionate to its inputs.

More broadly, as technology lowers barriers to entry across a range of pursuits and also lowers friction costs in those pursuits, more players will have the opportunity to compete. As that happens the average level of skill rises, and luck will become the key differentiator. Michael Mauboussin, author of the book The Success Equation, calls this ‘the paradox of skill’. He writes about it in the context of stock market investing, and uses baseball and marathon running to illustrate. I have previously shown how it applies in fantasy football. In all cases competitors are getting better and the range of skill between the top performers is shrinking, leaving more of the outcome to luck. As information gets democratised across more and more domains, it’s likely to happen elsewhere. The poor-quality restaurant that thrived because of its presence in a tourist location is no more thanks to online reviews, but as restaurant quality improves the success of one over another becomes more attributable to luck.

In the past circumstantial luck played a major role in life – where you were born, to whom, what kind of start in life you got. Malcolm Gladwell in his book Outliers examines Bill Gates’ success through this lens, and investors such as Warren Buffett and Howard Marks credit this form of luck for a large part of their success. While circumstantial luck is not going away, increasingly a more integral form of luck will play a part in shaping events. As in financial markets a debate may rage around relative contribution, but wherever it appears, participants would do well to recognise the role of luck. The best advice comes from David Brooks of the New York Times:

“You should regard yourself as the sole author of all your future achievements and as the grateful beneficiary of all your past successes…. As an ambitious executive, it’s important that you believe that you will deserve credit for everything you achieve. As a human being, it’s important for you to know that’s nonsense.”