Had it been a best-of-three set match, Stepanek would have won, having claimed the first two sets. Over the longer format, however, Murray's superiority came through: he is ranked number two in the world against Stepanek's 148th place.
Quality is more likely to be evident in the longer-run than in the shorter. The outsider might pull off an upset in a best-of three match, but he's less likely to do so in the longer format. The same is true in other sports. In cricket, the better team is more likely to win a two-innings match than a Twenty20 game, and in football the league, played over 38 games, is a better measure of teams' true ability than the FA Cup.
The same, of course, applies to investing. Over shortish periods, bad stocks or bad fund managers can beat the market. It is only in the long-run that we can judge true quality. In fact, this is even more true in investing than sport. Because shares are more volatile than top players' performances, the ratio of noise to signal is greater in investing, and so we need longer runs of data to distinguish between luck and true quality.
You might think all this obvious. So here's the surprise. Bookies don't appreciate this. Constantinos Antoniou at Warwick Business School and Christos Mavis at Surrey Business School studied Grand Slam tennis matches and found that the higher-ranked player won 77.7 per cent of them. But bookies' odds averaged a probability of just 73.9 per cent. Bookies therefore offer excessively generous odds on the better player - something they don't do in best-of-three matches.
This isn't because bookies try to drum up business in higher-profile Grand Slam matches: in women's matches, all of which are best of three, there is no disparity of odds between Grand Slam and other tournaments. Nor is the quirk confined to bookies; the same thing is true on betting exchanges.
What's going on here is what Messrs Antoniou and Mavis call process variance neglect. People fail to appreciate sufficiently that whilst random events can distort short runs of data, longer runs of data are less prone to surprises.
Investors are also guilty of this bias. Economists at Ohio State University have found that foreign exchange day traders make bigger trades after only a single week of profits - the sort of gains that can easily be due to dumb luck. This is because they mistake luck for skill, and so take on undue risk. Men are more prone to this than women.
Also, economists at Cass Business School have found a strong correlation between unit trusts' performance over the previous six months and retail investors' buying. Sadly, however, the correlation between that six-month performance and returns in the following six months is slightly negative. This means that investors who chase short-run returns end up losing money. This too is evidence that investors are prone to process variance neglect: they fail to appreciate that over periods as short as six months, good returns might be due to luck rather than skill.
The message here is simple. We should ask of anything, and especially our own success: how likely is this to be due to luck rather than skill? For shorter-term returns - by which I mean many months - the answer is often: luck.
