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other words, we can clearly explain why the past of the dye molecule developed as it did. But the water contains many other water molecules that could have been the ones that interacted with the dye molecule. To predict the dye molecule’s path beforehand would have therefore required us to calculate the paths and mutual interactions of all those potentially important water molecules. That would have involved an almost unimaginable number of mathematical calculations, far greater in scope and difficulty than the list of collisions needed to understand the past. In other words, the movement of the dye molecule was virtually impossible to predict before the fact even though it was relatively easy to understand afterward.

That fundamental asymmetry is why in day-to-day life the past often seems obvious even when we could not have predicted it. It’s why weather forecasters can tell you the reasons why three days ago the cold front moved like this and yesterday the warm front moved like that, causing it to rain on your romantic garden wedding, but the same forecasters are much less successful at knowing how the fronts will behave three days hence and at providing the warning you would have needed to get that big tent ready. Or consider a game of chess. Unlike card games, chess involves no explicit random element. And yet there is uncertainty because neither player knows for sure what his or her opponent will do next. If the players are expert, at most points in the game it may be possible to see a few moves into the future; if you look out any further, the uncertainty will compound, and no one will be able to say with any confidence exactly how the game will turn out. On the other hand, looking back, it is usually easy to say why each player made the moves he or she made. This again is a probabilistic process whose future is difficult to predict but whose past is easy to understand.

The same thing is true of the stock market. Consider, for instance, the performance of mutual funds. As I mentioned in chapter 9, it is common, when choosing a mutual fund, to look at past performance. Indeed, it is easy to find nice, orderly patterns when looking back. Here, for example, is a graph of the performance of 800 mutual fund managers over the five-year period, 1991–1995.

Performance versus ranking of the top mutual funds in the five-year period 1991–1995.

On the vertical axis are plotted the funds’ gains or losses relative to the average fund of the group. In other words, a return of 0 percent means the fund’s performance was average for this five-year period. On the horizontal axis is plotted the managers’ relative rank, from the number-1 performer to the number-800 performer. To look up the performance of, say, the 100th most successful mutual fund manager in the given five-year period, you find the point on the graph corresponding to the spot labeled 100 on the horizontal axis.

Any analyst, no doubt, could give a number of convincing reasons why the top managers represented here succeeded, why the bottom ones failed, and why the curve should take this shape. And whether or not we take the time to follow such analyses in detail, few are the investors who would choose a fund that has performed 10 percent below average in the past five years over a fund that has done 10 percent better than average. It is easy, looking at the past, to construct such nice graphs and neat explanations, but this logical picture of events is just an illusion of hindsight with little relevance for predicting future events. In the graph on chapter 10, for example, I compare how the same funds, still ranked in order of their performance in the initial five-year period, performed in the next five-year period. In other words, I maintain the ranking based on the period 1991–1995, but display the return the funds achieved in 1996–2000. If the past were a good indication of the future, the funds I considered in the period 1991–1995 would have had more or less the same relative performance in 1996–2000. That is, if the winners (at the left of the graph) continued