The Physics of Wall Street: a brief History of Predicting the Unpredictable

From Coastlines to Cotton Prices 
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ary school in 1942, he found himself unable to proceed to a grande 
école because his movements were so constrained. (Here his education 
is reminiscent of Bachelier’s, who was also unable to attend a grande 
école.) But Mandelbrot never went into detail about his experiences 
during this period, except to say that the year and a half after finishing 
school was “very, very rough” and he had “several very close calls with 
disaster.”
Since further schooling was out of the question, and because he 
needed to maintain a low profile, he avoided cities and moved often. He 
lived with members of the resistance, who took him in and attempted 
to hide him. He worked a series of odd jobs, attempting to disguise 
himself as a provincial frenchman. for some months he worked as 
a horse groom, and then as an apprentice toolmaker for the french 
railroad. But he was never a very convincing tradesman. Missing the 
scholarly life, Mandelbrot clung to the few books he managed to find 
during this period, carrying them with him and reading whenever he 
had an opportunity — not the smartest move for someone trying to 
pass as a horse groom.
At one point, at least, Mandelbrot very narrowly escaped deporta-
tion — and likely execution. But mostly he managed to keep clear of 
German forces. His father had a closer call. As Mandelbrot would later 
tell it, his father was arrested during this period and sent to a nearby 
prison camp. not long after, the prison was attacked by members of 
the resistance. the guards were neutralized and the prisoners were set 
free. But the resistance fighters were ill prepared to defend the camp, 
so they urged the prisoners to flee quickly to escape capture by Ger-
man reinforcements.
Lacking a plan or a clear route to safety, the prisoners set out in a 
group on the road to Limoges, the nearest major town. Shortly after 
leaving the camp, however, the elder Mandelbrot realized that this 
was a disastrous idea: they were traveling in a large pack, moving in 
the open on a major road. tracking them would be easy. the others 
couldn’t be persuaded, so Mandelbrot’s father left the group and struck 
out on his own. He headed toward a nearby forest, planning to slowly 
make his way back to where his family had been hiding before his ar-
rest. As he moved through the wilderness, he heard a gut-wrenching 

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noise: behind him, back at the main road, a German dive bomber had 
found the other prisoners.
Life during wartime is an unpredictable thing. In thomas Pynchon’s 
novel Gravity’s Rainbow, one of the characters, roger Mexico, is a stat-
istician charged with keeping track of where the v-2 rockets land in 
London during the final days of the third reich. He finds that the 
rockets are falling according to a particular statistical distribution —
the one you would expect if they were equally likely to fall anywhere 
in the city. Mexico is surrounded by people desperate to control their 
lives, to save themselves from the rockets’ whimsical paths. to these 
onlookers, Mexico’s charts and graphs hint at some underlying pat-
tern, something they might use to predict where the next rocket will 
fall.
Some areas of the city seem to be hit quite often. others, rarely. But 
to assume that these patterns say anything about where the next rocket 
will fall is to commit the same fallacy as the roulette player who is con-
vinced that a particular number is “due.” Mexico knows this. And yet 
he, too, finds the data seductive, as though the very randomness of the 
pattern holds the key to its power. And it does, at least if you happen 
to be standing on the street where the next rocket falls.
Yet mathematically, this sort of randomness is mild. the v-2 rock-
ets were fired systematically, several a day, aimed roughly at London. 
Working out the odds of how many rockets would land on St. Paul’s 
cathedral or in Hammersmith was a lot like working out how many 
times a roulette ball would fall into red 25. Indeed, many of the situa-
tions we think of as random are like this. So many, in fact, that it’s easy 
to fall prey to the idea that all random events are like coin tosses or 
simple casino games.
this assumption underlies much of modern financial theory. think 
back to when Bachelier was imagining how stock prices would change 
over time if they underwent a random walk. every few moments, the 
price would tick up or down by some small amount as though God 
were flipping a coin. Bachelier discovered that if this was a good ap-
proximation of what was happening, the distribution of prices would 
look like a bell curve, a normal distribution. osborne of course 
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t h e p h y s i c s o f wa l l s t r e e t

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