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

Swimming Upstream 
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even after having two dissertations rejected, osborne wasn’t ready 
to give up. He sent “Brownian Motion in the Stock Market” off to Op-
erations Research and set to writing a third dissertation. for this proj-
ect, he returned to a problem he had been working on just before he 
began to think about the stock market. the third idea concerned the 
migratory efficiency of salmon. Salmon spend most of their lives in 
the ocean. But when it comes time to breed, they return to their birth-
places, often up to a thousand miles upstream of the ocean, to spawn 
and die. But after leaving the ocean, they no longer eat. osborne real-
ized that this meant that one could figure out how efficiently a salmon 
can swim by looking at the distances traveled and the fat lost on ar-
rival. the idea was to think of a salmon as a boat that was traveling a 
certain distance without refueling.
When he finished this third dissertation and submitted it, he again 
received a lukewarm reaction. It was not clear that this third disser-
tation was any more “physics” than the second one had been. Ulti-
mately, however, the dissertation was accepted. the university was in 
the process of applying for a large grant in biophysics (the study of the 
physics of biological systems), and the administration wanted to have 
evidence of expertise in that field. And so, in 1959, almost twenty years 
after he had first moved to the nrL and the same year that “Brown-
ian Motion in the Stock Market” appeared in print, osborne finally 
received a doctorate (and a much-deserved promotion at the nrL).
the work on migratory salmon bears a surprising connection to 
osborne’s work on financial markets. His model of how salmon swim 
upriver included analysis at several different time scales. there were 
effects corresponding to how well the salmon were able to swim over 
short distances, which depended on things like the strength of the 
current in the river at a given moment. there were also effects that 
you couldn’t see clearly just by looking at a salmon swimming for a 
few feet or yards but became apparent when you looked at a salmon 
traveling over, say, a thousand miles. the first kind of effect might be 
called “fast” fluctuations in the salmon’s efficiency; the second might 
be called “slow” fluctuations. the trouble was that the data were much 
better on the slow fluctuations. It’s easy to record how many salmon, 

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roughly, have reached a given point at a given time; it is much harder 
to record just how well any given salmon is making headway as a riv-
er’s current changes.
osborne had worked out a theoretical model that tried to explain 
both the slow and fast fluctuations, and to show how they related to 
each other. And he wanted to figure out a way to test the model. Get-
ting better data on individual salmon would have been one way to 
do this — but it would have been difficult, and osborne didn’t have 
any idea where to start. A second possibility was to find another sys-
tem that might show both the fast and slow fluctuations that osborne 
wanted to study, to see if the same model described that system as 
well. this second option seemed much more appealing, but osborne 
needed an appropriate system. When he sat down to figure out how to 
understand the stock quotes in the Wall Street Journal, he soon real-
ized that markets, too, have different scales of fluctuations. Some mar-
ket forces, like the details of how an exchange works or the interac-
tions of traders, can affect how prices change over the course of a day. 
these are like the fast fluctuations that salmon experience from one 
river bend to the next. But there are other forces affecting markets, 
things like business cycles and government interest rates, that become 
apparent only when you step back and look at a longer time period. 
these are slow fluctuations. It turned out the financial world was the 
perfect place to look for data that could be used to test osborne’s ideas 
about how these different kinds of fluctuations affect one another.
the process worked in the other direction, too. After developing 
the migratory salmon model in the context of stock market prices, and 
after tweaking the model to better fit the data he had used to test it, 
he applied it to a problem in physics. osborne proposed a new model 
for deep ocean currents. Specifically, he was able to explain how the 
random motion of water molecules (fast fluctuations in the language 
of the salmon paper) could give rise to variations in apparently sys-
tematic large-scale phenomena, like currents (slow fluctuations). for 
osborne, work in physics and finance were intrinsically linked.
It is tempting to overstate both the reception of osborne’s work and 
his direct influence, because as we shall see, his ideas would ultimately 
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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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