Praise for Trading from Your Gut

part of market participants, and trade against that reaction or antic-
ipate an overreaction or underreaction based on previous market
behavior. You can make money from both overreactions and under-
reactions, either by predicting them or by reacting to them. Predict-
ing market prices themselves is very hard. Predicting human
reaction to market prices is somewhat easier. But easiest of all is
detecting what has already happened and reacting to that existing
market condition.
If the market overreacts, you can make money by anticipating a
return to “correct” price levels. If the market underreacts, you can
also make money by anticipating a return to “correct” price levels.
In each of these respective scenarios, the meaning of “correct” is
different. In the case of an underreaction of a price toward the
upside, the “correct” price level is above the market price, so you
can profit by buying at the market price and anticipating an eventual
return to the “correct” price. In the case of an overreaction of a
price toward the upside, the “correct” price level is below the mar-
ket price, so you can profit by selling at the market price and antici-
pating an eventual return to the “correct” price.
102
T
RADING FROM
Y
OUR
G
UT
From the Library of Daniel Johnson

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ptg
Markets as Emergent Systems
For example, the market reactions for most stocks are aggrega-
tions of the behavior of thousands of individual traders and
investors. The aggregation of these behaviors often exhibits a
repeatable consistency that is not readily apparent if one examines
the behavior of the individuals independently. This emergence of
more complex behavior out of the behavior of interacting individu-
als is found in nature and has been studied as a phenomenon known
as emergent systems.
Two common examples of a behavior stemming from an emer-
gent system are schooling in fish and flocking in birds. In both of
these examples, large groups of individuals coordinate their move-
ments with the group so that an entire school of fish or flock of birds
appears to be guided by a common thought. Scientists who study
emergent systems have used simple computer algorithms to model
similar behaviors, showing that simple rules among individuals often
suffice to specify seemingly complex behavior at the group level.
In simulations, a group of fish that simply point themselves in
the direction that is the average of the fish nearest to them will very
closely mimic the behavior of a large school of fish. By orienting
themselves parallel to the average direction that their closest peers
point to, fish can school. This is a classic example of emergent