Applying Expert Systems To Trading by Wolf von Ronik
Artificial intelligence was introduced 50-odd years ago to
model the way humans learn and extrapolate from the
knowledge they glean. How can the theory of expert systems,
one of the two current thoughts of artificial intelligence, be
applied to trading?
In a broad sense, artificial intelligence (AI) is an
attempt to model human learning and decisionmaking.
In recent years AI techniques have
been applied to a diverse number of activities,
including trading. A number of trading software
packages that traders can purchase today
are based upon AI techniques.
Since its introduction in the 1950s, artificial intelligence
has split into two camps — expert systems and neural
networks. Although these two terms are often used interchangeably,
they are distinct in their approach to modeling
human decision-making processes and, therefore, in their
applicability to trading.
WHAT ARE EXPERT SYSTEMS?
In its simplest form, an expert system is essentially a collection
of data and accompanying if-then rules configured into
the familiar decision tree (Figure 1). The decision tree begins
with a node containing a data statement, labeled D1. The
information in D1 is subjected to a pair of rules, denoted R1
and R2, in the following manner:
If the data in D1 fulfills the criteria of rule R1, then follow R1’s
accompanying branch; if the data in D1 fulfills the criteria of R2,
then follow R2’s accompanying branch.