Stocks & Commodities V. 21:3 (58-63): Applying Expert Systems To Trading by Wolf von Ronik

Stocks & Commodities V. 21:3 (58-63): Applying Expert Systems To Trading by Wolf von Ronik
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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.


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 R1s accompanying branch; if the data in D1 fulfills the criteria of R2, then follow R2s accompanying branch.

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