Using Neural Networks to Discover Patterns in International Equity Markets: A Case Study

Abstract

The use of neural networks represents a new approach to how this type of problem can be investigated. The economics and finance literature is full of studies that require the researcher to prespecify the exact nature of the relationship and select specific variables to test. In this study, we use a multistage approach that requires no prespecification of the model and allows us to look for associations and relationships that may not have been considered. Previous studies have been limited by the nature of statistical tools, which require the researcher to determine the variables, time frame, and markets to test. An intelligent guess may lead to the desired outcome, but neural networks are used to produce a more thorough analysis of the data, thus improving the researcher’s ability to uncover unanticipated relationships and associations.