Determinants of stock market classifications

Abstract

In this paper we use discriminant analysis to describe and predict market classifications. Potential discriminators are derived from relevant characteristics of market indices, in particular from the returns’ volatility. Using a training data set, an initial screening on the predictors is carried out by the Kruskal-Wallis test and a model based simple rule is constructed. The statistical significance of research results is confirmed by the high ratio of correct classifications (96.6%) along with formal statistical tests. Using a validation data set this rule is applied to allocate markets to one of the previously defined groups: Developed, Emerging, or Frontier. The easy to implement quantitative approach for classifying markets was able to anticipate market reclassifications, and erroneous classifications were found to be exactly those markets reclassified in the following classification review.