ABSTRACT
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 and a model-based simple rule is constructed with 96.6% of correct classifications. 10 new markets are allocated to one of the previously defined groups: Developed, Emerging, or Frontier, with only one misclassification. The quantitative approach was able to anticipate classification reviews.
Disclosure statement
No potential conflict of interest was reported by the authors.