Hierarchical cluster analysis (HCA) [31] was then used to group traders into clusters according to their level of similarity in the factors created by the FAMD. The Manhattan distance was used to assess the level of dissimilarity between 2 traders. The algorithm was agglomerative, and the Ward's criteria for linkage was adopted. Finally, a consolidation using the k-means algorithm was performed. FAMD and HCA were implemented in R 2.12.0 [32] , using the package FactoMineR 1.15 [33] .