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How do the Emerging Markets ETFs cluster together? An AI Perspective

Sep 28, 2018

  • We conducted an analysis of how correlations between liquid emerging markets ETFs (listed in the US) cluster using an AI technique called Affinity Propagation  
  • The study, which was conducted on a time series stretching back ONLY to the beginning of CY2018, is USD$-adjusted since all price moves are in USD$ 
  • The core difference between the graph and table below is that the graph visualizes conditional relations between the ETFs while the table measures marginal properties of the different ETFs -- both use the same AI clustering technique
  • If the ETFs cluster together, investors can assume they substitute one for the other to get the same factor exposure --- may offer smart macro traders an awesome opportunity to find some cool macro pair trades 
  • We are shocked to see that Hong Kong iShares (EWH), MSCI China Large-Cap (FXI) and MSCI China iShares DO NOT cluster together more 
  • It isn’t too much of a shock to see the ASEAN iShares clusters together though we don’t how to interpret why the Mexico iShares (EWW), Peru iShares (EPU), Saudi Arabia iShares (TSA) and Turkey iShares (TUR) cluster together...maybe it is because of price sensitivity to commodities?

Visual Representation of How Emerging Markets ETFs Cluster Together

Different Clusters Using 6-Neighbors
Cluster 1 INVESCO China Technology ETF, Chile iShares, Emerging Markets iShares, Indonesia iShares, Poland iShares, Hong Kong iShares, Malaysia iShares, Singapore iShares, Taiwan iShares, South Korea iShares, Brazil iShares, South Africa iShares, China Large-Cap iShares, India iShares, MSCI China iShares, VanEck Russia, Thailand iShares
Cluster 2 Peru iShares
Cluster 3 Mexico iShares
Cluster 4 Saudi Arabia iShares
Cluster 5 Turkey iShares