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Our Stable Dividend Yield Q-Folio Diversified through a unique concentrated approach

Jun 13, 2019

Better Data for Better Investment DecisionsBetter Data for Better Investment Decisions
Better Data for Better Investment DecisionsBetter Data for Better Investment Decisions

 

 

  • Today, we decided to take our AI clustering analysis model and apply it to our Stable Dividend Yield Q-Folio to get a better idea about its diversification
    • Remember, we use a hierarchal risk parity , a form of AI optimization algorithm built around the concept of clustering
  • Immediately, we can see that holdings in the portfolio are not overly concentrated in one cluster
  • It is interesting to that that cluster 6, which represents nearly 40% of the Stable Dividend Yield Q-Folio, is completely independent of the other clusters
  • In comparison to cluster 6, cluster 1 encompasses a large number of the Stable Dividend Yield Q-Folio holdings, albeit almost all are small positions
    • Obviously, this is partially skewed because of the fact that many of the holdings are US community banks
  • The AI Quant takeaway: The AI optimization scheme is creating a diversified portfolio by concentrating into a few small uncorrelated holdings and diversifying risk by introducing several smaller allocations into different industry groups

 

 

We Crunch the Numbers, You Make the Trade.We Crunch the Numbers, You Make the Trade.
We Crunch the Numbers, You Make the Trade.We Crunch the Numbers, You Make the Trade.

 

Stable Dividend Yield Q-Folio AI Clustering Analysis

 

 

dividend yield clustering

 

Global Top Stock IdeasTOP LONG & TOP SHORT STOCK IDEAS FOR GLOBAL MARKETSMONTHLY TOP IDEAS FROM OUR MULTI-FACTOR QUANTITATIVE MODELS
Global Top Stock IdeasTOP LONG & TOP SHORT STOCK IDEAS FOR GLOBAL MARKETSMONTHLY TOP IDEAS FROM OUR MULTI-FACTOR QUANTITATIVE MODELS