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CFA Level I · CFA Level I Exam · Introduction to Financial Data Science

A portfolio manager wants an algorithm to group 500 stocks into clusters with similar return behavior, without providing any predefined categories. Which approach is most appropriate?

Unsupervised learning using clustering is most appropriate. The manager has no predefined categories or target variable and wants the algorithm to discover natural groupings of stocks with similar return behavior. Classification and penalized regression are supervised methods that require labeled outcomes to train on.

  1. AUnsupervised learning using clusteringCorrect
  2. BSupervised learning using classification
  3. CSupervised learning using penalized regression

Explanation

With no predefined labels and a goal of discovering structure in the data, clustering under unsupervised learning is appropriate. Classification and penalized regression both need a labeled target variable.

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