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

An analyst applies a clustering algorithm to the return histories of 500 stocks to find groups that behave similarly, without predefining any groups. Which statement about this approach is most accurate?

Clustering stocks without predefined groups is unsupervised learning. The algorithm discovers structure from the return data itself, with no labeled outcomes to train on. Supervised learning and regression both need a target variable, which is absent here.

  1. AIt is unsupervised learning, because the groups are discovered from the data without labeled outcomes.Correct
  2. BIt is supervised learning, because the stocks are sorted into categories after the algorithm runs.
  3. CIt is a regression technique, because it estimates a continuous target from the returns.

Explanation

Clustering finds structure in unlabeled data, so it is unsupervised learning. Producing categories afterward does not make it supervised, since no labeled target guided training. It does not estimate a continuous target, so it is not regression.

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