- CFA Exams
- CFA Level I Exam
- Topic 1. Quantitative Methods
- Learning Module 6. Machine Learning
- Subject 4. Unsupervised Machine Learning Algorithms
CFA Practice Question
You are given 500 stocks and try to group them for portfolio diversification purpoases. Each company has multiple features, such as financial ratios, industry features, market shares, R&D expenditures, etc. Which model/algorithm would be the most appropriate one to use?
A. K-Nearest Neighbor
B. K-means clustering
C. Hierarchical clustering
Explanation: K-means can be used to derive different clusters of stocks.
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