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Does it even makes sense to run PCA on the change percentage of a stock. To me it would be make more sense to use it with physical properties of the under lying
by samfisher83 8y ago
Does it even makes sense to run PCA on the change percentage of a stock. To me it would be make more sense to use it with physical properties of the under lying the company. PCA helps you reduce dimensions of a higher order dimension to lower dimension so you can group stocks together. I am a little confused by what the author is trying to do.
- wjn0 8y agoSure it does. Author could've been clearer about the goals, though. Say that rather than pre-selecting 50 stocks, we ran the analysis on the whole market - then each component intuitively corresponds to some segment of the market. For example, some component might correspond to agro companies whose prices fluctuate with the weather. Another component might correspond to NFLX and other companies who rely on AWS, which fluctuate together based on cloud storage price changes. This kind of interpretation kind of falls out of the math (the eigendecomposition/SVD/covariance matrix interpretation of PCA in particular).
- kgwgk 8y agoIt does make sense and it's a pretty standard thing. See for example: https://thequantmba.wordpress.com/2017/01/24/principal-component-analysis-of-equity-returns-in-python/ https://thequantmba.wordpress.com/2017/01/24/principal-compo... or https://www.coursera.org/lecture/fundamentals-machine-learning-in-finance/pca-for-stock-returns-part-1-pv25P https://www.coursera.org/lecture/fundamentals-machine-learni...