Financial Econometrics Course: Principal Component Analysis

N.F. Katzke

Principal Component Analysis

Theory on PCA and EFA

In this theory session we discuss dimension reduction techniques.

Using these rotation conventions allow us to get a different view of our data - effectively allowing the modeler to reduce the dimension of input data to that which describes a sufficient amount of the underlying data.

The theory discussed here is introductory and not meant to be exhaustive. Interested readers should delve more into the topic that warranted here.

A detailed practical as well as a bonus application practical accompanies this theory session.

Theory: PCA & EFA (pdf)

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For attribution, please cite this work as

Katzke (2025, Sept. 15). Financial Econometrics Course: Principal Component Analysis. Retrieved from https://www.fmx.nfkatzke.com/posts/2020-08-10-theory3/

BibTeX citation

@misc{katzke2025principal,
  author = {Katzke, N.F.},
  title = {Financial Econometrics Course: Principal Component Analysis},
  url = {https://www.fmx.nfkatzke.com/posts/2020-08-10-theory3/},
  year = {2025}
}