PCA is a very useful tool in lots of places. But be warned that when you use it on stocks, you'll find correlations, make your investment, then discover that during a financial crisis all sorts of things that were not previously correlated, now are. Thus your analysis falls apart at exactly the moment you would least want it to do so.
Incidentally if you take answers to a wide variety of questions that are meant to test intelligence, how the component of your score on the first component on a PCA analysis should be fairly well correlated with IQ or your SAT score. The second component should be reasonably well correlated to the difference between your math and verbal scores on the SAT. And people have much less variability on the third component than on the first two.
In financial practice, asset-level PCA isn't as common, especially in systems where covariance estimation is fraught with misspecification errors. Instead, individual securities first condensed to factors (e.g., for equity some examples are book/price, momentum, large vs. small cap, etc.).
Incidentally if you take answers to a wide variety of questions that are meant to test intelligence, how the component of your score on the first component on a PCA analysis should be fairly well correlated with IQ or your SAT score. The second component should be reasonably well correlated to the difference between your math and verbal scores on the SAT. And people have much less variability on the third component than on the first two.