The principal components are the eigenvectors of the covariance matrix, and the eigenvalues are the variance explained.
Interpretation in rates markets is the textbook example: the first three components of a yield curve correspond closely to level, slope and curvature, and together explain the great majority of variation.
The caveats. Components are statistical constructs, not economic factors, and beyond the first few they are often noise. PCA is also scale-dependent, so standardise first unless the units are already comparable.