CDAR Co-Director Bob Anderson presented: “PCA with Model Misspecification”
The theoretical justifications for Principal Component Analysis (PCA) typically assume that the data is IID over the estimation window. In practice, this assumption is routinely violated in financial data. We examine the extent to which PCA-like procedures can be justified in the presence of two specific kinds of misspecification present in financial data: time-varying volatility, and the presence of regimes in factor loadings. Joint work with Stephen W. Bianchi (Berkeley).