Iterated and exponentially weighted moving principal component analysis

The principal component analysis (PCA) is a staple statistical and unsupervised machine learning technique in finance. application of PCA financial setting associated with several difficulties, such as numerical instability nonstationarity. We attempt to resolve them by proposing two new variants PCA: an iterated (IPCA) exponentially weighted moving (EWMPCA). Both rely on the Ogita-Aishima iteration crucial step.