Dynamic Risk Factor Model for Correlation Matrices:
From Random Matrix Theory to Econometrics

Modelling the dynamics of correlations of a large market has been a very challenging problem in finance. This is due to the enormous noise of individual assets and the dimensionality of the system. With the help of limit theorems in Random Matrix Theory (RMT), the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model, and Principal Component Analysis (PCA), the Dynamic Risk Factor (DRF) model for the dynamics of the cross correlation of a large system is proposed.