Factor models is a class of statistical and econometric frameworks used to explain the covariance structure among a set of observed variables by postulating their linear dependence on a smaller number of unobserved common factors and variable-specific idiosyncratic shocks. This methodology investigates the underlying latent dimensions or drivers influencing observed phenomena, offering dimensionality reduction and insights into systematic risk or common variation, and is significant for applications in data analysis, forecasting, and understanding complex systems across diverse disciplines.