Wishart process

A Wishart process is a mathematical model used to describe how certain matrices, especially covariance matrices, change over time in a stochastic (random) way. It extends the Wishart distribution, which is a way to represent the variability of matrices derived from multivariate data. This process ensures the matrices remain positive semi-definite, a necessary property for covariance matrices. Wishart processes are useful in finance, economics, and physics to model evolving uncertainties in multivariate systems, capturing both deterministic trends and random fluctuations in the relationships between multiple variables.