Discretize VAR(1) of arbitrary size, with arbitrary covariance matrix for innovations, and optional stochastic volatility.
Discretize VAR(1) of arbitrary size, with arbitrary covariance matrix for innovations. Support for VAR(1) with covariance matrix perturbed by common AR(1) volatility shock,
e.g. “volatility regime,” like baseline Bansal-Yaron process. Allows the elimination of support points with low probability in the ergodic distribution (non-tensor grid).
Uses the Armadillo library for C++, with HDF5 support for I-O.
Looking instead for a MATLAB library? Consider the code repository for “Discretizing Nonlinear, Non-Gaussian Markov
Processes with Exact Conditional Moments” by Leland E. Farmer & Alexis Akira Toda, in QE, or the refinement
of Grey Gordon’s “Efficient VAR Discretization” in EL.
