Multivariate ARCH Models
Bread Method
Generic Methods for the Copula GARCH model specification
Copula GARCH model specification
Extract Model Coefficients
Fast combination of n elements, taken m at a time
Dynamic Correlation Model Plots
Generic Methods for the DCC GARCH model specification
DCC GARCH model specification
FFT density, distribution and quantile method
Score Method
Estimates a model given a specification.
Expected Shortfall (ES) method for predicted and simulated objects
Extract Model Fitted Values
GOGARCH Model specification
Extract Log-Likelihood
News Impact Surface
Probability Integral Transform (PIT) for weighted FFT densities
News Impact Surface Plot
Model Prediction
Model Estimation Summary Print method
The Robust Accurate, Direct ICA ALgorithm (RADICAL)
Objects exported from other packages
Extract Model Residuals
Model Simulation
Model Estimation Summary
Weighted Moments Aggregation
Cokurtosis Extractor
Convolution
Correlation Extractor
Coskewness Extractor
Covariance Extractor
Model Filtering
tsmarch: Multivariate ARCH Models
Value at Risk (VaR) method for predicted and simulated objects
The Covariance Matrix of the Estimated Parameters
Feasible Multivariate Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models including Dynamic Conditional Correlation (DCC), Copula GARCH and Generalized Orthogonal GARCH with Generalized Hyperbolic distribution. A review of some of these models can be found in Boudt, Galanos, Payseur and Zivot (2019) <doi:10.1016/bs.host.2019.01.001>.
Useful links