EbEEMGARCH: Homepage of the documentation

In TaoussD/EbEEMGARCH: Estimating MGARCH(1,1) model equation by equation

Description

This package provides several tools to sample or estimate MGARCH(1,1) models equation by equation

Note

Functions available in the package

• GarchCCC.sim Simulation of a MGARCH(1,1) CCC-diagonal or semi-diagonal

• estimCCC.EbEE Estimation of a MGARCH(1,1) CCC-diagonal or semi-diagonal equation by equation

• MSD.CCC.EbEE Compute mean and standard deviation of the estimator for CCC models

• GarchDCC.sim Simulation of a Aielli or Engle MGARCH(1,1) DCC semi-diagonal

• estimDCC.EbEE Estimation of a Aielli or Engle MGARCH(1,1) DCC semi-diagonal equation by equation

• MSD.DCC.EbEE Compute mean and standard deviation of the estimator for DCC models

• residuals_DCC Compute residuals for DCC models

• VaR.Spherical Compute CVaR of a portfolio where yields follow a MGARCH(1,1) DCC model, for a spherical distribution of the residuals

• VaR.FHS Compute CVaR of a portfolio where yields follow a MGARCH(1,1) DCC model using FHS method

• Sqrt Square root of a symetric semi-definite positive matrix

• InvSqrt Inverse of a square root of a symetric semi-definite positive matrix

• vech0 vech0 operator

• inv.vech0 Inverse of vech0 operator

Author(s)

D. Taouss & C. Francq

References

C. Francq & J.M. Zakoian, Estimating multivariate GARCH and Stochastic Correlation models equation by equation
C. Francq & J.M. Zakoian, Joint inference on market and estimation risks in dynamic portfolios

Publications available at http://perso.univ-lille3.fr/~cfrancq/

See Also

Source of the package available at https://github.com/TaoussD/EbEEMGARCH

TaoussD/EbEEMGARCH documentation built on May 9, 2019, 4:18 p.m.