xdcclarge0.1.0 package

Estimating a (c)DCC-GARCH Model in Large Dimensions

cdcc_correlations

This function get the correlation matrix (Rt) of estimated cDCC-GARCH ...

cdcc_estimation

This function estimates the parameters(alpha,beta) and time-varying co...

cdcc_gradient

This functions calculates numerical gradient of log-likelihood of cDCC...

cdcc_loglikelihood

This function calculates log-likelihood of cDCC-GARCH model.

cdcc_optim

This function optimizes log-likelihood of cDCC-GARCH model.

dcc_correlations

This function get the correlation matrix (Rt) of estimated DCC-GARCH m...

dcc_estimation

This function estimates the parameters(alpha,beta) and time-varying co...

dcc_gradient

This functions calculates numerical gradient of log-likelihood of DCC-...

dcc_loglikelihood

This function calculates log-likelihood of DCC-GARCH model.

dcc_optim

This function optimizes log-likelihood of DCC-GARCH model.

xdcclarge

Package

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Functions for Estimating a (c)DCC-GARCH Model in large dimensions based on a publication by Engle et,al (2017) <doi:10.1080/07350015.2017.1345683> and Nakagawa et,al (2018) <doi:10.3390/ijfs6020052>. This estimation method is consist of composite likelihood method by Pakel et al. (2014) <http://paneldataconference2015.ceu.hu/Program/Cavit-Pakel.pdf> and (Non-)linear shrinkage estimation of covariance matrices by Ledoit and Wolf (2004,2015,2016). (<doi:10.1016/S0047-259X(03)00096-4>, <doi:10.1214/12-AOS989>, <doi:10.1016/j.jmva.2015.04.006>).

  • Maintainer: Kei Nakagawa
  • License: GPL (>= 2)
  • Last published: 2018-07-12