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Virbickaite, A., Ausín, M.C. and Galeano, P. (2015) A Bayesian Non-Parametric Approach to Asymmetric Dynamic Conditional Correlation Model with Application to Portfolio Selection. Computational Statistics and Data Analysis, 100, 814-829.
https://doi.org/10.1016/j.csda.2014.12.005

has been cited by the following article:

• TITLE: Estimating GARCH Modeling Using Metropolis-Hastings Method in R

  AUTHORS: Min Wang, Yunshun Wu

  KEYWORDS: Student’s t Distribution, Degree of Freedom, GARCH t Model, R, Metropolis-Hastings Method

  JOURNAL NAME: Open Journal of Statistics, Vol.8 No.6, December 20, 2018

  ABSTRACT: This paper mainly talks about a popular approach of volatility of a GARCH-type model in R, while the disturbances are independent and have identical Student-t distribution. It uses the Metropolis-Hastings method to perform the computations and gives the programs in details in R.