This function calculates the optimal DCC-GARCH specification
DCCGARCHselection( x, distributions = c("norm","snorm","std","sstd","ged","sged"), models = c("sGARCH","eGARCH","gjrGARCH","iGARCH","TGARCH","AVGARCH","NGARCH","NAGARCH","APARCH","ALLGARCH"), prob =0.05, conf.level =0.9, lag =20, ar =0, ma =0)
Arguments
x: zoo data matrix
distributions: Vector of distributions
models: Vector of GARCH models
prob: The quantile (coverage) used for the VaR.
conf.level: Confidence level of VaR test statistics
lag: Lag length of weighted Portmanteau statistics
ar: AR(p)
ma: MA(q)
Returns
Get best DCC-GARCH
References
Ghalanos, A. (2014). rugarch: Univariate GARCH models, R package version 1.3-3.
Antonakakis, N., Chatziantoniou, I., & Gabauer, D. (2021). The impact of Euro through time: Exchange rate dynamics under different regimes. International Journal of Finance & Economics, 26(1), 1375-1408.