GARCHselection function

Univariate GARCH selection criterion

This function estimates and evaluates a combination of GARCH models with different distributions and suggests the best GARCH models among all alternatives given some test statistics

GARCHselection(
  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 optimal univariate GARCH model specification

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.

Author(s)

David Gabauer