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我正在尝试预测 Copula Garch 模型。我曾尝试将 dccforecast 函数与 cGARCHfit 一起使用，但结果表明没有适用于类 cGARCHfit 对象的“dccforecast”方法是错误的。那么实际上我们如何预测 dcc copula garch 模型呢？

我有以下可重现的代码。

library(zoo)
library(rugarch)
library(rmgarch)
data("EuStockMarkets")
EuStockLevel <- as.zoo(EuStockMarkets)[,c("DAX","CAC","FTSE")]
EuStockRet <- diff(log(EuStockLevel))

# DCC timecopula MVN

  uspec = ugarchspec(mean.model = list(armaOrder = c(0,0)), variance.model = list(garchOrder = c(1,1), model = "sGARCH", variance.targeting=FALSE), distribution.model = "norm")
  spec1 = cgarchspec(uspec = multispec( replicate(3, uspec) ), asymmetric = TRUE,  distribution.model = list(copula = "mvnorm", method = "Kendall", time.varying = TRUE, transformation = "parametric"))
  fit1 = cgarchfit(spec1, data = EuStockRet, cluster = NULL, solver.control=list(trace=1))
  print(fit1)  

 > fit.copula = cgarchfit(spec1, data = EuStockRet, out.sample = 120, solver = "solnp", solver.control =list(),fit.control = list(eval.se = TRUE, stationarity = TRUE, scale = FALSE),cluster = NULL, fit =NULL, VAR.fit = NULL)
 > dcc.copula.focast=dccforecast(fit.copula, n.ahead = 1, n.roll = 0) 
   Error in UseMethod("dccforecast") : no applicable method for 'dccforecast' applied to an object of class "c('cGARCHfit', 'mGARCHfit', 'GARCHfit', 'rGARCH')"

感谢您的友好帮助。

谢谢

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1 回答 1

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DCC 预测仅适用于 dccfits。您可以尝试使用函数 cGARCHsim 或放弃 Kendall 方法并进行 dccfit。虽然如果您想预测未来更长的时期，使用 cGARCHsim 进行预测可能会很痛苦。

看：

??cGARCHsim

细节

由于没有明确的预测例程，用户应该使用这种方法 >通过模拟 1-ahead 逐步建立 n-ahead 预测， >获取收益、sigma、Rho 等的均值并将它们提供给下一轮 >模拟作为起始值。'rmgarch.tests' 文件夹包含说明这一点的特定示例。

于 2016-01-22T11:21:33.117 回答