在 R 中使用 for 循环拟合 DCC GARCH 模型

Using for-loop for fitted DCC GARCH model in R

我是 R 的新用户。请帮助我!

我有 1114 个观测值和 8 个资产。例如,我已将多元 DCC-GARCH 模型拟合到前 1000 个数据点,我想在 3 个周期后进行 1-ahead 预测,例如

1) Data[1:1000,] In-sample data, forecast for Data[1001,]
2) Data[1:1001,] In-sample data, forecast for Data[1002,]
3) Data[1:1002,] In-sample data, forecast for Data[1003,]

下面是我的可重现代码:-

# load libraries
library(rugarch)
library(rmgarch)
library(FinTS)
library(tseries)
library (fPortfolio)

data(dji30retw)
for (i in 1:3) {
Dat.Initial = dji30retw[, 1:8, drop = FALSE]
Dat <- Dat.Initial[1:(1000+(i-1)), ] 

#Fitting the data
uspec = ugarchspec(mean.model = list(armaOrder = c(0,0)), variance.model = list(garchOrder = c(1,1), model = "sGARCH"), distribution.model = "norm")
spec1 = dccspec(uspec = multispec( replicate(8, uspec)), dccOrder = c(1,1), distribution = "mvnorm")
fit1 <- list()
fit1[[i]] = dccfit(spec1, data = Dat, out.sample = 1, fit.control = list(eval.se=T))

#Out of sample forecasting
dcc.focast <- list()
dcc.focast[[i]]=dccforecast(fit1[[i]], n.ahead = 1, n.roll = 0)
print(dcc.focast[[i]])
}

代码完美运行。我现在可以获得 dcc.focast 值。但为什么会这样,如果我执行

 dcc.focast[[1]]
 NULL

它给了我 "NULL"。它不应该产生与循环中的 "print(dcc.focast[[i]])" 相同的答案吗?

这里的问题,只给我dcc.focast[[3]]。其余为"NULL"。我犯了什么错误?谁能帮忙解释一下?

修改您的代码以在 for 之外定义您的列表。在循环内重新定义列表时,您正在删除以前的计算。

data(dji30retw)
fit1 <- list()
dcc.focast <- list()
for (i in 1:3) {#i=1
  Dat.Initial = dji30retw[, 1:8, drop = FALSE]
  Dat <- Dat.Initial[1:(1000+(i-1)), ] 

  #Fitting the data
  uspec = ugarchspec(mean.model = list(armaOrder = c(0,0)), variance.model = list(garchOrder = c(1,1), model = "sGARCH"), distribution.model = "norm")
  spec1 = dccspec(uspec = multispec( replicate(8, uspec)), dccOrder = c(1,1), distribution = "mvnorm")
  fit1[[i]] = dccfit(spec1, data = Dat, out.sample = 1, fit.control = list(eval.se=T))

  #Out of sample forecasting
  dcc.focast[[i]]=dccforecast(fit1[[i]], n.ahead = 1, n.roll = 0)
  print(dcc.focast[[i]])
}
summary(dcc.focast)
dcc.focast[[1]]

> summary(dcc.focast)
     Length Class       Mode
[1,] 1      DCCforecast S4  
[2,] 1      DCCforecast S4  
[3,] 1      DCCforecast S4  
> dcc.focast[[1]]

*---------------------------------*
*       DCC GARCH Forecast        *
*---------------------------------*

Distribution         :  mvnorm
Model                :  DCC(1,1)
Horizon              :  1
Roll Steps           :  0
-----------------------------------

0-roll forecast: 
, , 1

       [,1]   [,2]   [,3]   [,4]   [,5]   [,6]   [,7]   [,8]
[1,] 1.0000 0.3378 0.3244 0.2383 0.2730 0.5086 0.3470 0.5073
[2,] 0.3378 1.0000 0.3498 0.5423 0.5910 0.3321 0.2802 0.3658
[3,] 0.3244 0.3498 1.0000 0.2372 0.2771 0.3479 0.2433 0.3625
[4,] 0.2383 0.5423 0.2372 1.0000 0.5746 0.2877 0.2303 0.3593
[5,] 0.2730 0.5910 0.2771 0.5746 1.0000 0.3063 0.2169 0.3101
[6,] 0.5086 0.3321 0.3479 0.2877 0.3063 1.0000 0.3637 0.4307
[7,] 0.3470 0.2802 0.2433 0.2303 0.2169 0.3637 1.0000 0.3976
[8,] 0.5073 0.3658 0.3625 0.3593 0.3101 0.4307 0.3976 1.0000