[问答] 程序问题 [推广有奖]

11楼

july0710 发表于 2013-4-6 19:01:49

july0710 发表于 2013-4-6 15:02
garch模型的，用coef的出来的那些

garch的参数

12楼

epoh 发表于 2013-4-6 19:17:00

july0710 发表于 2013-4-6 19:01
garch的参数

data(dji30ret)
spec = gogarchspec(mean.model = list(model = c("constant", "AR", "VAR")[2],
   lag =1), variance.model = list(model = "gjrGARCH", garchOrder = c(1, 1),
   submodel = NULL, variance.targeting = FALSE), distribution.model = c("mvnorm",
   "manig", "magh")[2], ica = c("fastica", "radical")[1])
fit = gogarchfit(spec, data = dji30ret[,1:4, drop = FALSE], out.sample = 0,  gfun = "tanh", rseed = 7)

fit@mfit$ufit@fit
[[1]]

*---------------------------------*
*       GARCH Model Fit       *
*---------------------------------*

Conditional Variance Dynamics
-----------------------------------
GARCH Model    : gjrGARCH(1,1)
Mean Model    : ARFIMA(0,0,0)
Distribution : nig

Optimal Parameters
------------------------------------
      Estimate  Std. Error  t value Pr(>|t|)
omega 0.006230 0.002275 2.7389 0.006165
alpha1  0.053348 0.009749 5.4721 0.000000
beta1 0.952193 0.008148 116.8574 0.000000
gamma1 -0.023126 0.009476  -2.4405 0.014666
skew -0.077369 0.027028  -2.8625 0.004203
shape 2.089454 0.240408 8.6913 0.000000

[[2]]

*---------------------------------*
*       GARCH Model Fit       *
*---------------------------------*

Conditional Variance Dynamics
-----------------------------------
GARCH Model    : gjrGARCH(1,1)
Mean Model    : ARFIMA(0,0,0)
Distribution : nig

Optimal Parameters
------------------------------------
      Estimate  Std. Error  t value Pr(>|t|)
omega 0.003303 0.001172 2.8186 0.004823
alpha1  0.074723 0.011095 6.7350 0.000000
beta1 0.943551 0.008022 117.6137 0.000000
gamma1 -0.039514 0.010135  -3.8989 0.000097
skew -0.101541 0.025540  -3.9757 0.000070
shape 2.083179 0.228506 9.1165 0.000000
...
...