如何在GARCH模型中使用ARIMA [英] How to use ARIMA in GARCH model

问题描述

我有财务数据，我的目标是能够进行预测.我运行了一个arima模型，发现最合适的是arima(1,1,1)w/漂移.我想在数据集上使用GARCH，因为由于波动性，它是更好的模型，当我对残差求平方时，确实具有拱效应.但是我知道GARCH接受2参数Arima，但我不确定它如何从我现在拥有的3参数Arima中转换.

I have financial data and my goal is to be able to forecast. I ran an arima model and found that the best fit was arima(1,1,1) w/ drift. I want to use GARCH on the data set because it is the better model to use due to volatility and when I squared my residuals it did have the arch effect. But I know that GARCH takes in a 2 parameter arima and I am not sure how that translates from the 3 parameter arima I currently have.

library(dplyr)
library(tidyr)
library(lubridate)
library(ggplot2)
library(TSA)
library(forecast)
spnew<-read.csv(file="~/Desktop/SPNEW.csv", header=T, 
sep=",",check.names=FALSE)
sfts1=ts(sp$`Adj Close`, 
freq=260,start=decimal_date(ymd("2009-01-02")))
arsf1=auto.arima(sfts1, trace=T)

我有要为GARCH运行的代码，但不确定为Arima部分输入什么.

I have the code to run for GARCH but am not sure what to input for the arima portion.

model1 <-  ugarchspec(variance.model = list(model="sGARCH",         
                                                 garchOrder=c(_,_)), 
                           mean.model = list(armaOrder=c(_,_)), 
                           distribution.model = "norm")        
mod2 <- ugarchfit(spec=model1, 
                          data=sfts1)

我将需要输入的内容留空.一旦知道如何放入Arima，我将按照garch顺序进行操作.如果知道更好的GARCH模型代码编写方法，请告诉我.

I left blanks for what I would need to input. I will play with the garch order once I know how to put in arima. If a better way to code the GARCH model is known please let me know.

推荐答案

下面，我将称为2参数arima的模型称为ARMA.
rugarch :: ugarchspec()可以将ARMA(p，q)或ARFIMA(p，d，q)模型视为 mean.model .
(注意:当d为整数时，ARFIMA(p，d，q)等同于ARIMA(p，d，q))

Below, I refer to the model that you call 2 parameter arima as ARMA.
rugarch::ugarchspec() can treat ARMA(p, q) or ARFIMA(p, d, q) model as mean.model.
(NOTE: when d is integer, ARFIMA(p, d, q) is equivalent to ARIMA(p, d, q))

这是我的例子；

p <- 1
q <- 1
# d <- 1    # if you want to fix d

model1 <-  ugarchspec(variance.model = list(model="sGARCH",         
                                            garchOrder=c(_, _)), 
                      mean.model = list(armaOrder=c(p, q),
                                        arfima = T),    # using arfima model
                      # fixed.pars=list(arfima = d),    # If you want to fix d
                      distribution.model = "norm"))

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