Tải dữ liệu
library(readxl)
setwd("d:/DATA2020/Yen_ARIMA")
dulieu <-read_excel("Nhom1.xlsx")
head(dulieu)
## # A tibble: 6 x 6
## MACK DATE SAN PCLOSE RATE PJCLOSE
## <chr> <dttm> <chr> <dbl> <dbl> <dbl>
## 1 BID 2014-01-24 00:00:00 HOSE 18800 0.763 14352
## 2 BID 2014-01-27 00:00:00 HOSE 18400 0.763 14047
## 3 BID 2014-02-06 00:00:00 HOSE 17600 0.763 13436
## 4 BID 2014-02-07 00:00:00 HOSE 16600 0.763 12673
## 5 BID 2014-02-10 00:00:00 HOSE 17000 0.763 12978
## 6 BID 2014-02-11 00:00:00 HOSE 16900 0.763 12902
Lựa chọn p q trong arima
library(forecast)
## Registered S3 method overwritten by 'xts':
## method from
## as.zoo.xts zoo
## Registered S3 method overwritten by 'quantmod':
## method from
## as.zoo.data.frame zoo
## Registered S3 methods overwritten by 'forecast':
## method from
## fitted.fracdiff fracdiff
## residuals.fracdiff fracdiff
kqua=data.frame(Model=0,AIC=0)
n=0
for (i in 0:9){
for (j in 0:9){
n=n+1
temp=Arima(dulieu$PJCLOSE,c(i,1,j),seasonal = c(0,1,0))
kqua[n,]=c(i+j/10,temp$aic)
}
}
plot(kqua[c(1:60),],col=c(1,2,3,4),pch=20)
kqua[which.min(kqua$AIC),]
## Model AIC
## 95 9.4 22871.61
lựa chọn p q trong arch
library(fGarch)
## Warning: package 'fGarch' was built under R version 3.6.3
## Loading required package: timeDate
## Loading required package: timeSeries
## Warning: package 'timeSeries' was built under R version 3.6.3
## Loading required package: fBasics
## Warning: package 'fBasics' was built under R version 3.6.3
Result=data.frame(Model="m",AIC=0)
q=0
for (i in 1:9){
for (j in 1:9){
q=q+1
fit=garchFit(substitute(~garch(p,q),list(p=i,q=j)),data=dulieu$PJCLOSE,trace=F)
Result=rbind(Result,data.frame(Model=paste("m:",i,"-",j),AIC=fit@fit$ics[1]))
}
}
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
## Warning in sqrt(diag(fit$cvar)): NaNs produced
Result=Result[2:nrow(Result),]
plot(Result,col=c(1,2,3,4),pch=20)
Result[which.min(Result$AIC),]
## Model AIC
## AIC m: 1 - 1 19.40903