Hi all,
I try to simulate an ADF test rolling on a window.
The thing is that it seems I´m doing well...applying to al AR(1) model with
unit root.
I see in some econometrical papers that the t-stat maximum and minimum
should have negative values on the quantiles 0,01 to 0,03
and in my case only the minimum are negative values.
¿It is posible I´m doing wrong calculus on lm?
I m getting mad
Ob <- 100
Re <- 50
H2<-matrix(0,Ob,Re)
for (j in 1:Re){
for (i in 2:Ob){
H2[i, j] <-1+ 1*H2[i-1, j]+rnorm(1)
}
}
H3<-matrix(0,Ob,Re)
for (i in 2:Ob){
for (j in 1:Re){
H3[i,j]<-H2[i,j]-H2[i-1,j]
}}
a3<-H3[2:nrow(H3),1:ncol(H3)]
a2<-H2[1:(nrow(H2)-1),1:ncol(H2)]
write.csv(a3,"a3.csv")
write.csv(a2,"a2.csv")
a3<-read.csv("a3.csv")
a2<-read.csv("a2.csv")
delta<-round(Ob*(1/3))
fg<-matrix(0,nrow(H3)-delta+1,Re)
for (j in 1:Re){
for (i in delta:nrow(H3) ){
z2<-(i-delta+1)
z3<-i
fg[i-delta+1,j]<-coef(summary(lm(a3[z2:z3,j+1]~(1+a2[z2:z3,j+1]) )
))[2,"t value"]
print(j)
}
}
MaxrollingT<-apply(fg, 1, max)
MinrollingT<-apply(fg, 1, min)
Diffrolling<-MaxrollingT-MinrollingT
Meanrolling<-apply(fg, 1, mean)
write.csv(MaxrollingT, file = "MaxrollingT.csv")
write.csv(MinrollingT, file = "MinrollingT.csv")
write.csv(Diffrolling, file = "DiffrollingT.csv")
write.csv(Meanrolling, file = "Meanrolling.csv")
print(c(quantile(MaxrollingT,0.01),quantile(MinrollingT,0.01)))
print(c(quantile(MaxrollingT,0.015),quantile(MinrollingT,0.015)))
print(c(quantile(MaxrollingT,0.02),quantile(MinrollingT,0.02)))
print(c(quantile(MaxrollingT,0.025),quantile(MinrollingT,0.025)))
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Can anyone help me to see why maximum t-stat quantile has no Negative
values?
¿It is posible lm estimation is not fine?
---------- Forwarded message ----------
From: Jose Narillos de Santos <narillosdesantos@gmail.com>
Date: 2013/9/8
Subject: ADF test
To: r-help <r-help@r-project.org>
Hi all,
I try to simulate an ADF test rolling on a window.
The thing is that it seems I´m doing well...applying to al AR(1) model with
unit root.
I see in some econometrical papers that the t-stat maximum and minimum
should have negative values on the quantiles 0,01 to 0,03
and in my case only the minimum are negative values.
¿It is posible I´m doing wrong calculus on lm?
I m getting mad
Ob <- 100
Re <- 50
H2<-matrix(0,Ob,Re)
for (j in 1:Re){
for (i in 2:Ob){
H2[i, j] <-1+ 1*H2[i-1, j]+rnorm(1)
}
}
H3<-matrix(0,Ob,Re)
for (i in 2:Ob){
for (j in 1:Re){
H3[i,j]<-H2[i,j]-H2[i-1,j]
}}
a3<-H3[2:nrow(H3),1:ncol(H3)]
a2<-H2[1:(nrow(H2)-1),1:ncol(H2)]
write.csv(a3,"a3.csv")
write.csv(a2,"a2.csv")
a3<-read.csv("a3.csv")
a2<-read.csv("a2.csv")
delta<-round(Ob*(1/3))
fg<-matrix(0,nrow(H3)-delta+1,Re)
for (j in 1:Re){
for (i in delta:nrow(H3) ){
z2<-(i-delta+1)
z3<-i
fg[i-delta+1,j]<-coef(summary(lm(a3[z2:z3,j+1]~(1+a2[z2:z3,j+1]) )
))[2,"t value"]
print(j)
}
}
MaxrollingT<-apply(fg, 1, max)
MinrollingT<-apply(fg, 1, min)
Diffrolling<-MaxrollingT-MinrollingT
Meanrolling<-apply(fg, 1, mean)
write.csv(MaxrollingT, file = "MaxrollingT.csv")
write.csv(MinrollingT, file = "MinrollingT.csv")
write.csv(Diffrolling, file = "DiffrollingT.csv")
write.csv(Meanrolling, file = "Meanrolling.csv")
print(c(quantile(MaxrollingT,0.01),quantile(MinrollingT,0.01)))
print(c(quantile(MaxrollingT,0.015),quantile(MinrollingT,0.015)))
print(c(quantile(MaxrollingT,0.02),quantile(MinrollingT,0.02)))
print(c(quantile(MaxrollingT,0.025),quantile(MinrollingT,0.025)))
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