I have a dataset for the daily USD/DKK exchange rate for the past 10 years. my training set consists of the first 9 years and my test set consists of the last year. I am trying to choose between the following to two ARIMA models. 1. arima (1,0,1)
# Arima (1,0,1) n <- 2332 # length(train_ts) m <- 259 # AVG numbers of observations a year y <- ts(rnorm(n) + (1:n)%%100/30, f=m) fit3 <- auto.arima(y, seasonal=FALSE, xreg=fourier(y, K=4)) fit3 fit4 <- Arima(train_ts, order= c(1,0,1), xreg = fourier(y, K=4)) autoplot(forecast(fit4, h=2*m, xreg=fourier(y, K=4, h=2*m))) + autolayer(test_ts, series= "Test data")
- arima model (2, 1, 3)
arima_fit <- Arima(train_ts, order = c(2, 1, 3), include.constant = FALSE) arima_fit
My thought is to go with the first model, becuase the AIC is simulair, but the MASE is much lower, but I dont know if I am wrong.
Can anybody help me decide which model to go with, and tell me if I should only look at AIC and BIC when comparing ARIMA models?