I have been asked to build an ARMA model for some oil WTI spot prices.
I have manipulate the data to make it stationary (taking log-returns), and stationarity has been confirmed by the Augmented Dickey Fuller test and all the other stationarity tests available in EViews. However, when I plot out the correlogram to decide about the order of my ARMA, it appears to be almost flat (both the acf and the pacf) and the Q-stat suggest to reject the null of no-autocorrelation for all the lags beyond the first one. All the correlation coefficients appear to be insignificant, using the confidence interval 1.96 + - 1/T^1/2 .
My intuition is that the ARMA model is not a good guess for this kind of data, but I’m struggling to find a scientific justification to my results.
I have thought that the reason for the non-decaying acf and pacf is that the data might be still highly persistent, or that it might have to do with the fact that the manipulated dta doesn't have a unit root but still hasn't got constant variance, but I still struggle to back up my thoughts with solid theory.
Can anybody help me?
Thank you!
I have manipulate the data to make it stationary (taking log-returns), and stationarity has been confirmed by the Augmented Dickey Fuller test and all the other stationarity tests available in EViews. However, when I plot out the correlogram to decide about the order of my ARMA, it appears to be almost flat (both the acf and the pacf) and the Q-stat suggest to reject the null of no-autocorrelation for all the lags beyond the first one. All the correlation coefficients appear to be insignificant, using the confidence interval 1.96 + - 1/T^1/2 .
My intuition is that the ARMA model is not a good guess for this kind of data, but I’m struggling to find a scientific justification to my results.
I have thought that the reason for the non-decaying acf and pacf is that the data might be still highly persistent, or that it might have to do with the fact that the manipulated dta doesn't have a unit root but still hasn't got constant variance, but I still struggle to back up my thoughts with solid theory.
Can anybody help me?
Thank you!