I need a tip or two.
I am performing OLS with dynamic factors (4x1 factors each representing a PANEL of 24 series, hence 4 time series).
My OLS has autocorrelation in the error so I want to use OLS with ARIMA errors, therefore I model my initial error and the only model that I have found that kills the autocorrelation is ARMA(3,7).
AR(1) does, OK job but I have some significant residuals in lag 4 and few later lags and everything else makes it worse until ARMA(3,7) which make the error 100% white noise (not a single value with significant Q-statistic).
My concern is that ARMA(3,7) model is crazy complex.. what does MA(7) even mean of the OLS error, I have no explanation behind it.
Should I perform a OLS with AR(1) errors even thought it is not perfect (DW statistic is around 2.1) or should I go for OLS with ARMA(3,7) errors which makes the regression perfect?
Any tips? Thanks :)