Resolved: ARMA model
Hi!
I had an error in the 3 lecture of ARMA in time-series. When I fit the model it says:'The computed initial AR coefficients are not stationary You should induce stationarity, choose a different model order, or you can pass your own start_params'.
I guess it's not something about the code or the data
model_returns_arma_33=ARMA(train.returns[1:],order=(3,3))
results_returns_arma_33=model_returns_arma_33.fit()
I also did adfuller test, which has shown very low p-value.
sts.adfuller(train.returns[1:])
(-17.03445719098116, 8.28053702031718e-30, 17, 5002, {'1%': -3.431658008603046, '5%': -2.862117998412982, '10%': -2.567077669247375}, 16035.926219345134)
1 answers ( 0 marked as helpful)
Hi Max,
Thanks for reaching out!
When this occurs, you need to specify the number of starting AR parameters you're giving the model before fitting. Usually, 1 more than the number of lags you're using is sufficient, but you might need to add more depending on the data.
Hence, just add start_ar_lags = 4 to the fit function, like so:
results_returns_arma_33=model_returns_arma_33.fit(start_ar_lags = 4)Hope this helps! Best, 365 Vik
Submit an answer
