PACF and ACF plot does not show any significance

This is my very first time building time series forecasting and i'm currently trying ARMA in python. I'm stuck in building my ARMA (ARIMA(p,0,q) model because of there's no significance at all in my ACF and PACF plot. I have read several articles about ARIMA but all of them at least shows significant correlation in their ACF and PACF plot. So for my case, i don't know what to do since this is my first time building times series forecasting model. My data is very stationary so i thought i could go on to plot the ACF and PACF and to build the model. But now i start to doubt if ARMA suits my problem.

1. What should i do if i could still go on building the ARMA model?
2. If ARMA is not for my data, what other algorithm should i use?
ADF Statistic: -7.654896
p-value: 0.000000
Critical Values:
1%: -3.508
5%: -2.895
10%: -2.585


My PACF ACF plot

Seasonal Decompose

Fit the ARMA to my data, red line is the predicted, blue is the observed

• Pulses , level shifts, seasonal pulses and local time trends can mask the identification of arima models . Why don't you post your actual data and I will try and help further . – IrishStat Apr 28 '20 at 22:58