Question: I start to work with a dataset with more than 3000 samples, and realize that ACF plot does not make sense with respect of confidence intervals, see figure.

[![enter image description here](https://i.stack.imgur.com/SXbla.png)](https://i.stack.imgur.com/SXbla.png)

My purpose is to fit an ARIMA on this, however, I'm not sure if it's a good choice because of this large sample size, as @IrishStat [answer](https://stats.stackexchange.com/a/185555/143783) alerts. Does anyone recommend an approach to handle this ACF plot to model the ARIMA?

**EDIT**: In acf, the first lag inside interval confidence is in something about 400.

Answer: 
From the ACF plot, it seems there is periodic behind it , try the seasonal difference. 

If possible, do the unit root test to make sure the series is stationary before chooses the parameters for arima .
In case of a large sample you don't need to do ACF, you can use spectral analysis with periodograms, FFT etc. ACF and ARIMA is a poor man's spectral analysis when the sample is small. Whether 3,000 is a large sample is a different question