# Autocorrelate relative difference between two time series

I would like to verify the similarity of two time series. So far I have resampled and interpolated one time series, so that the two have synchronous time.

Next I have computed the relative difference to measure the difference between the two series. I have been recommended to compute the auto-correlation error by summing up the relative difference at each time lag. However, I am unsure if this is the correct way to go as I read that auto-correlational is computing the similarity of one series with itself.

Is cross-correlation what I need? Or RMSE? I don't need to measure how one series affect the other, but rather a difference (error).

Another question is that without resampling and interpolation, how I can compute the time lag between two time series? One series has way more samples than the other.

EDIT:

When I plotted the cross-correlation between the two series I get the below image. Does this mean that the two series are almost without error?