I have two time series, spanning about 2.5k observations each. One series is observed values, the other one is predicted values based on a simple linear regression model. Both time series share the same unit.
I plotted both observed and predicted values along the observations (x) and now I am looking for a measure that continuously investigates the similarity/difference between them. At this point, I am not interested in the coefficient of determination or other measures of goodness of fit that give you one value.
I plotted the normalised difference between observed and predicted values along x (difference here as in simply subtracting predicted from observed values). This gives me another series with equal length (x).
I was wondering if there are any other statistical measures that investigate the similarity or difference between two time series. I would like to visualize such a measure, hence, any tests with a single value outcome are not what I am looking for right now. "Continuously" might not be the ideal word for what I am after, I merely tried to highlight that I am interested in a measure that is good to plot. Is there something like a "moving Pearson" and how would it work?
Happy for any suggestions!