Am I interpretting this interaction term correctly? I am running a model with an interaction term and I am unsure of the interpretation even after reading the other questions here in the forum.
My model looks as follows:

Where roi is the return on investment, logfreq is the log transformed trading frequency and treated is the binary treatment variable.
My interpretation of the interaction:
The interaction term is negative implying that being treated leads to lower trading frequency.
Is this the correct interpretation? Any hint would be much appreciated, and I hope this does not seem too trivial.

You have two linear equations for roi as a function of logfreq, one for no treatment and one with treatment. To decide which one results in a larger roi, we have to know what range your logfreq values are in. In the code below, roi1 is the ROI in the treated case:
> logfreq <- seq(0, 10, .1)
> roi <- 0.11147 + 0.35369*logfreq
> roi1 <- 0.11147 + 0.35369*logfreq + 0.84900 -0.30848*logfreq
> plot(logfreq, roi, type = 'l', col = 'seagreen', panel.first = grid())
> lines(logfreq, roi1, col="steelblue") 


Here, the blue line is with treatment. Thus, if your values of logfreq are below $\approx 3$, treated will have a positive effect on roi, but above three, it will have a negative effect. Note, that this is independent of the value of the nonsignificant intercept.
More professional visualization of interactions can be achieved e.g. with the interactions R-package.
