# How to interpret the Score-Based CUSUM test results?

Context
I'm doing an analysis of a price time series and checking for structural breaks (s.b. further on). One of these tests is the Score-Based CUSUM test. As far as I understand, this test is more dedicated to checking the instability of coefficients of the model fitted to the series. However, it is often proposed for s.b. testing (e.g. this post).

I use 3 lags for prediction (i.e. each new point is forecasted using 3 previous points); also I use efp from R:

res = efp(y ~ y1 +y2+y3, data = d, type = "Score-CUSUM")

The output is the following:

Also, I use sctest(res) to obtain the p-value.

Questions
Q1. What do the plots show to us?
Q2. What hypotheses sctest(res) tests in the given case.

Any hint is welcome.

NB. The series itself is the following:

Q1: The panels show the appropriately scaled cumulative sums of the model scores for each parameter. The coefficients of y1, y2, and y3 seem to fluctuate randomly while the process for the intercept and the variance have a distinct peak at around 40% of the data. This signals that the parameters decreased at about that time (because the cumulative sum switches from going up to going down). While the peak in the intercept is not large enough to cross the critical value, the process for the variance clearly exceeds the boundary formed by the critical value.