How to understand the filter coefficients in FIR filter
2-tap FIR filters can be understood with a simple intuition (I use Python for plotting, but freqz is the same there).

Let's start with two taps with the same value: b = [1, 1]. This lets through constant signals (e.g. [1, 1, 1, ...]) but will more or less block rapidly changing ones (e.g. [1, -1, 1, -1, ...]), i.e. it is a lowpass:

w, h = scipy.signal.freqz([1, 1], 1)

plt.plot(w, abs(h))




On the other hand, b = [-1, 1] will do the opposite: let changing signals pass but block constant ones, i.e., we have a highpass.

w, h = scipy.signal.freqz([-1, 1], 1)

plt.plot(w, abs(h))




I'm not sure it is straightforward to expand this intuition to more complex signals like yours. But looking at the shape, I would expect some band-pass behavior (because we have both high- and lowpass components) with a peak frequency around one third of the sampling frequency (because a signal like [1, 0, 0, -1, 0, 0, 1, ...] will be able to pass). This apparently isn't so far from the truth: