Signal Timing Recovery, Loop Bandwidth and SNR
Ultimately we are trading how much signal we lose versus how much noise (phase noise dominantly) we are rejecting along with being able to track dynamics in the overall model between trasnmitter and receiver. If I was optimizing this I would do a simulation with the actual parameters for all noise sources and expected dynamics in my system, but I start with the rule of thumb as I suggested in this other post Loop bandwidth for symbol timing recovery of using something between $R/100$ to $R/20$ where $R$ is the symbol rate. The bottom graph shows the effect of a lower cut-off frequency in that more of the symbol energy is maintained. 

To see this consider the following graph showing a bi-phase signal (+1/-1) after passing through a high pass function. This also shows the motivation to not have an excessively long stream of all 1's or all 0's in the modulated data, which is one reason for data scrambling at the source (another reason is timing recovery).



The top graph shows the bi-phase signal with infinite bandwidth including DC. The issue with maintaining bandwidth to DC in the receiver is phase noise and timing drift. Ultimately the DC value that here is centered on 0 would drift as the receiver estimate of the transmit carrier shifts from true value. We use the received signal to track this, which is a high pass function. If we track too quickly, as in the second graph, we remove too much of the symbol energy since the carrier tracking loop with wider bandwidth would assume the new DC value representing the symbol is actually the carrier, thus removing it. A very long stream of 1's or 0's in a row would have the same effect. 

So the answer is to understand first what is the longest possible run of symbols that would not change in the receiver and then choose a loop bandwidth that minimizes the amount of symbol energy lost over that time interval, while ensuring the bandwidth is fast enough to track changing conditions and minimizing noise from low frequency sources such as phase noise.

As a rough measure of the impact of a loop BW using a loop BW of $R/20$, where $R$ is the symbol rate, consider that the single sided bandwidth of a properly pulse shaped waveform is slightly over $R/2$. If the loop BW was $R/20$ the SNR loss would approximately be 0.46 dB from tracking loss alone:

$$10log_{10}\bigg(1-\frac{R/20}{R/2}\bigg) =10log_{10}(0.9) = -0.46 dB $$

This can be decreased by lowering the loop bandwidth further (-0.18 dB for $R/50$), but you need to then see if you are adding more noise to this from the increased phase noise that would be added from the local oscillator and other jitter sources (sampling clock) as I show here PLL for Phase Demodulation and Carrier Tracking
, or if the dynamics in the system (Doppler for a moving transmitter or receiver for example) are changing faster than this can track. 

This graph I have shows the basic concept and to consider the optimization problem, and as depicted there typically is a long shallow bottom in choosing the carrier recovery loop bandwidth where the noise is minimized. In a properly designed receiver, amplified thermal noise would be the dominant noise source (the goal of analyzing the cascaded noise figure), and the carrier loop bandwidth should be within this region where that applies. LO and jitter noise sources are typically set to be 10 dB or more below this noise level so as to add only a small contribution to the overall noise figure budget. As we see in this graph, if we however set the loop bandwidth too low, the LO/Jitter contributed noise sources will start to dominate. If we set the loop bandwidth too high, then tracking noise (which is tracking out the modulation as I show above as well as self-noise that can be originate from our carrier tracking loop) will start to dominate. Overall this is a system design challenge as it considers all noise sources in both the analog and digital domain and is a great example of how such mixed signal implementations cannot be designed individually in a vacuum.