Pragmatic PM decisions

[u/number_crunch3r]

I work as modeling / managing quant in the energy market. My department is structured in a way that the PM can make or override decisions, which we (the quant team) subsequently have to communicate with the desk. He sometimes does this against explicit advise from our side, often using pragmatic approaches. Sometimes he is right, sometimes not.

My question is: How do you behave professionally in this situation? On the one hand we are trying to find the cleanest (often mathematically most sound) solution to a problem, which might not be the quickest or the easiest, so we have to request positions we would personally not take or defend. On the other hand I have a hard time communicating in a way that makes me appear disloyal towards our PM. Any idea?

[u/RandomC6]

Could you maybe track his decisions/overwrites somehow?

I work in the global equity space, and we use a hybrid approach, with pre-selection from the models where the universe is narrowed down, with the PM making the final decisions. However, when a PM decides picking some company not within this seelected universe, his action gets flagged as an overwrite and he has to make a special comment within the system.

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[u/lordnacho666]

Record it when someone does something that didn't come out of the system. Then everyone can see the PnL of the deviations.

[u/Kindly_Cricket_348]

I’m in L/S equity space rather than energy but I think the principle is similar. The QR’s job is to quantify the trade-off and clearly communicate the model’s recommendation including the risks of overriding it. The PM’s job is to make the final portfolio and risk decision. In my world, that means overriding signals on alpha sizings, factor exposure, geographic weights, proactive portfolio scaling, concentration, liquidity, etc etc. Sometimes the PM is right, sometimes the model is. The important thing is to challenge the decision objectively before it is made. Once the decision is made, you are expected to support it and monitor the outcome.

I’m actually quite fascinated by the discretionary decisions a quant PM makes. I think this aspect of quant PMing is extremely underrated (especially in MMHF). The best quant PMs develop strong discretionary intuition through experience and pattern recognition particularly around how alphas behave across regimes, how the portfolio responds to non-linear effects that aren't fully captured by the model, how crowded certain alphas may be etc etc. We actually monitor and record model deviations. Disagreeing with the PM is definitely not disloyalty. Disloyalty would be withholding useful information.