Deleted for anonymity. Deleted for anonymity.

I’ll take this one. I work at an MM. we route trades through the firm’s OMS (order management system). This is basically a json interface where you specify execution broker(s) (depends what deals/ set up was done at a firm level, think bank execution/ trading services), algorithm (twap, vwap, broker custom algo (they all market a bunch claiming to add a splash of alpha (they don’t))), and a bunch of other fix like/ mapped tags. Some firms do do some internal crossing before sending the remainder out the door (this can be very nice)

From there the brokers try to match the schedule specified (ie don’t fall too far behind vwap and if so be more aggressive/ cross more), try to target lit market (exchanges) / dark (dark pools) as specified (or left to their discretion), try to have various levels of posting vs taking, etc.

Wrt to impact, that’s a very wide, but extremely important and as a result very studied question. Obviously it depends on size/ liquidity (top quintile liquid names take literally millions and millions to even have temporary impact (vs permanently impact)) and a host of other things. Generally people model it with a power law at the permanent/ temporary impact level. To just put a verrry loose fund size metric on it I’d say for folks trading a decent number of names (3k) in a l/s stat arb style day to week holding period, I wouldn’t even really worry too much about impact until at several hundred MM’s deployed in the us equity market. (Of course if you don’t model it well you could obviously hit impact a lot sooner than that with higher trading of lower liquid names, but assuming good pm skills/ size/trading limits in portfolio construction, that’s roughly where I see it really come in at/ start to be a serious cost to address)

Hope that helps and of course there are many other situations where “impact” occurs, just giving you my experience with it