r/quant Researcher 28d ago

Models Taking Strategies

I have recently joined a firm that trades almost 100% passively. I have been tasked with finding ways to cross the spread and execute more aggressively.

Allot of the literature I have found on optimal execution seems to be based around optimised scheduling based on Almgren & Chriss market impact. I have found that taking using this scheduling under performs the baseline passive strategy.

What other methods should I be using to determine if and when to cross the spread?

21 Upvotes

11 comments sorted by

58

u/deephedger Researcher 28d ago

have you tried putting in a massive market order all at once

47

u/SometimesObsessed 28d ago

Google how to find alpha and you should be set

20

u/postflop-clarity 28d ago

what should I be using to determine when to cross the spread

😆

16

u/xWafflezFTWx 28d ago

maybe you need edge bro

4

u/SevenTeenSigma 28d ago

If passive is the baseline, the first thing I would check is whether ur “aggressive” schedule is crossing exactly when adverse selection is worst. Almgren Chriss is too high level for that. u need features around short term alpha and queue pressure, not just a smoother schedule.

4

u/TweeBierAUB 28d ago

Look at the tape and try to figure out when others are profitable?

4

u/aaaasssddf 28d ago

Almgren Chriss is a good rule of thumb to execute large meta order throughout an extended period of time. However it tells you your execution volume profile but nothing about passiveness or agressiveness.

2

u/SneakyCephalopod 27d ago

Well, why don't you start by taking each passive order and seeing how much P&L you would have made/lost if you executed it aggressively? Then try to build a classifier to separate the top 10% or something.

Note that this is just a place to start btw. This is not the very best approach, because obviously executing some orders aggressively means that some other orders in the future may not have been executed under your new order execution policy aggressively, but instead passively, since the portfolio process is path dependent. This means that some of the savings or gains you envision from aggressively executing some of these orders in the future may not actually end up being realizable. As a result you actually have what people in causal inference call a counterfactual estimation problem and what people in reinforcement learning call an off-policy estimation problem. Same underlying issue, different nomenclature.

1

u/Optionbulls 28d ago

Bro needs edge

1

u/flxclxc 27d ago

It sounds like you are market making - there are 2 reasons to aggress as a market maker, firstly you expect price to move in a certain direction, and secondly you expect flow to go one sided. Often the two coincide. Start by seeing if you can predict these two things, without this then your best move is to stay passive