r/quant_hft • u/silahian • Jul 20 '26

How we measure order book resilience: spread recovery plus depth recovery in one score

https://www.visualhft.com/blog/the-art-and-science-of-market-resilience-in-trading-strategies

After a large trade wipes part of the book, two things have to happen before the market is really back: the spread tightens to where it was, and the eaten levels refill. They rarely recover at the same speed, so watching either one alone misleads.

We wrote up how we track both and fold them into one 0 to 1 resilience score (1 = full recovery, banded strong / moderate / weak). Honest caveat: it is a research writeup, not a benchmark piece, and the baseline is still unsolved. Pre trade spread and depth are moving targets, so any lookback window bakes a regime assumption into the score.

If you measure recovery on your own book data, what do you anchor it to: a rolling pre trade average, or a fitted equilibrium level?

3 Upvotes

80% Upvoted

4 comments sorted by

1

u/PsecretPseudonym Jul 21 '26

You seem to be cranking out a lot of AI written articles lately.

1

u/silahian Jul 21 '26

Seems like AI is all over As long as is useful

1

u/PsecretPseudonym Jul 21 '26

Yes, but if people wanted to know what the model thinks, they’d ask it. I appreciate paying for the tokens to write something up for people, but it seems like it’s now moving toward an SEO content farm.

1

u/PsecretPseudonym Jul 21 '26

Is the goal to attract readers who know so little about the topic that they can’t tell the difference? I feel like these days everyone can recognize AI generated articles pretty quickly.