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@gumby_arc
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learning about crypto mm/hft -rust🦀
Joined December 2023
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I'm at around 2 months into this mm/hft rabbit hole.
I feel like you can learn by yourself most of what you will need to become a good dev, but finding good resources about trading is extremely hard
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my quoting system is finally working like I wanted, this is actually a good representation of the logic behind it:
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second day of testing live and it looks like I have some latency and fair price problems. Markouts are generally positive but once in a while I get very toxic fills from big taker orders
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this was not even 4 months ago, feels like ages
I will post my entire learning arc about crypto market making while building a bot from scratch. I will be trading on Hyperliquid with a $50M volume goal
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started building a simple mm infra as a uni project and now I can't stop working on it, integrating hyperliquid is the next week goal
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my infra is such a mess right now that it takes me ages to implement a new exchange
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I recently had to change how I model my bid/ask spread in order to quote a bit wider. Nothing special I just track volatility, trading intensity and inventory.
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I will post my entire learning arc about crypto market making while building a bot from scratch. I will be trading on Hyperliquid with a $50M volume goal
Switch to Hyperliquid for a holiday gift 🎁
CEX traders get 50% off fees for your first $50M volume. Go to to get started.
Fees become 0.012% taker and 0.002% maker rebate - the cheapest place to trade perps. All you need is an email to start trading.
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today I'm working on my theo model, never worked much on anything similar so it's a lot of stuff to process... I will probably spend a lot of time on this until I get back to other parts of my mm infra
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Do you guys have any advice on where to start from/study to build a fair price model? What would you focus on if you started from zero? ideas, books, papers and repos are welcome
today I'm working on my theo model, never worked much on anything similar so it's a lot of stuff to process... I will probably spend a lot of time on this until I get back to other parts of my mm infra
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I feel like I have a good idea on how wide my quotes should be in an optimal market condition. But when volatility spikes it seems like my quotes don't adapt fast enough. I'm trying to implement some simple feature to make my spread model more "reactive" in the short term
super busy with uni this week but I finally finished my spread model or whatever you want to call it. No more crazy things on volatility spikes, still feels far from perfect tho
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super busy with uni this week but I finally finished my spread model or whatever you want to call it. No more crazy things on volatility spikes, still feels far from perfect tho
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looks perfect, I'm providing liquidity to the other side of the book!
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abstracted all the exchange generic logic, I'm on the grind
my infra is such a mess right now that it takes me ages to implement a new exchange
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found this interesting repo on Poisson processes some time ago but not sure if any of this could be useful in prod
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I have to pick back up some stats books, it's time to level up my modelling skills
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still working on this damn quote updates queue, slowly starting to make more sense but it's not good enough yet
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should I try to quote at multiple depth levels to get a better avg fill price on this large market orders? I will probably test something live and quickly see if it's better or worst
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high volatility --> more inventory --> quotes get skewed to much on one side
opposite will happen when vol is little --> quotes remain almost symmetrical and I accumulate too much inventory
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I'm building a very simple market making infra for a university project (classic A&S model). I update my quotes every 1s and I want a wider spread as volatility increases. How do you model the volatility parameter so that it is meaningful for such a short period?
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just finished adding errors alerts and logs, what else am I missing on my dashboard? I don't want to add to much data tho
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@369brrr
@chameleon_jeff
@KasperLoock
@frothybeverage
Are there enough front runners worth front running tho?
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@BeatzXBT
Yeah I had a wrong param in my config file and the spread went crazy, no damage done tho
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@thodoha
mmh I see, also I guess rate limits could became a problem... but I guess that most of the times my theo changes I wouldn't have to cancel all orders at once
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@0xyieldmaxi
@twinkonchain
depends on the stakes, if low anything from 12 to 20 and more if I could find enough
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@TimMeggs
okay, will do soon. I put something together really fast because I didn't want to miss out and just now realized how bad it got over time
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let's say I want to start quoting more then 1 level per side, how do you decide at what depth you are going to quote the second level bids/asks. Any suggestions on how to build this?
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I'm not fumbling PURR here, would make sense if buying is rewarded more then just holding the airdrop.
But maybe this is just cope for not having a spot mm infra ready
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@cryptohound666
@TimMeggs
I think it's more about next tick prediction rather then second in hft
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ig it's time to move all the infra monitoring out of the main process, it's getting quite heavy on my ec2 instance. Do I keep error monitoring and move out the rest?
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I'm trading on OKX but a lot of data I use comes from other exchanges (Binance, Bybit...) How do you decide where to put your infra? (ali cloud, aws hk, aws tokyo)
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btw I removed any implementation of the A&S paper into my market making infra. I think it's a good theoretical paper but I don't find it useful for what I'm trying to achieve
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nice timing
HIP-1 and HIP-2 will soon open up for users to permissionlessly deploy on the Hyperliquid L1.
To recap, HIP-1 is a standard to deploy native tokens and onchain spot order books. HIP-2 permanently commits liquidity to a spot order book for HIP-1 tokens and synergizes with users'
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question for all CT quants: is the microprice paper by Stoikov a good starting point to build a fair price model for crypto markets? I'm thinking of adding more features to it other then the ob imbalance;
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imagine the future of decentralized exchanges if every dex could write docs like Paradex
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just learned this lesson. I thought that quoting a wider spread would remove the bad markouts (it kinda did) but it also removed all the good ones
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I'm currently quoting 1 order per side but I'm thinking about starting to place multiple orders at different depth levels. Is this the most common approach when market making crypto?
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I'm looking for exchanges with their servers in the HK region, anything other then OKX?
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Just asking because I see many people doing this and maybe there is some particular reason
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damn pricing funding rates is much harder then I thought... this thing is a mess
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Is there any reason to cancel orders and then make new ones instead of using the amend orders endpoint?
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@0xyieldmaxi
@BeatzXBT
@CantianSeven
mmh I will try something like this for now, might need to find a better solution later tho
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the main problem I've found is that the microprice is always somewhere between the bid and ask spread which doesn't seems to be a realistic assumption in crypto perps
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I've just realized that rather than trying to improve some of this bad fills I can just place less orders. Need to find the good middle ground so that I can grind some volume
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@MrEhpresso
@sasuke___420
@laurentzeimes
oh wow what's a good tick to trade latency in crypto?
I always wondered how fast is crypto hft but there are not many info out there
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The problem I've found when trying to skew quotes based on inventory is that I kinda get the opposite result of what I wanted.
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about my last post: I added a request queue to my mm infra. I no longer use a fixed interval between order updates. It's not completed yet but it's better then what I had before...
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@BeatzXBT
*from stackoverflow
The "T" or Trade time is the time of the transaction in milliseconds.
The "E" or Event time is the time value is inherent only to the sockets. It is associated with creating a socket object.
I still don't understand how there is such a huge difference in ms
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@BeatzXBT
Hey, I'm building something similar for a uni project but I'm having some problems understanding how to model short term volatility. How do you define a volatility range?
I'm building a very simple market making infra for a university project (classic A&S model). I update my quotes every 1s and I want a wider spread as volatility increases. How do you model the volatility parameter so that it is meaningful for such a short period?
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this is the first time I came to a roadblock in my project. I'm having an hard time understanding how to implement pricing features in my market making infra, I will have to do some studying before I can progress. Any resource or ideas are welcome
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I tried to work with this model but it seems like it is not the best solution for crypto because of the small tick sizes of instruments
question for all CT quants: is the microprice paper by Stoikov a good starting point to build a fair price model for crypto markets? I'm thinking of adding more features to it other then the ob imbalance;
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I have been working a lot on my simple market making infra in the past few weeks. Any tips on how to manage rate limits? Maybe there are some good repos out there but I can’t find any
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@BeatzXBT
no it's the same for the real time trade stream, there is 1-4 ms difference and I don't understande why
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