Smells of AI writing: "Timestamps aren't enough. Exchanges need a stronger ordering primitive." etc
How exchanges turn order books into distributed logs
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Re: How exchanges turn order books into distributed logs
#12Earlier quoted context omitted.
Curious what your actual role was -- sounds very interesting! Project manager? Dev? Operations specialist? E.g. were you hired into this role, and what were the requisites?
I was what was called "Trade Desk". Many firms have them and they are a hybrid of: - DevOps (e.g. we help, or own, deployments to production) - SRE (e.g. we own the dashboards that monitored trading and would manage outages etc) - Trading Operations (e.g. we would work with exchanges to set up connections, cancel orders etc) My background is: - CompSci/Economics BA - MBA - ~20 years of basically doing the above roles…
Thanks for all the info!
I'm a front office engineer at a prop firm -- always interesting to get insight into how others do it.
We have fairly similar parallels, maybe with the exception of throwing new exchange connections to the dedicated networking group.
Always love watching their incident responses from afar (usually while getting impacted desks to put away the pitchforks). Great examples of crisis management, effectiveness and prioritization under pressure, ... All while being extremely pragmatic about actual vs perceived risk.
(I'm sure joining KCG in August of 2012 was a wild time...)
Re: How exchanges turn order books into distributed logs
#13> Every modern exchange has a single logical sequencer. No matter how many gateways feed the system, all events flow into one component whose job is to assign the next sequence number. That integer defines the global timeline. A notable edge case here is that if EVERYTHING (e.g. market data AND orders) goes through the sequencer then you can, essentially, Denial of Service to key parts of the trading flow. e.g. one o…
why would market data go through the sequenced stream on an exchange?
for an exchange: market data is a projection of the order book, an observer that sits on the stream but doesn't contribute to it
and client ports have rate limits
Re: How exchanges turn order books into distributed logs
#14This article both undersells and oversells the technical challenge exchanges solve. First, it is of course possible to apply horizontal scaling through sharding. My order on Tesla doesn't affect your order on Apple, so it's possible to run each product on its own matching engine, its own set of gateways, etc. Most exchanges don't go this far: they might have one cluster for stocks starting A-E, etc. So they don't eve…
Once sequencing is done, the matching algorithm can run with some parallelism. For example, Order A and order B might interact with eachother... but they also might not. If we assume they do not, we can have them processed totally independently and in parallel, and then only if we later determine they should have interacted with each other then we throw away the results and reprocess. It is very similar to the way sp…
Off the cuff, id expect this leads to less improvement than you might think. The vast majority of orders, especially orders arriving in sequence close to one another, are likely on a small set of extremely liquid symbols, and usually all for prices at or near the top of the book for those symbols.
Happy to discuss more, might be off the mark... these optimizations are always very interesting in their theoretical vs actual perf impact.
Re: How exchanges turn order books into distributed logs
#15Earlier quoted context omitted.
Once sequencing is done, the matching algorithm can run with some parallelism. For example, Order A and order B might interact with eachother... but they also might not. If we assume they do not, we can have them processed totally independently and in parallel, and then only if we later determine they should have interacted with each other then we throw away the results and reprocess. It is very similar to the way sp…
Off the cuff, id expect this leads to less improvement than you might think. The vast majority of orders, especially orders arriving in sequence close to one another, are likely on a small set of extremely liquid symbols, and usually all for prices at or near the top of the book for those symbols. Happy to discuss more, might be off the mark... these optimizations are always very interesting in their theoretical vs a…
in high scale stateless app services this approach is typically used to lower tail latency. two identical service instances will be sent the same request and whichever one returns faster “wins” which protects you from a bad instance or even one which happens to be heavily loaded.
Re: How exchanges turn order books into distributed logs
#16At a past job (hedge fund), my role was to co-ordinate investigations into why latency may have changed when sending orders. A couple of quants had built a random forest regression model that could take inputs like time of day, exchange, order volume etc and spit out an interval of what latency had historically been in that range. If the latency moved outside that range, an alert would fire and then I would co-ordina…
All technical problems are people problems
Re: How exchanges turn order books into distributed logs
#17Always fun to read about HFT. If anyone wants to learn about the Order Book data structure you can find it in JS here:
Re: How exchanges turn order books into distributed logs
#18This article both undersells and oversells the technical challenge exchanges solve. First, it is of course possible to apply horizontal scaling through sharding. My order on Tesla doesn't affect your order on Apple, so it's possible to run each product on its own matching engine, its own set of gateways, etc. Most exchanges don't go this far: they might have one cluster for stocks starting A-E, etc. So they don't eve…
> My order on Tesla doesn't affect your order on Apple
not necessarily
many exchanges allow orders into one instrument to match on another
(very, very common on derivatives exchanges)
Re: How exchanges turn order books into distributed logs
#19Very interesting. I wished to know the author. The site doesn't seem to have readily available information on the author.
Re: How exchanges turn order books into distributed logs
#20At a past job (hedge fund), my role was to co-ordinate investigations into why latency may have changed when sending orders. A couple of quants had built a random forest regression model that could take inputs like time of day, exchange, order volume etc and spit out an interval of what latency had historically been in that range. If the latency moved outside that range, an alert would fire and then I would co-ordina…
What kind of founding ethos doesn't allow tracking internal latency? Is their founding ethos "Never Admit Responsibility?"; "Never Leave A Paper Trail?"
This company's official ethical foundation is "Don't Get Caught."