Most trading firms are past the whole "beat the other guys to buy". Established large investment firms already have all that on lockdown in terms of infrastructure and influence to the extent where they basically just run the stock market at this point (i.e Tesla posts horrible quarter numbers, but stock goes up).
Most of the smaller firms basically try to figure out the patterns of the larger firms and capitalize on that. The timescales have shifted quite a bit.
No, there are absolutely electronic trading markets where a difference of milliseconds of latency to certain events is worth more than a M PnL. That’s a long time.
The top trading firms are firing off orders in double digit nanoseconds, not milliseconds.
In some cases the order leaving the card starts to emerge before the packet containing the market data event that they're responding to has even finished arriving.
Waiting for a full microsecond for the packet to arrive before responding means you're already too slow
Doesn't the fact that a modern FPGA-centric (probably ASICs in the mix too at this point) hybrid NIC/order-parser/state-machine thing is rumored to be able to hit glass-to-glass of ~20-40ns mean that the speed game is hotter than ever?
Do you mean that because it involves a lot of hardware design now? The days of being able to offer around the inside in C++ on a regulated securities exchange are over, but there's still C++ driving the thing, that 20ns "tick to trade" or however it's being measured in some instance is still pretty basic response stuff, light speed is still a thing. There's a C++ program upstairs running the show, and it's trying to do it's job in under a mike for sure.
But there are more recent talks (Optiver is especially transparent about it but other people talk about it too): https://www.youtube.com/watch?v=sX2nF1fW7kI, that's David Gross at CppCon last year, it can't have changed that much since last year.
Thats all cool and all, but the major trading firms own properties that are all physically connected to the exchanges faster than any competitor in terms of physical location and routing.
No matter how fast you process the data, the ping difference of 1ms is going to be an advantage that you can never beat.
There is a reason why firms like HRT trade mostly in derivatives and futures.
That’s irrelevant to the fact that the expected PnL on a millisecond of latency improvement is a lot more than 1M in some markets. Obviously if you are getting what ever trade you are concerned with off in less than one millisecond, the question isn’t well posed.
There are many more games to play than delta one takeout and the solutions certainly don’t fit on one or a handful of FPGA’s.
I took the parent post to mean that a few large firms have emerged as clear winners of the speed game, and most other companies compete on (relatively) longer time scales now.
It's not uncommon to have a fast core and then an API that alpha / research teams feed signals into
if you are someone like HRT I presume the bulk of their money comes at very short holding periods so you have e.g. fast signals that work short term and then mid frequency alpha signals that spit out a forecast over a few timeframes i.e. it might not be that they buy (aggressively) really quickly but rather than someone sells to them and then they hold onto the position for longer than they would if they have no opinions.
Similarly this shapes where you post your orders e.g. if you really want it then you want to be top of the book
Well there's gonna be people writing code who can't do it in say a high performance C/C++ setup. Not professional programmers, but professional <some finance discipline>.
Sometimes it will be worth the tradeoff to put that person and a programmer together to code up a solution in another language. Sometimes it will be worth it to have the non-programmer write it in Python and then do Herculean things in the background to make it fast enough.
The gulf between high performance C/C++ and Python is vast and includes most other programming languages, many of which are friendly to write or can be made friendly to write for a limited domain, with significantly less rocket science needed than making python faster.
Even at the speediest trading firms, the large majority of code is not latency sensitive. Systems and algos are structured such that the fast acting stuff is simple and contained.
Honestly if you're a millisecond too slow you might as well not trade at all. From my own experience with trying to get Python to go fast for crypto trading, you can get it pretty fast using Cython - single digit microseconds on an average AWS instance for a simple linear regression was my proudest moment. They're probably pushing it even faster because nanoseconds are where the money's at. Many HFT firms are down in the double digit nanoseconds, I believe. Maybe lower.
In crypto, you have centralised (e.g. Coinbase) and decentralised exchanges (e.g. Uniswap). Decentralised exchanges operate onchain via smart contracts.
Most trading firms are past the whole "beat the other guys to buy". Established large investment firms already have all that on lockdown in terms of infrastructure and influence to the extent where they basically just run the stock market at this point (i.e Tesla posts horrible quarter numbers, but stock goes up).
Most of the smaller firms basically try to figure out the patterns of the larger firms and capitalize on that. The timescales have shifted quite a bit.