[HolyLampshade]

There are really two schools of approach to this.

On one hand you have quantitatively driven strategies that try to predict either a price or direction based on various inputs. Here you’re mostly focused on predictive accuracy, and the challenge is in exiting the trade at the right time. This is where a lot of the speed comes into play (what is your predictive horizon, and can you act fast enough to take advantage of the current market prices?).

The other mode of trading tends to focus on structural mispricing in the market. An easy to understand example is an intermarket arbitrage trade where one market’s buyer or seller crosses prices with the opposite side of the market on another exchange. These events permit a trader to swoop in a capture the delta between the two order prices (provided they can get to both markets in time).

As easy opportunity has dried up (markets have grown more efficient as systems have gotten faster, and parties understanding of the market structure has improved) you see some blending of the two styles (this is where another commenter was talking about mixing a traditionally computed alpha with some hardware solution to generate the order), but both come with different technical challenges and performance requirements.

[vinay_ys]

Isn't there challenges with slippage and managing the volumes while exiting? And isn't speed also about processing the data feed as fast as possible to time the exit decisions accurately?

[HolyLampshade]

Absolutely to both questions, with different answers depending on what style of strategy you’re running.

The market mechanics trades tend to have no recoverability if you miss the opportunity, so you’re often trading out in error and it’s a matter of trying to stem the loss on a position that you do not have an opinionated value signal on.

And there’s definitely an angle to inbound processing speed for both styles of trading, with differing levels of sensitivity depending on the time horizons you are attempting to predict or execute against. Using the example above again, detecting the arb opportunity and firing quickly is obviously paramount, but if you’re running a strategy where you have a 1 minute predictive time horizon sure, there’s some loss that can be associated with inefficiency if you aren’t moving quickly and someone else is firing at a similar signal, but generally speaking there’s enough differentiation in underlying alpha between you and any competitors that the sensitivity to absolute speed isn’t as prevalent as most people expect.

Basically it boils down to going fast enough to beat the competition, and if there isn’t any you have all the time in the world to make decisions and act on them.

[cout]

This is true -- in the early 00's there was hardly any competition and we could take out both sides of a price cross with 100ms latency. Even after colocation we could still be competitive with over 4ms latency (plus the network). Trading technology has come a long way in 20 years.