HFT signals are about detecting those patterns right before they occur, but as early as the information is available globally. For example someone just bought huge amounts of X, driving the price up, and you know Y is positively correlated to X, so Y will go up as well, so you buy it before it does.

X and Y might be fungible, correlated mechanically or statistically.

You can also do it on Y=X as well; then what you need is the ability to statistically tell whether a trade will initiate/continue a trend or revert. You only need to be right most of the time.

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.