4 ms·

> Basically, there's a bit of a spectrum of fast vs smart. In general it's hard to do incredibly smart stuff fast enough to compete in the "speed-critical" buc

by howlin 6y ago

> Basically, there's a bit of a spectrum of fast vs smart. In general it's hard to do incredibly smart stuff fast enough to compete in the "speed-critical" bucket of trades and vice-versa there's barely any point in being ultra-fast in the "non-speed-critical" bucket because your alphas last for minutes to hours. Depending on the overall strategy, you can be smart and fast at once. If you have occasional alpha harvesting opportunities that must be acted on quickly (very low latency but also low-ish frequency), then it is possible to spend the time in between trades modeling market context and developing optimal short-term plans for how to react in case of various market triggers.

traK6Dcm 6y ago
I think he means smart as in "how long your model prediction takes". If your neural net (haven't actually met anyone who uses these in trading) takes 5ms to make a prediction that'll lock you out of a whole lot of trading opportunities/strategies. Speed always matters, no matter where on the smartness spectrum you are, but it's relative. If your model prediction takes 5ms you're not getting much ROI out of investing $1M into shaving off 50ns in your data processing. But if your end-to-end latency without prediction is 1ms, you better invest in getting that down.
- howlin 6y ago
  > If your neural net (haven't actually met anyone who uses these in trading) takes 5ms to make a prediction that'll lock you out of a whole lot of trading opportunities/strategies. Let's say you have trading opportunities once every 100ms. They need to be acted upon within 2ms or they vanish. You don't have the time budget to run a NNet every time the state of the market changes. You can, however, train a NNet to output a very small decision tree that can run in under 1ms. The NNet can then decide which "micro-strategy" in the form of a much faster and more reactive decision tree is more appropriate for the current market context.

by howlin 6y ago

traK6Dcm 6y ago

I think he means smart as in "how long your model prediction takes". If your neural net (haven't actually met anyone who uses these in trading) takes 5ms to make a prediction that'll lock you out of a whole lot of trading opportunities/strategies. Speed always matters, no matter where on the smartness spectrum you are, but it's relative. If your model prediction takes 5ms you're not getting much ROI out of investing $1M into shaving off 50ns in your data processing. But if your end-to-end latency without prediction is 1ms, you better invest in getting that down.

howlin 6y ago
> If your neural net (haven't actually met anyone who uses these in trading) takes 5ms to make a prediction that'll lock you out of a whole lot of trading opportunities/strategies. Let's say you have trading opportunities once every 100ms. They need to be acted upon within 2ms or they vanish. You don't have the time budget to run a NNet every time the state of the market changes. You can, however, train a NNet to output a very small decision tree that can run in under 1ms. The NNet can then decide which "micro-strategy" in the form of a much faster and more reactive decision tree is more appropriate for the current market context.