Tuesday, August 9, 2011

##high frequency trading system expertise

Background -- what asset classes are we talking about? Equities, FX, index futures, listed options, US/German government bonds, ED futures, ...See also http://bigblog.tanbin.com/2011/06/algorithmic-vs-high-frequency-vs-low.html.

Here are some basic features/techniques of HF (high-frequency) systems. In other words, HF trading systems compete on these --

1) latency - see other blog posts such as http://bigblog.tanbin.com/2011/08/low-latency-key-expertise.html

2) algo trading -- a mature body of knowledge and technique starting from vwap/twap, Arrival-Price, Implmentation-Shortfall ...
** trade origination

3) market data -- basis of algo and latency techniques. HF systems have higher requirement for market data

?) real time risk measurement/control -- i feel risk system is different if you do thousands of trades a minute. I know some HF shops run trading engine on autopilot, so risk system is not a barometer for a trader to look at

---- Above are the 3 aspects I know ----

4) architecture? Do HF system demand a special architecture? I think A) latency and B) market data volume dictates architecture

5) pricing model? It's Part of every trading algorithm, but are they any different from the regular run-of-the-mill pricing engine in every automated trading system? Well, there are models and there are models. I feel algo trading models are slightly more [1] sophisticated than pricing models in other pretrade pricing engines.

[1] sometimes less. In practice, some HF engines compete on latency and seeks small profit on each trade, so pricing is probably simplified.

I feel HF systems sometimes use simpler pricing models than non-HF. However, it's possible that for a given instrument a large percentage of HF trades come from a single trading engine, and that engine happens to use a simple or complex, fast or slow pricer. I won't argue with such statistics. I'm only giving a personal perspective.

The more sophisticated pricing models usually exist in time-insensitive pre-trade Aanalysis or post-trade phases (no such luxury in the millisecond real time battlefield). They often analyze a larger body of market data, unconstrained by latency of data analysis. They often involve time-consuming simulations. They often involve optimizations. They may output a price decorated with a bunch of metrics about the quality of the price. Such output is often intended for a human consumption not machine consumption.

Now, if another buy-side runs a traditional trading system to compete against a HF, latency-gap alone could spell defeat - consider front-runners

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