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In the Q3 issue’s Technology Forum, our panel of experts agreed that grid computing had not yet been fully harnessed to support automated trading. So Automated Trader asked Mike Stoltz, VP, Architecture and Strategy, Financial Services at Gemstone Systems, Inc, to explain how grid computing might support a theoretical automated trading strategy.
Get a Grid!
Mike Stoltz
The Scenario
A large proprietary trading operation wishes to develop a global, automated synthetic pairs trading programme across its offices in New York, London and Singapore. In its first phase, the objective is to identify baskets of instruments that can be traded as synthetics against individual real securities. In its second phase, the intention is to extend this strategy so that both legs of the pairs trades consist of synthetic instruments.
The intention is that the strategy will involve multiple security types denominated in various currencies and that it will also operate across twenty different timeframes (ranging from one minute to daily data). Combining these factors with the need to conduct in- and out-of-sample testing for cointegration means that the computational requirements will be very significant from the outset, but will expand substantially with the second phase of the project.
Furthermore, the trading operation is making the assumption that the tradable pairs arrived at after ‘out of sample’ cointegration testing will not be stable (i.e. the cointegration relationship will probably decay), especially in short timeframes. Therefore, the decision has been made that development and testing must be continuous, so all calculations and testing on all possible pairs and timeframes will be updated in real time. In the case of shorter time frames, this will result in calculations having to be performed during market hours. The intention is not to have a ‘Big Bang’ go live, but a gradual ramp up. Initial testing and trading will only involve a subset of the final instrument universe, but will still be conducted across all three locations.
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