The application of high performance complex event processing technology to algorithmic trading is gaining a great deal of attention these days, and I’d like to share a few thoughts on this area. Just last Wednesday, we presented on this topic to an audience of about 40 senior Wall Street executives in New York.
Algorithmic trading is essentially the real time analysis and execution of transaction decisions in the financial markets. Strategies generally involve identifying patterns within historical data to predict future market behavior, and building rules into a model so that order placement timing may be optimized to cause the least impact on a stock's price.
Although the natural application of CEP to algorithmic trading is in the system which executes trading strategies, what really resonated with our audience is that many other components of the end-to-end-system require CEP. As depicted in the figure below these include up-front data cleansing and normalization, risk management and profit & loss, execution strategy and order management, exchange interfaces, and the integration of all of these complex event flows. CEP allows these to be done at considerably higher performance, much shorter time-to-deployment and at vastly lower lifecycle costs than traditional approaches.
Stay tuned for subsequent posts where I'll speak more about the best practices and capabilities in these areas.