Graphical Algorithm Modeling
One interesting innovation that is being employed in conjunction with CEP platforms is the ability to implement new algorithms graphically. Graphical programming has always been a challenging area. Using graphical development environments to develop new programs on top of traditional languages, it can take as much time and knowledge as simply typing in the text of the language syntax. However, graphical modeling tools have been very successfully used in conjunction with CEP platforms. Modeling state flow and rules in an event-based system is well suited to graphical abstractions (see Figure 4).
As well as graphically modeling the logic inside their algorithms, today's tools give the traders the ability to visualize, in real time, all runtime activity once their algorithm is running. Real-time "dashboards" can display representations of the changing real-time variables within the algorithms, with automatic alerts when complex conditions or exceptions are detected. Dashboard design studios and runtime rendering frameworks act as a complete design and deployment environment with a wide range of visual objects, including meters, scales, tables, grids, bar and pie charts, along with trend and x-y chartsall of which change dynamically as events occur in real time (Figure 1 shows an example of a deployed dashboard). Elements are accessible through a design palette from which the objects can be selected, placed on a visual canvas, and parameterized. This capability removes the reliance on the technical development team traditionally required for the creation and adaptation of trading strategies.
One question that is occupying the minds of many with an interest in algorithmic trading is: "Will this ultimately replace the trader?" The answer is nofor now. Algorithms have expanded the capabilities of the trader, making each trader much more productive. It still falls to humans to devise new algorithms by analyzing, with computer help, opportunities in the changing market.
Algorithmic trading technology will only begin to replace humans if algorithms are actually devised, developed, tuned, and managed by other algorithms. There are already some techniques being deployed to this end.
One approach is the automatic selection of an appropriate algorithm to use in a particular circumstance, based on events occurring in the market at that point.
Another approach is the use of "genetic" algorithms, whereby a large number (potentially thousands) of variants of an algorithm are createdeach with slightly different operating parameters. Each variant can be fed with real market data, but rather than actually trading, can calculate the profit or loss it would be making if it was live in the market. Thus, the most profitable algorithm variants can be swapped live into the market on a continuing basis.
In all of these approaches, Complex Event Processing offers a compelling platform for the creation and management of trading algorithms. The promise of CEP is in providing a powerful platform to enable even the nonprogrammer to encode an event-based algorithm. This year, we will see increased adoption of this approach.
Algorithmic trading is just the first of many exciting applications of CEPin the financial markets, use in risk management and compliance are the obvious next steps. As we move into 2007, CEP will continue to revolutionize trading on the capital markets as we know it.