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A-Team Insight Blogs

Opinion: Hybrid Algorithm Development Environments for Intelligent Trading

By Jamie Oschefski, Head of Accounts and Strategic Partnerships, Quantica Trading

It is becoming clear the latency arms race is quickly becoming a theme of the past. The fastest microwave networks between Aurora, Ill., and Carteret, NJ, is currently clocked at about 4.14ms (one-way), where the theoretical minimum is 3.95ms based on the speed of light. With only 0.19ms of improvement, this variable is fast approaching the physical limitations of the universe set by quantum mechanics and relativity. The unimaginable barriers to entry and exorbitant overhead in maintaining and advancing the infrastructure and technology required to keep a competitive edge, only a few trading firms can play in the space.

So where’s the new edge?

The focus in no longer on how fast a firm can trade, it’s on how fast firms can get from idea to execution. The opportunity is in the ability to get new or updated strategies to market in the shortest amount of time, whether it be through an intuitive development environment or the use of drag-and-drop strategy building tools.

One of the biggest changes in the financial markets industry has been the deployment of drag-and-drop technology, which allows traders to put their own strategies into production themselves without the need for any programming background. Our clients are looking for broker-neutral solutions that allow them to rapidly construct, test and globally deploy extremely complex strategies across all asset classes with the path of least resistance. What’s needed is to blend the speed of deployment of modern algorithmic development techniques with rigorous quality assurance and testing disciplines.

The process of connecting algorithm ‘states’ through rules-based signal generation is mirrored behind the intuitive interface with the underlying code. The user is essentially manipulating the building blocks of the complex event processor (CEP) with a variety of parameter values (such as looking at the NBBO spread or using a specific technical indicator), which are automatically inserted correctly into the code.

Conventional methods of developing quantitative or systematic trading strategies involve standard programming languages such a C++, JAVA and C#, or proprietary scripting languages commonly used by vendors as a tactic to ‘lock-in’ their users. The advancement in drag-and-drop strategy design has opened the door for firms to seek out hybrid development environments. When you eliminate the need for ‘coding’, you substantially decrease the time required for debugging and testing for correctness while virtually eliminating the opportunity for coding errors. That said, there will always be a need for a development environment specifically for the firms with highly skilled programmers.

Technology vendors with the ability to provide clients with a truly hybrid solution to incorporate the ease of a high-level drag-and-drop environment for visual construction, with an extensive lower level development kit specific for algorithm design, will ultimately come out ahead. Traders and computer scientists usually speak a different language, and this hybrid toolset will create a culture where traders and developers can actually work together.

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