Yesterday, The Wall Street Journal published an article titled “Algorithmic Trading: The Play-at-Home Version” highlighting the growth of a new crop of DIY tools that allow retail traders to easily automate their trading strategies. The users quoted in the article expressed excitement about having the ability to quickly build and deploy their own strategies, but they lamented that unforeseen issues in their algorithms led to sizable losses.
Since 1994, TT has been building tools to allow professional derivatives traders to automate their strategies. It’s encouraging to see the DIY algo programming trend start to migrate to retail traders, but the potential for loss with some of these systems is a detriment. To that end, allow me to point out a few differences between our approach and the others.
Our ADL visual programming platform represented a major breakthrough in algorithmic trading when it was first brought to market in 2009. Using drag-and-drop actions to assemble building blocks, traders and programmers alike can rapidly design, test and deploy automated trading strategies without writing a single line of code. With ADL, users can generate executable strategies in hours to seize and act on fleeting market opportunities in timeframes that were difficult or even impossible to achieve previously.
|With ADL, users drag and drop blocks containing pre-tested code onto a canvas to create automated trading programs.|
Instead of providing pre-made strategies, ADL allows the user to create custom algorithms by stitching together building blocks that convert to well-tested code, allowing for extreme flexibility. This approach eliminates syntax errors, while visual feedback and warnings provide built-in safety by guarding against undesirable algorithm behavior. Moreover, algorithms can be tested with live market data using TT’s robust simulated matching engine for a high degree of realism.
Algorithms are deployed to proximity-based execution servers to achieve ultra-low-latency performance no matter where the trader is located. Users can easily launch algorithms, update parameters and monitor each algo’s status from their workspaces.
We also provide risk management tools to prevent the scenario described in the WSJ article: “If things went wrong, he could lose his savings.” ADL is a visual platform written in a domain-specific language, which means that it can catch many common mistakes before the user turns the strategy on for the first time. This is possible because domain-specific languages are developed with a precise context in mind. As such, ADL can detect issues with blocks connected in problematic arrangements.
|ADL warns against potentially problematic logic.|
Such intelligent assistance could have minimized, if not mitigated, the programming glitches discovered by these users during live trading. So, too, could the use of the ADL “Risk block” that allows the algorithm designer to create self-imposed limits to guard against the consequences of undesirable algorithm behavior. And then there is the variety of limits that can be set in the risk and administration system by administrators.
ADL, which is an integral part of both our X_TRADER® and TT platforms, has been embraced by professional traders because of the flexibility and speed with which they can build, test and deploy custom trading strategies. The pace of technology advancement is breaking down barriers, allowing tools like ADL to be used by traders of all levels. As such, we will continue to focus on making ADL both an empowering and safe experience.
Stay tuned as we continue to iterate on ADL and roll out new enhancements. Feel free to reach out to us to learn more or to schedule a product demo. Or you can try the new TT platform yourself by going to trade.tt—it only takes a few seconds to create a demo account.
Posted by: Andrew Renalds, Product Manager