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OptionsCity To Launch Algo-testing Integrated with Trading Platform

Freeway Analytics takes algorithms from simulation into production with a single click.

OptionsCity is preparing to launch Freeway Analytics, an algorithmic-trading program that allows traders to back-test their programs against real market scenarios – from flash crashes to a market rally, in real time, with historical data, and under fictitious scenarios.

The hosted solution will help developers build models and proof of concept trading strategies using Java and Scala. Should clients wish, they can deploy the trading and execution models to production using the same code and on the same platform.

Standard Hurdles

Those who produce algorithmic trading codes traditionally have a lot of custom ideas they want to test, and seek a system to create and deploy new algos with a simulator. Many turn to home-brewed systems, or competitors like Matlab, which will generally work fine, but once a code is completed, and the developers decide to run it, users have a difficult time transitioning their code into production.

“When I was a trader, we spent a lot of time building out simulation strategy,” says Andrew Lisy, product manager for Freeway Analytics. “It takes a long time to get the pieces in place, and I was usually doing so on a different platform than I would deploy on. So I’d have to write it again on the execution platform. Then we ran into issues of capabilities, different coding languages, etc.”

Trading firms and investment banks traditionally develop their own algos internally, presenting hurdles like properly simulating the market, high costs of development, testing, reporting, and ultimately reworking the code for deployment in the real market. In Lisy’s experience, traders find it too taxing to employ a team to meet all these goals. “They want the tools to reduce resources, and tools to hide a lot of the complexities not critical to their business” he says.

Streamlined Process

These issues have spurred on the development of Freeway Analytics, which is currently in beta with select clients, and will launch in late September.

When the back testing program is launched, it will leverage Vertex Analytics to provide data on options on futures and will offer a direct integration into Freeway, OptionCity’s multi-asset automated trading platform designed for deploying user-built algorithmic strategies, launched in 2011. According to CEO Hazim Dawani, users can opt to take their back-tested code off the Freeway Analytics platform and onto their own execution system, or simply “graduate” to Freeway and execute there.

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“We built this out of a combination of customers who have not adopted Freeway yet because they may not have a need to execute in microseconds, but they have a lot of ideas they want to test, and a want a platform to create new ideas with a simulator,” says Dawani. “When I was trading, a lot of what I put together on my own was a mix of programs. We’re trying to replace all of that and offer a better solution, essentially taking people who are cobbling together systems and put them on this instead.”

Becca Lipman is Senior Editor for Wall Street & Technology. She writes in-depth news articles with a focus on big data and compliance in the capital markets. She regularly meets with information technology leaders and innovators and writes about cloud computing, datacenters, ... View Full Bio

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User Rank: Apprentice
9/12/2013 | 2:08:31 PM
re: OptionsCity To Launch Algo-testing Integrated with Trading Platform
@Ivy G㢠if you use a trading simulator/simulation that covers edge cases and load/stress conditions along with a good code-coverage tool you can be confident in both the safety of your code and the supporting system (the platform logic and the algo's interface experience) that underpins it. Back testing against historic data alone is generally insufficient if you are concerned about resiliency, as you point out.
User Rank: Author
9/10/2013 | 1:48:54 PM
re: OptionsCity To Launch Algo-testing Integrated with Trading Platform
Transitioning algos into the real-time market runs the risks of erroneous or buggy, dormant code suddenly surfacing. We've seen this happen before. How does this process of backtesting and simulation help detect an error before it implodes in the live market?
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