Quant Robo Technology

SpeedLabs’s R&D develops our quantitative strategies and translates them into our QuantRobo Tech Software suite.

At SpeedLab we bring together a lot of different areas of expertise. Combining in-depth knowledge in quantitative methodology, real time data management, finance, soft-and hardware to create this seamless product we strive to generate the highest possible high risk premium.

The QuantRobo Tech Suite is series of modular products are designed to automate the entire value chain of the SpeedLab investment and risk management process:


    ensures concurrent management of multiple algorithms. Currently we are running a total of 185 robots across all portfolios at the same time


    provides intelligent adjustments of allocations in the RoboPortfolios reading market volume, speed, volatility and trends


    soon to be launched – automates parameters based on neural network approach

We design QuantRobo Technology based on the following best practices:


Ensures seamless functionality of the modules we create and algorithm scalability.

Technical Efficiency:

Secure and fast execution of algorithmic parameter decisions. We confirm our R&D results through extensive live test prior to deployment in any of our hedge fund products.


Data automated decisions are based upon must be reliable and proven, i.e. not only in back tests but in live trading. For back testing we rely on quality data using bid and ask data up to tick level. In addition, we adhere to strict and on a regular basis performed parameter optimization. Finally, we maintain highest standards in data security using state-of-the art hardware and a mirror server structure.

Trading Standards:

We work with generally accepted trading standards that are compatible with other trading systems.

Our fully automated, software-based systems are operated by purely quantitative-mathematical rules screening and running historical data on specific patterns. They produce sophisticated, complex digital algorithms free of any human emotion.