Whether by using statistical and mathematical modeling techniques, pattern recognition and machine learning techniques or by exploiting behavioral tendencies of market participants; our systems constantly search for statistical market anomalies that form the basis of our proprietary trading approach.
Methodologies such as trend and breakout, mean reversion, long/short, volatility and market events are just some examples of the patterns our systems search for.
Our behavioral trading approaches detect occurrences of almost imperceptible systematic price movements caused by predictable movements of large fundamental market players or that are result of market constraints e.g. seasonality.
By using machine-learning techniques our systems constantly update the significance of even the smallest identified deviations and anomalies in patterns and automatically fine-tune trading parameters.
By design, all systems use a build-in stop-loss methodology to avoid large drawdowns and to improve portfolio return patterns. Additionally, all our technology is designed to actively support our risk management process as our in-house low-latency order management system restricts transaction costs.