Financial markets as complex networks of interacting traders exhibit universal features in proximity of critical transitions.
We developed a robust detection methodology to extract emergent patterns from the dynamics of market observables. Our detection runs in real-time on a wide range of timescales from minutes to days.
Model-based features inferred from financial time series are translated into signals that provide insights about upcoming market changes.
A specific set of financial instruments and detection timescales is tailored to customer objectives, which may involve active intraday trading, long-term asset holding, or market analytics and advisory functions.
Chief Executive Officer
Chief Science and Technology Officer
Blending computational physics, complex systems research, and technology management with entrepreneurial flexibility and persistence.