Machine Learning at Scale

Machine Learning at Scale

Proprietary machine learning algorithms run on AWS supercomputer infrastructure to generate entry and exit parameter sets for long and short models.

Patterns behave like locks and keys: historic sequences are stored so the model can match similar signals as market conditions evolve.

The system ranks millions of combinations per component, selecting robust parameter groups designed to withstand shifts in market regimes.