Innolab believe that market prices are not random and there are persistent sources of alpha in markets that can be identified and harvested systematically.
To capture these inefficiencies, we use artificial intelligence and deep learning to create proprietary systematic investment engines.
While far from high-frequency, Innolab is sampling data, adjusting signals and return forecasts continuously, 24 hours a day for most asset classes in the world.
All research and models are deployed in a highly resilient, scalable, zero-downtime environment in the cloud.
Deep Learning can extract information from the markets that humans can’t.
Inefficiencies exist across asset classes that can be exploited.
Constant And Never-ending Improvement (CANI) is of great importance.
Making decisions based on evidence is far more reliable than ones based on instinct, assumptions or human emotions which can be biased.
Intellectual curiosity is a key ingredient for thinking differently and solving problems creatively.
Engineering experience can be used in financial applications with great success.
Deep learning seeks to uncover tendencies in historical data more efficiently than could be done by humans. These techniques can uncover robust and statistically significant patterns that would have been entirely impossible for a human being to uncover.