Our approach

What we believe in.

Investment beliefs

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 deep learning to create proprietary systematic investment engines. Through deep learning we analyse, forecast and rank all assets classes on a dailybasis.

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.

AI Investment Platform (AIIP)

Our engineering beliefs

Deep learning

Deep Learning can extract information from the markets that humans can’t.

Inefficiencies

Inefficiencies exist across asset classes that can be exploited.

Improvement

Constant And Never-ending Improvement (CANI) is of great importance.

Robustness

Strategies are rigorously tested before they are allowed into the portfolio.

Self-healing

Models are deployed as autonomous self-healing systems to ensure maximal stability.

Engineers

Engineering experience can be used in financial applications with great success.

Deep learning seek 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.

Peter Smedegaard
CEO AND FOUNDER
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