At AI Alpha Lab we strive to optimize the intersection of domain knowledge from finance and machine learning. A thorough understanding of the structure of financial markets exploited through the use of advanced artificial intelligence enables us to provide risk adjusted excess returns to our clients both within and across asset classes.

The investment world is predominately relying on a reductionist investment approach rooted in how we believe markets should behave and rationalized through linear economic theory, most of which has failed to be practically applied to investing. These models adhere to our desire for simple linear explanations and intuitions, but are rarely significant in their explanatory efforts.

Today we don’t need to rely on simplistic models, reliance on averages and questionable assumptions. We can do advance signal extraction from complex data, resulting in much better and stable outcomes.

We have combined the non-linear features of deep neural networks with a probabilistic framework routed in Bayesian thinking, thereby enabling us to explore the non-linearity in financial markets, without running the risk of over-optimizing our model.