Using AI to uncover hidden factors

Fundamental equity risk factor models can be combined with the power of statistical models.

Identifying hidden factors is extremely important, especially for hedge fund strategies. For statistical arbitrage or market neutral managers, hedge fund traders will want to mitigate that risk. For discretionary or macro strategies, traders may want to take a directional bet, based on this hidden factor.

Bringing together equity risk factor models 

Equity risk factor models can help hedge fund managers understand risk factors and exposures and can be an important part of their toolset. Statistical factor risk models can potentially pick up sources of risk not captured by a linear fundamental risk model. They are very powerful but lack intuitive explanatory power because the fundamental factors get jumbled together. Linear fundamental risk models, on the other hand, provide a good understandable story but are limited by their factor set, potentially leaving more unexplained residual risk on the table. The standard assumption is that this fundamental residual risk is random and unstructured. Or is it?

In this research report, you will learn about a factor included within the latest version of our equity risk factor model that brings together the explanatory power of fundamental models with the dynamic combinatorial power of statistical factor models, enabling managers to better pinpoint sources of risk and return.