Digital Assets Report


Like this article?

Sign up to our free newsletter

Euronext partners with Quant Insight

Related Topics

Quant Insight, a London-based firm specialising in machine learning-driven macro analytics, in partnership with Euronext, has developed a new alternative data service, Macro Risk Insight, to provide asset managers with insight into the risk exposure of their investments to global macro factors. 

Macro Risk Insight uses innovative quantitative techniques to help clients identify and quantify the key macro drivers, such as real rates, exchange rates, inflation and commodity prices, that drive the pricing of their assets and portfolios. The service, which covers pan-European blue-chip equities, uses Quant Insight’s proprietary adaptive models to calculate each stock’s exposure to macro factors. Additionally, it calculates the sensitivity of each stock for more than 30 individual factors and predicts the corresponding share price movement for a given change in the value of each factor.
Nicolas Rivard, Head of Advanced Data Services at Euronext, says: “Our clients are increasingly looking for high quality alternative datasets to help them manage their risk exposure, and we are working closely with a number of exciting new content providers, like Quant Insight, to develop the products that will help them with this challenge. We believe that Macro Risk Insight will be invaluable in helping asset managers to manage the risk exposure of their portfolios to a wide range of macro factors. It is the first of a number of alternative data products that Euronext will be introducing over the course of 2019.”
Mahmood Noorani (pictured), Founder & CEO at Quant Insight, says: “The influence of macro factors is growing across asset classes, and understanding the true underlying macro exposure of assets is becoming critical. This partnership with Euronext is a key step for Quant Insight in bringing powerful solutions to a much broader universe of clients.”

Like this article? Sign up to our free newsletter

Most Popular

Further Reading