BNP PARIBAS & MILLENNIUM GLOBAL INVESTMENTS (MGI) LAUNCH AI FX INDEX

  • Investment Management
  • 05.03.2019 10:57 am

BNP Paribas today announced the launch of the BNP Paribas MGI Systematic Currency Alpha Index using artificial intelligence through machine learning. The index, created by BNP Paribas in partnership with Millennium Global Investments (MGI), went live in Q1 2019.

MGI provides systematic FX Signals to BNP Paribas, determining the long or short exposure to four liquid currency pairs selected to represent the global FX market (USDGBP, USDEUR, USDAUD and USDJPY).  The Index can be considered as a new frontier for investors seeking cross-asset portfolio diversification, as it is enhanced by signals generated by an artificial intelligence model that uses machine learning to identify every day the dominant factors driving the performance of currency pairs. 

Francois Oustry, Head of Quantitative Investment Management and Innovation at Millennium Global Investments said: “Millennium Global’s foreign exchange systematic strategy was designed to provide an uncorrelated, diversifying stream of returns, and we look forward to collaborating with BNP Paribas to ensure that together we deliver a useful and effective solution for investors.”

Mark Astley, Chief Executive Officer of Millennium Global Investments said: “We are very pleased that BNP Paribas has selected Millennium Global as a product partner. We believe that by offering our innovative strategy through their platform, BNP Paribas will enable a wide range of users to gain access to a solution that is normally only available to large institutional investors.”

Matthew Yandle, Global Head of Structuring at BNP Paribas said:  “The collaboration with MGI allows investors to access a new class of quantitative signals in the FX markets with the aim to provide further diversification across risk factors. This new index broadens our range of systematic FX risk premia strategies for clients by combining BNP Paribas FX cost-efficient indices with MGI’s proprietary signals and risk management modules.”

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