With global energy markets facing unprecedented challenges and opportunities, X Machina Capital Strategies (“XMC”) today announced its formation. The firm will employ a new systematic, quantitative approach to private investing in energy and commodities. X Machina Capital Strategies seeks superior returns without relying on commodity price appreciation or taking credit risk to the operator.
XMC’s team, led by Talal Debs, PhD, managing partner, offers exceptional technical and commercial capability and the experience to advance these innovations. The XMC vision combines key themes from energy and commodity markets, systematic quantitative investing, and insurance. Each of XMC’s senior advisors brings unparalleled expertise in these areas: Catherine Flax, most recently former head of commodities, foreign exchange, and emerging markets for the Americas at BNP Paribas; Brian Hurst, formerly a leading partner at pioneering quantitative fund manager AQR Capital Management; and Mike McGavick, former CEO of XL Group, a global leader in traditional and innovative insurance solutions and services.
Debs, who previously led J.P. Morgan’s Reservoir Engineering and Technical Analysis team within its market leading Oil and Gas Finance business, commented: “We see a new risk factor, ‘dynamical risk,’ as the missing link to breaking past value-destroying patterns of investment in energy. XMC is focused on how this insight and others like it, which constitute our foundational approach, can invigorate this crucial segment of our economy.”
To learn more about X Machina Capital Strategies’ new approach to private energy investing, visit www.xmcstrategies.com.
X Machina Capital Strategies LLC (together with its affiliates, “XMC” or the “Firm”) is a new breed of asset manager. Based in New York, the firm develops systematic, quantitative strategies for private investment in energy and commodities. It uses a distinctive analytical approach – foundational analysis – that goes underneath and beyond the limitations of current market assumptions. XMC improves upon standard fundamental approaches by applying the physics of natural systems, powered by newly available data sets, machine learning, and modern data science.