The Tech Company That Predicted the Energy Crisis Six Months Ago — And Made a Fortune From It

An AI-powered energy trading firm predicted the Hormuz crisis scenario months before the Iran war began and positioned its clients to profit. Here is how it works and why it raises questions.

In September 2025, an energy trading firm named Stratagem Analytics — operating from servers in London and processing nodes in Dublin, with a 23-person staff and no permanent office — began systematically building long positions in European gas futures for clients including several major hedge funds and three European energy companies. The positions were not enormous by commodity market standards, but they were consistent, patient, and — in retrospect — timed with remarkable precision relative to what happened when the Iran war began on February 28, 2026.

By the time TTF prices had surged 70 percent in March, Stratagem's client positions were generating returns that, across the portfolio, exceeded 300 percent. The firm has declined to comment on its specific trading positions or methodology, citing confidentiality obligations to clients. But its founding CEO, speaking at a London energy conference in November 2025, described the firm's analytical approach in terms that are revealing in retrospect.

'We don't predict specific events,' she said. 'We identify scenario clusters — groups of scenarios with distinct probability distributions — and we identify positions that pay off across multiple scenarios within a cluster. The cluster of scenarios involving escalating US-Iran tensions, Gulf energy supply disruption, and European storage vulnerability was not difficult to identify from publicly available information. The question was always timing, and timing is something we are honest about not knowing.'

Stratagem's approach illustrates both the potential and the concern associated with AI-powered financial prediction. The potential: combining enormous volumes of public information — geopolitical reporting, shipping data, energy market signals, weather patterns, policy announcements — in ways that human analysts cannot replicate produces genuine predictive edge. The concern: firms that can systematically predict crises before they happen will position their clients to profit from those crises, contributing to their severity by amplifying market reactions once the scenarios they anticipated begin to materialize.