The Lynx Program posted a strong first half of 2026, returning 25.9 percent, its second-best first-half performance in its 25-year history. Lynx Asset Management’s flagship trend-following strategy outperformed its peers in the Société Générale Trend Index in every single month during the period, while the index itself advanced 9.1 percent. A backdrop of resurgent inflation, escalating tensions between the U.S. and Iran, and widening divergence in global monetary policy created an uncertain but ultimately highly favorable environment for the $7.4 billion strategy.
While trend following remains the cornerstone of the Lynx Program, the strategy also allocates a portion of its risk budget to complementary systematic models designed to generate returns in market environments where traditional trend-following signals are less effective. These diversifying “alpha overlays” include machine learning, systematic macro, and other idiosyncratic strategies, helping the Nordic region’s largest hedge fund outperform many of its global managed futures peers during the first half of the year.
“The Program’s robust performance in the first half of 2026 reflects both favorable market conditions and the strength of our diversified approach, which combines modern statistical trend-following models with machine learning, systematic macro and other idiosyncratic strategies,” writes the Lynx Asset Management team, led by CEO Martin Källström, in a report to investors. “We remain committed to enhancing and evolving our systematic process, refined over more than two and a half decades.”
“The Program’s robust performance in the first half of 2026 reflects both favorable market conditions and the strength of our diversified approach, which combines modern statistical trend-following models with machine learning, systematic macro and other idiosyncratic strategies.”
Performance was broad-based across both asset classes and trading models. Equity indices, commodities, currencies, and fixed income all generated positive contributions, while attribution was split almost evenly between the Program’s core trend-following models and its diversifying strategies. Although the Société Générale Trend Index returned 9.1 percent over the same period, Lynx benefited from particularly strong contributions from its complementary models. Machine learning strategies were particularly successful in identifying opportunities in equities and fixed income, systematic macro models generated strong gains in energy markets, and short-term trend models helped keep the Program profitable during the more challenging months of March and June, when many trend-followers struggled.
While the first-half results were noteworthy, the Lynx Program’s longer-term track record remains equally significant. Since inception more than 25 years ago, the strategy has generated an annualized net return of 9.6 percent with annualized volatility of 14.6 percent. Over the same period, it has maintained a correlation of negative 0.12 to global equities, underscoring its diversification characteristics within a broader investment portfolio.
