Hudson River Trading posted record quarterly trading revenues of $11.4bn as volatile markets created favourable conditions for proprietary trading firms and their market-making businesses.
The performance came during market volatility linked to the war in Iran and large swings in AI stocks. Proprietary firms such as Hudson River have benefited from those conditions, while specialist market-making divisions use advanced technology and models to profit from small differences in asset prices.
The scale of revenues across proprietary trading has also been substantial. In 2025, Jane Street, Hudson River and Citadel Securities made more than $60bn in trading revenues. Trading hauls this year have also outpaced those of trading desks at major investment banks including JPMorgan Chase and Goldman Sachs, which have themselves benefited from volatile markets.
JPMorgan Chase and Goldman Sachs also benefited from whipsawing markets even as proprietary firms’ trading hauls this year exceeded their trading desks. The comparison shows that volatile conditions have supported trading activity at both proprietary firms and major investment banks.
Jane Street has recorded significant revenues alongside a major investment loss. The firm reported a $15bn loss in July after an investment in Leopold Aschenbrenner’s hedge fund Situational Awareness, together with other AI stock investments, backfired. Despite that loss, Jane Street had generated more than $40bn in net trading revenues in the year to last Friday.
Market-making remains an important source of opportunity during choppy trading conditions. These businesses use powerful models and advanced technology to act quickly on small differences in asset prices, making periods of volatility favourable to specialist trading operations.
Hudson River has also made significant investments in AI infrastructure. Proprietary firms are competing to secure computational capacity and augment the trading models they use across financial markets. That competition for computing resources is taking place alongside the strong trading revenues generated during periods of market volatility.
Iain Dunning, Hudson River’s head of AI, has described the amount of computing capacity he expects to have next year compared with this year as exponential. He has also said the firm is already carrying out work that he had not previously imagined.
Hudson River’s record $11.4bn quarterly trading revenues therefore coincide with significant investment in AI infrastructure and a wider race among proprietary firms for computational capacity. The financial and operational picture combines strong trading revenues during volatile conditions with continued investment in the computing resources used to support trading models.
