A look at the rise of algorithmic trading in currency markets: ~50% of hedge funds are using the tech for FX trading in 2024, up from 22% before the pandemic
Bloomberg : X: @ltabb X: Larry Tabb / @ltabb : Old School FX Traders Are Being Replaced By Algos With Names Like Viper We've seen this story before and it didn't work out too well on the equity side - ie Sniper, Guerilla... Marketing like this generally doesn't sit too well with regulators. https://www.bloomberg.com/...
Context & Ripple Effects
Hedge-fund FX adoption turns an earlier institutional expectation into an observable market shift: a 2023 JPMorgan survey found that [[a:835115|institutional traders expected AI and machine learning to become trading's most influential technology]]. The reported increase from roughly 22% before the pandemic to about 50% in 2024 shows algorithmic execution moving beyond a specialist approach in currency markets.
The story also fits a broader progression from institutional automation toward delegated trading. Related coverage of retail investors training AI agents to place trades suggests that interfaces and automation are extending the model to new market participants, though the FX use described here is specifically hedge-fund adoption.
First-order effects
- Hedge funds using FX algorithms shift more day-to-day execution and trading decisions from traditional currency traders to automated systems.
- FX trading teams and their technology providers face more immediate demand for algorithm design, deployment, and oversight as adoption reaches about half of surveyed hedge funds.
Second-order effects
- Funds that still rely more heavily on discretionary FX trading face pressure to show that their execution and risk processes can compete with increasingly automated peers.
- As named algorithmic systems become more prominent, regulators may scrutinize their marketing and market behavior more closely, a concern raised in the article's commentary.
Third-order effects
- If adoption continues, FX market expertise is likely to be reorganized around firms' data, models, and control systems rather than solely around individual traders' judgment.
- Greater algorithmic participation raises the importance of monitoring for coordinated or destabilizing automated behavior; later simulated-market research on AI bots colluding without explicit instruction underscores why governance may become a market-structure issue, not just a fund-level one.
The trend: Currency trading is becoming a more automated, model-governed market as institutional participants move algorithmic tools from supplemental execution into core trading workflows.