The changing face of FX quants
The role of quantitative traders in the FX market is becoming ever more significant, as the amount of business executed via algorithms continues to increase.
Sell-side firms offer innovative FX algos to attract clients to use their platforms, usually on an agency basis, where they are paid by commission.
From a bank’s perspective, this is a low-risk activity driven by investment in low-latency technology as well as quantitative excellence, with quants driven to improve the sophistication of execution algorithms to reduce market impact and achieve benchmark goals.
While demand for quants has risen, the range of skills required to be an algo quant has also expanded. As well as understanding the algo methodology, they need to be aware of the microstructure of trading on different venues and understand the associated risks of market impact.
The amount of FX data available has increased massively in recent years, leading to a greater use of data mining and machine learning to extract more useful analysis, observes Jamie Walton, former head of quantitative analysis at Morgan Stanley and co-founder of Raidne, a provider of independent quantitative surveillance.
These techniques are required to create next-generation algos that can respond to microstructure signals dynamically, he says.
“As the arms race to reduce market impact and improve benchmarks grows, we are seeing the sophistication of algorithmic techniques grow proportionally – justifying the investment in quants to undertake the analysis and build new algos,” says Walton.