UBS looks to machine learning to plug FX liquidity gaps
ZURICH (Reuters) – As global currency markets grapple with a growing number of flash crashes triggered by shutdowns in algorithmic trading systems when volatility spikes, UBS is utilizing machine learning technology to carry on dealing.
While algorithmic trading has played a growing role in the $5.1 trillion-a-day global foreign exchange market, accounting for up to a fifth of all trading and about 70 percent of all orders placed on multi-dealer currency platform EBS, machine learning is still relatively new.
UBS’s ORCA-Direct learns in real time, utilizing historical trading data to find the bank’s clients the best available liquidity when volatility rises.
First rolled out to a limited numbers of clients in May 2018, it helped volumes in the bank’s algorithmic FX business double in 2018. That made UBS the fastest-growing FX algo broker by market share from the second to the fourth quarter, according to Boston Consulting Group and Expand, a benchmarking house for financial institutions.
UBS is not the only large bank investing millions of dollars in algo technology as it cuts back on trading teams and relies more on automatically computed strategies to trade more efficiently.
JP Morgan, which also reported double-digit growth in its algorithmic trading business in recent months, has released a new machine learning algorithm, and Citibank is another top player in electronic currency trading.
ORCA’s machine learning enables the algorithm to determine within microseconds the best platforms and execution sequence to use, estimating the probability of trading and market impact for each specific order and reducing costs for the bank’s clients.
That can be crucial in the fragmented currency market, where about 70 different platforms exist with multiple banks, hedge funds and technology firms jostling for market share.
The growing number of flash crashes – where prices of currencies can swing wildly within seconds – also complicates matters.
“What is unique about ORCA is the machine learning we put into it,” said Chris Purves, head of the bank’s FRC Strategic Development Lab. “Clients…can see their executions improving, they can see their fill rates improving.”
While first-quarter figures are not yet available for algorithmic trading performance, UBS said growth has continued this year.
The bank expanded ORCA to U.S. Treasury trading in late 2018, with further roll-outs expected in the Foreign Exchanges, Rates and Credit (FRC) space.
Investment Bank Chief Operating Officer Beatriz Martín Jiménez said banks have traditionally focused on premium clients but new digital technologies would allow access to a broader customer base.
“The way forward for everybody is to build a platform where you’re going to be able to serve a much wider group of clients at a very low margin of cost per new client,” she said.
Its innovation lab expects to complete a further one or two major projects over coming months.
Meanwhile, from Tuesday until Thursday, UBS will hold sessions for employees on digitalisation and innovation.
“We’ve learned along way there’s a sort of science of innovation,” Purves said. “You can teach people to be better at innovation.”