The outlook for compensation is certainly changing on Wall Street where credit derivatives traders could easily earn $2 million a year. But now that banks are faced with the need to reduce costs, trim headcount and comply with Dodd-Frank's derivatives reforms, algorithms are starting to unseat human traders in the credit instruments.
On Tuesday, Bloomberg News reported that UBS fired the head of credit-default swaps index trading, David Gallers, last week, and replaced him with computer algorithms. Citing unnamed sources familiar with the matter, Bloomberg's story said the bank replaced Gallers "with computer algorithms that trade using mathematical models."
The bank reportedly has no plans to hire a replacement.
The move should not come as a shock to those of us who have followed the evolution of electronic trading which has taken over equities and moved into options, futures, FX and fixed income. With Dodd-Frank pushing standardized swaps onto electronic exchange-like platforms, credit dealers are automating the trading to reduce costs. Also, credit dealers are going digital because humans are simply too expensive, Bloomberg reports.
Though credit derivatives have been one of the biggest money makers for banks, Dodd-Frank's push toward electronic trading is expected to reduce profits for the banks as prices become more transparent and spreads narrow for buyers and sellers.
Instead of emailing indicative prices to clients, the algo can automate pricing and publish them to screens.
According to the Bloomberg story, UBS released its algorithm last month, which can trade as much as $250 million of the Markit CDX North America Investment Grade Index and $50 million on the speculative-trade benchmark in one transaction. Algorithms also can slice and dice credit default index trades into smaller sizes, which has been a trend in U.S. stock trading.
"It's natural to push away from humans and large size to machines and small size, Peter Tchir, the founder of New York-based TF Market Advisors, aid in a telephone interview. "It's been gaining momentum."
The move by UBS follows the actions of several Wall Street firms including Barclays, Credit Suisse and Goldman Sachs, which already use computer models to trade credit instruments, according to Bloomberg.
Prior to the financial crisis in 2007, managing directors on credit derivatives desks were commanding $250,000 salaries and $1.75 million in bonuses, noted Bloomberg, which cites The Options Group as a source.
However, Tchir, a former credit derivatives trader, tells Bloomberg that developing an algorithm may cost a few hundred thousand dollars.
Another force behind the trend is that trading volumes in the Markit CDX high-yield credit swaps index have decreased 20.4 percent through Oct. 26 from last year, so with volumes in a slump, dealing desks are looking to cut costs. Other sources in the article suggest that banks like UBS are in a rush to roll out algos because it will help them to grab market share by offering the "best plug and play model" to institutional clients."
The algos can be utilized for small trades, where there is less risk at stake, enabling banks to free up sales people and traders to spend more time on solving more complex problems for clients.
But as the algos evolve they may handle larger size trades and become more popular as the market structure shifts. An algo offered by Barclays in April 2011, started handling trades as large as $25 million on the CDX investment-grade index and $5 million on the high yield index. But that has since doubled.
Another potential benefit is that when firms post margin and clear their trades under Dodd-Frank, algorithmic trades may allow traders to post less capital. Dealers instead can choose to focus on block trades and on designing dark pools where institutions can trade large size anonymously, a source tells Bloomberg.
However, buy-side institutions may end up preferring to trade through the algorithms. The algos in the market will become liquidity providers under Dodd-Frank, according to sources. The algos will respond to liquidity and widen or tighten the bid-offer spread based on the amount of flows available, Drew Mogaverao, Barclays' head of U.S. credit swaps trading tells Bloomberg.
Although many people fear algos given the fallout stemming from the 2010 Flash Crash, they may help dealers provide more liquidity.