Goldman Sachs Brings Algos to Fixed Income
Goldman Sachs has turned its algorithmic trading acumen towards the corporate bond market, reports the Financial Times.
The investment bank’s algorithm gathers publically available quotes and uses that data to provide a firm tradeable price to investors.
“Our trading desk receives thousands of inquiries every single day, and the Goldman Sachs Algorithm has allowed us to address these types of inquiries in a systematic and automated fashion that enabled our traders to focus more on more challenging situations,” Amy Hong, head of market structure strategy for global credit at Goldman, told the broadsheet.
Coming off a poor second quarter earnings in the credit market where it saw a 40% drop in bond-trading revenue, Goldman Sachs continues to ramp up its presence in the corporate bond market. The firm has increased the number of securities in which it is willing to quote by 200%. Later this year, the bank plans to expand into the junk bond market as well.
The firm plans to broaden its client base as well as its product offering to improve its bond trading revenue. The bank seeks to include more corporations and non-active managers, which it plans to approach with more cross-selling opportunities, said Marty Chavez, CFO of Goldman Sachs, during the firm’s second quarter earnings call.
We are “asking them how we’re doing with them, what’s working, what’s not, what they like to see more of and less of,” he said.
The deal will expand QuantHouse's US coverage.
Broker-dealer algorithms are evaluated, normalized and eventually rewarded for their performance.
Are trades executed in line with the intent of the orders?
Cowen estimates at least 6 basis points saved per block trade, more for less liquid securities.
eFinancialCareers reports that low-vol markets favor man over machine.