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(双语新闻) 摩根大通研发机器人执行金融交易


希尼尔翻译公司(www.sinosenior.com.cn)2017年8月4日了解到:JPMorgan will soon be using a first-of-its-kind robot to execute trades across its global equities algorithms business, after a European trial of the bank’s new artificial intelligence (AI) programme showed it was much more efficient than traditional methods of buying and selling.

The AI — known internally as LOXM — has been used in the bank’s European equities algorithms business since the first quarter and will be launched across Asia and the US in the fourth quarter, Daniel Ciment, JPMorgan’s head of global equities electronic trading, told the Financial Times.
摩根大通全球股票电子交易业务负责人丹尼尔?西蒙(Daniel Ciment)告诉英国《金融时报》,在内部被称为LOXM的这款人工智能自第一季度以来被用于该行的欧洲股票算法业务,并将在第四季度在亚洲和美国启用。
LOXM’s job is to execute client orders with maximum speed at the best price, by using lessons it has learnt from billions of past trades — both real and simulated — to tackle problems such as how best to offload big equity stakes without moving market prices.
“Such customisation was previously implemented by humans, but now the AI machine is able to do it on a much larger and more efficient scale,” said David Fellah, of JPMorgan’s European Equity Quant Research team. Mr Ciment said that, so far, the European trials showed that the pricing achieved by LOXM was “significantly better” than its benchmark.
“这种定制操作以前是由人实施的,但现在AI机器能够以大得多的规模和高得多的效率来做,”摩根大通欧洲股票量化研究团队的戴维?费拉(David Fellah)表示。据西蒙介绍,到目前为止,欧洲的试验显示,LOXM达成的定价“显著好于”基准水平。
Investment banks have been trying to use AI, automation and robotics to help cut costs and eliminate time-consuming routine work. For example, UBS’s recent deployment of AI to deal with client post-trade allocation requests, which saves as much as 45 minutes of human labour per task. UBS has also brought in AI to help clients trade volatility.
JPMorgan, which is the world’s biggest investment bank by revenue, believes it is the first on Wall Street to use AI with trade execution and said it would take rivals 18 to 24 months and an investment of “multiple millions” to come up with similar technology.
“Best execution is becoming more and more important to clients,” said Mr Ciment of JPMorgan’s decision to invest in the pioneering technology, adding that it could become part of the marketing pitch the bank makes to clients.

The AI was developed using “Deep Reinforcement Learning” methods, which are able to learn from millions of historic scenarios. Mr Fellah said DRL had “many other potential uses in banking, such as in automatic hedging and market making”.

One possible evolution of LOXM is teaching the machine how to get to know individual clients, so that it could consider their behaviour and reaction as it decides how to trade. “Any customisation would only be if the client agrees to that,” Mr Ciment added.
Unlike the robo advisers offered by some private banks, JPMorgan’s AI has no decision-making capabilities around what is bought and sold, its role is solely to decide how things are bought and sold.
The bank has had no risk management issues with the technology. “The machine is restricted in its trading behaviour, as it learns under, and operates within, our general electronic trading risk framework, which is overseen by internal control groups and validated by regulators,” Mr Fellah said.



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