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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.
摩根大通(JPMorgan)不久将利用一款首创的机器人在其全球的股票算法业务部门执行交易，此前该行在欧洲对其新型人工智能(AI)程序的试验表明，它的效率比传统的买卖方法高得多。
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.
LOXM的职责是以最佳价格和最高速度执行客户交易指令——运用它从数十亿笔过往交易（既有真实交易，也有模拟交易）中汲取的经验教训来解决各种问题，比如怎样抛出大笔股份而不影响市场价格。
“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.
各投资银行一直在尝试使用AI、自动化和机器人技术来帮助降低成本，消除耗时的日常工作。例如，瑞银(UBS)最近部署了AI来处理客户的交易后配置请求，为每个任务节省了多达45分钟的人力劳动。瑞银还已采用AI来帮助客户利用市场波动进行交易。
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.
按营收计算为世界最大投行的摩根大通相信，它是首家使用AI执行交易的华尔街投行，并称，竞争对手将需要18至24个月和“数百万”美元的投资才能开发出类似技术。
“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.
“最佳执行对客户来说越来越重要，”西蒙在谈到摩根大通投资于这种开创性技术的决定时表示。他补充说，该项技术可能成为该行对客户营销宣传内容的一部分。
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”.
这款AI是利用“深度强化学习”(DRL)方法开发的，这类方法能够从数百万种历史情形中学习。费拉表示，深度强化学习在银行业有“其他很多潜在用途，比如自动对冲和做市”。
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.
一个可能的发展是，向LOXM机器传授如何了解个人客户，以便它在决定如何交易的时候考虑他们的行为和反应。“任何定制将在客户同意的情况下进行，”西蒙补充说。
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.
与一些私人银行提供的机器人顾问不同，摩根大通的AI对于买卖什么是没有决策能力的，其作用仅仅是决定买卖的方式。
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.
该行认为这种技术没有风险管理问题。“机器的交易行为受到限制，因为它在我行的通用电子交易风险框架下学习和运行，这个框架受到内控小组监督，并由监管机构验证，”费拉表示。
