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 Knight Capital, the market maker at the centre of the latest malfunction in electronic share trading, bills itself as: "the science of trading, the standard of trust".

近日遭遇电子股票交易故障的美国做市商Knight Capital Group以"交易科学,信任标杆"作为宣传语。
Yet that public trust in US equity markets is being severely tested now. Following on from the technical glitches that marred the flotations of Facebook and BATS Global Markets this year, comes Wednesday's erroneous trading in 148 shares listed on the New York Stock Exchange.
然而,美国股票市场的公信力正遭遇严峻考验。今年以来技术故障已导致Facebook和BATS Global Markets首发上市出现问题,上周三纽约证交所(NYSE)又出现了148只股票交易异常的情况。
Once more investors and traders in the US equity market are left bewildered by another episode of an algorithmic or "algo" trading system running wild.
这起算法交易系统故障再次令美国股市的投资者和交易员感到无所适从。
More than two years after the flash crash of May 2010 – when Wall Street tumbled hundreds of points within minutes – it demonstrated how much of the US equity market in effect operates on autopilot. It also serves as a reminder that trading firms, exchanges and regulators still face huge challenges in safeguarding how stocks trade in a superfast dealing environment.
在2010年5月"闪电暴跌"(flash crash)事件发生两年多以后——当时道琼斯指数在半小时内暴跌650点——这件事折射出了美国股市自动化交易的普遍程度,对于交易商、证交所以及监管当局而言也是一记警钟,提醒他们:在高速交易环境下保障股票交易正常进行方面,他们仍面临艰巨挑战。
While the wider market was unaffected by Knight's "technology issue", suggesting that regulatory and exchange reforms since the flash crash helped to prevent a panic, the episode has revived a long-running debate over the benefits and dangers of relying on complex computer systems.
尽管整体市场未受Knight"技术问题"影响(似乎表明监管当局和交易所自"闪电暴跌"以来推行的改革措施对防止恐慌起到了作用),但这件事重新引燃一场持续多年的辩论,其主题是依赖复杂电脑系统的效益与风险。
Much trading in equities now comprises sophisticated algos that are created to trade in specific ways, reacting to changes in prices, sectors, volatility, economic data and other parameters across the fragmented trading landscape.
如今,美国股市的很大一部分交易由复杂的算法执行,这些算法的设计宗旨是以某种特定的方式进行交易,对价格、行业形势、市场波动、经济数据以及跨越交易版图上不同板块的其他参数的变化作出反应。
By replicating the way human traders ascertain where other investors want to buy and sell stocks, the algos spit out a torrent of orders, many of which are quickly cancelled before a trade is executed, all within fractions of a second.
通过复制真人交易员判断其他投资者买卖意向的方式,算法程序发出一连串交易指令(其中很大一部分在执行前被取消),整个过程耗时不足几分之一秒。
Since the advent of such trading in the past decade, the average trade size has dropped from 1,000 to 200 shares. Some market participants and observers worry about the risks of an "algo" running out of control.
自从过去10年里算法交易诞生以来,单笔交易的平均规模已从1000股下降至200股。一些市场参与者和观察人士担心算法交易存在失控风险。
"We are still vulnerable to all kinds of glitches, no matter what changes and precautions we make, there will always be an unanticipated scenario," says James Angel, associate professor at Georgetown University.
乔治敦(Georgetown University)副教授詹姆斯•安吉尔(James Angel)指出:"我们在各种技术故障面前仍然十分脆弱。无论我们采取什么改革或防范措施,总会有意想不到的情形出现。"
In the case of Knight, which suffered a loss of $440m, Tom Joyce, chief executive, told Bloomberg yesterday the implementation of new software contained a bug that sent erroneous orders into the market. "So we ended up with a large error position which we had to sort through the balance of the day," he said.
Knight公司首席执行官托马斯•乔伊斯(Thomas Joyce)上周四对彭博(Bloomberg)表示,发生技术问题是由于公司新安装的软件存在缺陷,向市场发出了错误的交易指令。他说:"结果我们持有规模庞大的错误头寸,被迫在当日余下的时间进行整理。"
Traders said they believed a large order for a number of stocks was executed in five minutes rather than a longer period of either one or up to five days. The scale of orders pushed prices sharply higher or lower and overwhelmed the liquidity of the market.
交易员们认为,涉及多只股票的大额交易指令在5分钟内就执行完毕,而没有在一整个交易日甚至五个交易日的更长时段内分批进行。这些指令的庞大规模导致股价剧烈波动,超出市场流动性的承受能力。
It also sparked wild trading in exchange traded funds; the Vanguard Utility ETF experienced volumes of 4m, well beyond its usual 128,000 trades a day.
该指令还导致交易所交易基金(ETF)的交易量暴增,先锋(Vanguard)公用事业类ETF的交易量达到400万笔,远远超过每日12.8万笔的正常水平。
Since the flash crash, the market has put in place circuit breakers, designed to limit wild swings in the price of stocks beyond a rise or fall of 10 per cent during a five minute period.
闪电暴跌事件后,市场引入了"断路开关"机制,以扼制股价剧烈波动,使股价在5分钟内的涨跌幅度不超过10%。
In total at least 40 of the 148 stocks affected by the Knight trading algo experienced a change of more than 10 per cent, as circuit breakers do not start operating until 15 minutes into the trading day and reflect volatility, not order flow.
受Knight算法交易影响的148只股票中,至少有40只股票的股价波动幅度超过了10%,因断路开关机制在开盘15分钟后才投入运行,而且该机制反映的是股价波动性,而非指令流量。
Among the stocks that triggered circuit breakers on Wednesday were Molycorp, CoreLogic, Kronos Worldwide, China Cord Blood Corporation and Trinity Industries. The changes in their share prices went well beyond 10 per cent, with China Cord jumping as much as 151 per cent before falling back.
上周三触发了断路开关机制的股票包括莫利矿业(Molycorp)、数据供应商CoreLogic、化学品生产商Kronos Worldwide、中国脐带血库公司(China Cord Blood Corp)以及铁路运输商Trinity Industries。这些公司的股价波幅远超10%,中国脐带血库公司股价在回落前曾暴涨151%。
"The industry has been well aware of defects with the circuit breakers," says Prof Angel.
安吉尔教授指出:"断路开关机制的缺陷业内早已知晓。"
Meanwhile, only trades in six of the 148 stocks were subsequently broken by the NYSE. That leaves Knight potentially facing substantial costs and raises broader questions. "This is not only a problem for Knight, but creates a whole new thing for regulators to dwell on and for investors to lose trust in the market," says one Wall Street analyst.
在148只受影响股票中,纽约证交所只中断了其中6只股票的交易。这使Knight可能面临重大损失,并带出更广泛的问题。一位华尔街分析师表示:"这不是Knight的个体问题,而是监管当局应该仔细研究的新领域,也让投资者有新的理由对市场失去信任。"
For some, the notion of breaking trades underlines the problem of using and relying heavily on high-speed computer technology. Once a trade is executed it soon triggers a chain of positions that becomes very expensive to break.
在某些人看来,停止交易的概念,凸显出使用并过分依赖高速电脑交易技术的问题。一旦一条交易指令被执行,将迅速触发一连串新头寸,这导致停止交易的成本非常高。
"There is no kill switch; the minute you hit the send button on an algo it's running and you can't stop it," says Ken Polcari, managing director at ICAP Equities. "Maybe we do need to reflect on where the line is between humans and computers."
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