IF YOU'RE READING THIS, IT'S TOO LATE: A MACHINE GOT HERE FIR

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To most humans, the following sentence makes little sense: “Symbol ticker = ‘MAN' country = ‘US' cusip = ‘56418H100' isin = ‘US56418H1005' / symbol changesign = ‘+' caltype = ‘percent' 2.5 / change to price value = ‘44.52'.”

But to a new breed of computers specially programmed to trade automatically on the latest news stories, it could be enough to make a huge sum of money.

Hedge funds and bank trading desks are pouring unprecedented sums into such computers to find faster and more inventive ways to outsmart their rivals.

News has always affected market prices. And there are already programs that track news headlines and alert traders if certain market-sensitive terms or words appear frequently. “Hurricane” could signal a shift to sell insurance stocks. “Drought” could affect wheat prices.

But a recent breakthrough is the ability to use computers to analyse years' worth of news stories to see how certain headlines affected market movements and use those patterns to program computers to trade on the latest news developments.

Computers are now being used to generate news stories about company earnings results or economic statistics as they are released. And this almost instantaneous information forms a direct feed into other computers, which trade on the news.

The result is a boom in demand from news and information providers such as Reuters, Bloomberg and Thomson Financial for “machine readable news”, which is written in a computer-friendly language of strings of words and numbers without sentences. Computers can trade on such news within milliseconds of receiving it – much faster than a human trader.

“One of the big consumers of news now is a computer,” says Matthew Burkley, senior vice- president of strategy at Thomson Financial. “This area has turned out to be broader than we thought. Instead of being limited to a marginal number of our clients, the demand for news which is readable by a computer is very widely spread.”

Reuters reports a similar demand. “There is real interest in moving the process of interpreting news from the humans to the machines,” says Kirsti Suutari, global business manager of algorithmic trading at Reuters. “More of our customers are finding ways to use news content to make money. This is where news is exciting.”

The human eye is far from redundant, however. “News events are extremely subjective,” says Will Sterling, head of institutional electronic trading at UBS. “Our general approach has been to blend the automation . . . with a degree of human oversight. It's better to take an extra few seconds to be sure.”




对于大多数人而言，下面这句话可能没什么意义：“Symbol ticker = ‘MAN' country = ‘US' cusip = ‘56418H100' isin = ‘US56418H1005' / symbol changesign = ‘+' caltype = ‘percent' 2.5 / change to price value = ‘44.52'.”

但对于那些安装了专门的程序、自动根据最新新闻进行交易的新一代电脑而言，这一句话可能足以赚上一大笔钱。

对冲基金和银行的交易部门正在倾注空前规模的巨额资金，为自己装备这样的电脑，以便用更加迅速、更加创新的方式战胜自己的竞争对手。

新闻总是能够影响市场价格。目前已经有一些软件程序，能够跟踪新闻标题，当市场敏感的一些词汇频繁出现的时候，程序会提醒交易员注意。“飓风”可能是卖出保险类股的信号，“干旱”则会影响到小麦的价格。

但是，人们最近在这方面取得了一个突破性进展，可以利用电脑分析最近几年的新闻价值，看看一些新闻标题是如何影响市场走势的，并利用这些模式为电脑编程，让电脑根据最新新闻进展进行交易。

现在，人们利用电脑“生产”新闻消息，在公司发布收益报告或政府发布经济统计数据的时候，“生产”出相关的业绩新闻或经济数据新闻。而这些近乎即时的信息则直接提供给另外一些根据新闻进行交易的电脑。

其结果是，在路透(Reuters)、彭博(Bloomberg)和汤姆森金融(Thomson Financial)等新闻和信息供应商，“机器可读新闻”的需求量大幅上升。这些新闻以电脑可读的语言编写，只有一连串的字符和数据，中间没有句子。在收到信息后的数毫秒之内，电脑即可根据新闻进行相关交易，其速度远非人类交易员所能企及。

“现在，电脑已经成为巨大的新闻消费群体之一，”汤姆森金融负责战略工作的高级副总裁马修•伯克利(Matthew Burkley)表示。“这个领域比我们原先想象的广阔得多。我们不再受到客户数量的限制，电脑可读新闻的需求非常广泛。”

路透社也遇到了类似的需求。路透社自动交易业务全球经理基尔斯蒂•苏塔里(Kirsti Suutari)表示：“人们确实感兴趣于将解读新闻的工作由人类交给机器。我们越来越多的客户正在想方设法利用新闻内容赚钱。这就是新闻的令人激动之处。”

然而，人类的眼球远没到达退休的日子。瑞银(UBS)机构电子交易主管威尔•斯特林(Will Sterling)称：“新闻事件是非常主观的。我们的通常做法，是自动化……和一定程度的人类审阅相结合。多用几秒钟确认一下会更好。”