2019年经济学人 金融界的计算机革命(2)（在线收听）

In the past decade computers have graduated to running portfolios. Exchange-traded funds (ETFS) and mutual funds automatically track indices of shares and bonds. Last month these vehicles had $4.3trn invested in American equities, exceeding the sums actively run by humans for the first time. A strategy known as smart-beta isolates a statistical characteristic— volatility, say—and loads up on securities that exhibit it. An elite of quantitative hedge funds, most of them on America’s east coast, uses complex black-box mathematics to invest some $1trn. As machines prove themselves in equities and derivatives, they are growing in debt markets, too.

在过去的十年中，计算机已经逐渐发展为运行投资组合。交易所交易基金和共同基金自动跟踪股票和债券的指数。上月，这些投资工具向美国股市投资了 4.3 万亿美元，首次超过了人类活跃的投资总额。一种被称为 smart-beta 的策略隔离了一种统计特性——比如波动性——并大量买入表现出波动性的证券。数量对冲基金的精英们，大部分在美国东海岸，使用复杂的黑箱数学来投资大约1万亿美元。随着机器在股票和衍生品领域证明自己的价值，它们在债券市场也在增长。

All the while, computers are gaining autonomy. Software programs using AI devise their own strategies without needing human guidance. Some hedgefunders are sceptical about AI but, as processing power grows, so do its abilities. And consider the flow of information, the lifeblood of markets. Human fund managers read reports and meet firms under strict insider-trading and disclosure laws. These are designed to control what is in the public domain and ensure everyone has equal access to it. Now an almost infinite supply of new data and processing power is creating novel ways to assess investments. For example, some funds try to use satellites to track retailers’ car parks, and scrape inflation data from e-commerce sites. Eventually they could have fresher information about firms than even their boards do.

与此同时，计算机正在获取自主权。使用人工智能的软件程序在不需要人工指导的情况下设计自己的策略。一些对冲基金对人工智能持怀疑态度，但随着处理能力的增长，人工智能的能力也在增长。想想信息的流动，市场的命脉。人力基金经理阅读报告，并在严格的内幕交易和信息披露法律下与公司会面。它们的目的是控制公共领域的内容，并确保每个人都有平等的访问权。如今，几乎无限的新数据和处理能力正在创造评估投资的新方法。例如，一些基金试图利用卫星跟踪零售商的停车场，并从电子商务网站搜集通胀数据。例如，一些基金试图利用卫星跟踪零售商的停车场，并从电子商务网站搜集通胀数据。最终，他们可以获得比董事会更新鲜的公司信息。