Leaders
来源于《社论》版块
Masters of the universe
宇宙主宰者
Forget Gordon Gekko. Computers increasingly call the shots in financial markets
忘记葛登·盖柯。越来越多在金融市场上发号施令的是计算机
The job of capital markets is to process information so that savings flow to the best projects and firms. That makes high finance sound simple; in reality it is dynamic and intoxicating. It reflects a changing world. Today’s markets, for instance, are grappling with a trade war and low interest rates. But it also reflects changes within finance, which constantly reinvents itself in a perpetual struggle to gain a competitive edge. As our Briefing reports, the latest revolution is in full swing. Machines are taking control of investing—not just the humdrum buying and selling of securities, but also the commanding heights of monitoring the economy and allocating capital.
资本市场的工作是处理信息，使储蓄流向最好的项目和公司。这使得高级金融听起来很简单；实际上，它是动态的、令人陶醉的。它反映了一个不断变化的世界。例如，如今的市场正努力应对贸易战和低利率。但它也反映了金融内部的变化，在不断的竞争中不断重塑自己，以获得竞争优势。正如简报所述，最新的革命正在全面展开。机器正在控制投资——不仅仅是单调的证券买卖，也是监管经济和资本配置的制高点。
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Funds run by computers that follow rules set by humans account for 35% of America’s stockmarket, 60% of institutional equity assets and 60% of trading activity. New artificial-intelligence programs are also writing their own investing rules, in ways their human masters only partly understand. Industries from pizza-delivery to Hollywood are being changed by technology, but finance is unique because it can exert voting power over firms, redistribute wealth and cause mayhem in the economy.
由遵循人类规则的计算机运行的基金占美国股市的35%，占机构股票资产的60%，占交易活动的60%。新的人工智能程序也在以人类主人只能部分理解的方式，编写自己的投资规则。从披萨外卖到好莱坞电影业的各个行业都在被技术所改变，但在金融业是独一无二的，因为它可以对企业施加投票权、重新分配财富，并在经济中造成混乱。
Because it deals in huge sums, finance has always had the cash to adopt breakthroughs early. The first transatlantic cable, completed in 1866, carried cotton prices between Liverpool and New York. Wall Street analysts were early devotees of spreadsheet software, such as Excel, in the 1980s. Since then, computers have conquered swathes of the financial industry. First to go was the chore of “executing” buy and sell orders. Visit a trading floor today and you will hear the hum of servers, not the roar of traders. High-frequency trading exploits tiny differences in the prices of similar securities, using a barrage of transactions.
由于涉及巨额交易，金融业总是有足够的资金尽早实现突破。第一条横跨大西洋的光缆于1866年建成，用来在利物浦和纽约之间传输棉花价格。上世纪80年代，华尔街分析师是Excel等电子表格软件的早期拥护者。从那以后，计算机征服了金融业的大片领域。首先要做的是“执行”买卖订单。今天去交易大厅，你会听到服务器的嗡嗡声，而不是交易员的吼叫声。高频交易利用类似证券价格的微小差异，进行大量交易。
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。
Until now the rise of computers has democratised finance by cutting costs. A typical ETF charges 0.1% a year, compared with perhaps 1% for an active fund. You can buy ETFs on your phone. An ongoing price war means the cost of trading has collapsed, and markets are usually more liquid than ever before. Especially when the returns on most investments are as low as today’s, it all adds up. Yet the emerging era of machine-dominated finance raises worries, any of which could imperil these benefits.
到目前为止，计算机的兴起通过降低成本使金融民主化。典型的ETF每年收取0.1%的费用，相比之下，主动型基金可能收取1%的费用。你可以在手机上购买ETF。一场持续的价格战意味着交易成本大幅下降，市场的流动性通常比以往任何时候都更强。特别是当大多数投资的回报和今天一样低的时候，这一切都是有意义的。然而，机器主导金融的新时代引发了这些好处可能被危及的担忧。
One is financial stability. Seasoned investors complain that computers can distort asset prices, as lots of algorithms chase securities with a given characteristic and then suddenly ditch them. Regulators worry that liquidity evaporates as markets fall. These claims can be overdone—humans are perfectly capable of causing carnage on their own, and computers can help manage risk. Nonetheless, a series of “flash-crashes” and spooky incidents have occurred, including a disruption in ETF prices in 2010, a crash in sterling in October 2016 and a slump in debt prices in December last year. These dislocations might become more severe and frequent as computers become more powerful.
一是金融稳定。经验丰富的投资者抱怨说，电脑可以扭曲资产价格，因为许多算法追逐具有特定特征的证券，然后突然抛弃它们。监管机构担心，随着市场下跌，流动性会蒸发。这些说法可能有些过火——人类完全有能力自己制造屠杀，而计算机可以帮助管理风险。尽管如此，还是发生了一系列“闪崩”和令人毛骨悚然的事件，包括2010年 ETF 价格的崩溃、2016年10月英镑的暴跌和去年12月债务价格的暴跌。随着计算机功能的增强，这种错位可能会变得更加严重和频繁。
Another worry is how computerised finance could concentrate wealth. Because performance rests more on processing power and data, those with clout could make a disproportionate amount of money. Quant investors argue that any edge they have is soon competed away. However, some funds are paying to secure exclusive rights to data. Imagine, for example, if Amazon (whose boss, Jeff Bezos, used to work for a quant fund) started trading using its proprietary information on ecommerce, or JPMorgan Chase used its internal data on credit-card flows to trade the Treasury bond market. These kinds of hypothetical conflicts could soon become real.
另一个担忧是，电脑化的金融如何能够集中财富。因为性能更多地依赖于处理能力和数据，那些有影响力的人可以赚到不成比例的钱。定量投资者辩称，他们拥有的任何优势很快就会被竞争殆尽。然而，一些基金正在为获得数据的专有权而付费。想象一下，例如，如果亚马逊(其老板杰夫•贝佐斯曾在一家定量基金工作)开始利用其在电子商务方面的专有信息进行交易，或者摩根大通利用其在信用卡流动方面的内部数据进行美国国债市场的交易。这种假想的冲突可能很快就会变成现实。
来源：经济学人
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