用社交媒体选股

I n 1997, when Richard Peterson was a medical school student, he would play poker with a buddy who never seemed short of money. His friend was raking it in trading penny stocks. One day he showed up with a brand new Jeep in the driveway, evidence he was doing something right.

1997年，正在医学院就读的理查德·彼得森(Richard Peterson)喜欢和一位似乎从不缺钱的朋友打扑克。这位朋友通过交易便士股票（指每股低于一元的低额股票——译者注）赚得盆满钵满。有一天，他开着一辆崭新的吉普出现在车库门前，这证明他做得不错。

“He was just following rumours on the web, Mr Peterson says, recounting his introduction into the world finance.

彼得森在讲述他初次接触金融世界的经历时说：“他仅仅是在跟踪网络上的谣言而已。

As the internet developed from the basic chat rooms of the late 1990s, Mr Peterson knew he wanted to do something with this idea of using social media to gain a market edge. After an 11-year career as a psychiatrist, he raised $1m from friends and colleagues to set up a hedge fund, and a further $750,000 to set up MarketPsych, the tech company behind it.

随着互联网从20世纪90年代末的基本聊天室发展起来，彼得森明白，他想要利用社交媒体做些什么，以获得市场优势。在做了11年精神病专家以后，他从朋友和同事那里筹集了100万美元，建立了一支对冲基金，随后又筹集了75万美元建立了支持这家对冲基金的科技企业MarketPsych。

The Santa Monica-based fund, MarketPsy Capital, used servers that trawl chat rooms, blogs, websites and tweets to determine sentiment on thousands of companies, many of which Mr Peterson would then buy or sell in the stock market.

总部位于加州圣莫尼卡的MarketPsy Capital基金利用服务器追踪聊天室、博客、网站和微博，以确定市场对成千上万家企业的情绪，然后彼得森会在股市上买卖其中多家企业的股票。

It might sound like science-fiction, and alarmingly intrusive, but using social media to predict the future has become a popular pursuit in the financial sector.

这听起来可能像科幻小说一样，而且就侵入而言令人震惊，但利用社交媒体预测未来，已成为金融界的流行追求。

It has never been so easy to trace what influences our decisions. People Google their questions, tweet their thoughts and post their findings on blogs and Facebook. Now some entrepreneurs are building algorithms to find patterns and make predictions in order to beat the stock market.

追踪影响人们决策的因素从未像现在这样容易。人们在谷歌(Google)上搜索问题答案，在微博上发表想法，在博客和Facebook上张贴自己的发现。现在，有些企业家正在设计算法，以期找出模式，做出预测，达到跑赢股市的目的。

Mr Peterson’s fund certainly seemed to at first. MarketPsy Capital made 40 per cent returns for the first two years.

彼得森的基金最初似乎做到了这一点。成立前两年，MarketPsy Capital回报率达40%。

“Everything seemed straightforward, we were on the success path, he says.

他说：“当时一切似乎都很直截了当，我们走在成功之路上。

Then, in 2010, the fund lost 8 per cent. “When the market mood shifted from fear to recovery, our models didn’t catch it because they were based on fear, he says. “It was a tough time to read capital.

但到了2010年，这支基金亏损8%。他说：“当市场情绪从恐惧转向复苏，我们的模型没有把握这种趋势，因为模型还是以恐惧为基矗那是研究资本趋势的艰难时期。

Johan Bollen, associate professor of informatics and computing at Indiana University in the US, is more sceptical and offers another explanation for the poor results. “How do you filter out the garbage? he asks. “Even with 80 per cent accuracy, you could be so wrong 20 per cent of the time that it bankrupts you.

美国印第安那大学(Indiana University)信息科学及计算技术副教授约翰·博伦(Johan Bollen)对此抱有更强的怀疑态度，他对糟糕投资表现提供了另一种解释。他问道：“你如何过滤垃圾信息？即使准确度达到80%，你还是有20%的几率出大错，这足以让你破产。

Prof Bollen believes there is indeed value in looking at the broader emotional states of society on the internet. But tracking what people are writing about one specific company on social media forums is less useful. “Just because it’s relevant doesn’t mean it is predictive, he ex-plains.

博伦教授认为，从互联网上研究整体的社会情绪状态确实有价值。但追踪人们在社交媒体论坛上就某家公司发表的看法不那么有用。他解释道：“仅仅因为信息相关，并不代表信息具有预测性。

His study “Twitter Mood Predicts the Market set out to categorise the mood of tweets through text analysis. The results, published in the Journal of Computational Science in 2011, revealed that a change in calmness online is manifested in market movements, with a strong predictive correlation with the rise and fall of the Dow Jones Industrial Average index.

他的研究以“用Twitter情绪预测市场为标题，尝试通过文本分析对微博帖子的情绪进行分类。研究结果在2011年发表于《计算科学杂志》(Journal of Computational Science)。其结果揭示出，网络平静状态的变化反映在市场变动中，与道琼斯工业平均指数(Dow Jones Industrial Average)涨跌具有强烈的预测相关性。

Despite his doubts about social media stock picking, Prof Bollen believes broader internet mood analysis could lead to something big, and likens the pursuit to the Californian gold rush. He has set up a venture called Guidewave in an at-tempt to strike gold. “We’re looking for hidden societal undercurrents, he says.

尽管他质疑通过社交媒体选择股票的方法，但博伦教授认为，整体的互联网情绪分析能产生重大收获，就像当年加州淘金热一样。他建立了一家Guidewave的企业，试图发现“金矿。他说：“我们在寻找隐藏的社会潜流。

As Prof Bollen was doing his res-earch, Bernardo Huberman, director of the social computing research unit at HP Labs, Hewlett-Packard’s res-earch unit, began investigating where people direct their attention online.

在博伦教授展开研究之际，惠普研究部门惠普实验室(HP Labs)的社交计算研究部门主管伯纳多·休伯曼(Bernardo Huberman)开始调查人们把自己的注意力放到网上什么地方。

Prof Huberman, author of The Laws of the Web, is interested in the relationship between what people tweet and what happens in the real world. He calls this “the economics of attention.

休伯曼教授著有《网页法则》(The Laws of the Web)一书，他感兴趣的是人们发布的微博与现实世界发生的事情之间的关系。他称之为“注意力经济学。

“I wanted to look for something that was extremely precise to see if we were predicting accurately – so we chose movies and box office revenues, he says.

他说：“我想要寻找一些极其精确的东西，看看我们的预测是否准确，于是我们选择了电影和票房收入为研究对象。

Prof Huberman found that analysing what people were tweeting ahead of a movie release predicted box office revenues more accurately than the Hollywood Stock Exchange, a futures exchange linked to the performance of blockbuster movies owned by Cantor Fitzgerald, the broker.

休伯曼发现，在一部电影上映之前，通过分析人们发布的微博来预测票房收入，比好莱坞证券交易所(Hollywood Stock Exchange)更加准确，后者是一家与大片表现相关的期货交易所，由经纪商坎托·菲茨杰拉德(Cantor Fitzgerald)拥有。

Unsurprisingly, the resultant paper, “Predicting the Future with Social Media, received attention from advertisers keen to manipulate Twitter to increase demand for products.

并不令人意外的是，发布研究结果的论文《用社交媒体预测未来》(Predicting the Future with Social Media)受到了急于操纵Twitter来扩大产品需求的广告商的关注。

But it also inspired a group of Dutch entrepreneurs to set up a similar predictor for stock price moves. The idea turned into a prototype with the help of angel investors at Clipit, a Dutch social media monitoring company.

但这也启发一批荷兰企业家设立了一个用来预测股价走势的类似预报器。在荷兰社交媒体监测企业Clipit的天使投资人的帮助下，这个创意转变成了一个原型。

“We primarily use Twitter because it is in real time, is easier to get data and it also has the most explanatory value, says Vincent van Leeuwen, one of the four founders.

四位创始人之一文森特·范莱文(Vincent van Leeuwen)表示：“我们主要使用Twitter，因为它是实时的，获得数据更加容易，也最具有阐释价值。

Their start-up, called SNTMNT, offers Twitter analysis for retail investors and is in the process of signing a deal with a Dutch bank. Mr van Leeuwen says other interested parties include online brokerage firms. “They are always looking for new tricks to get their clients to make trades, Mr van Leeuwen adds.

他们的初创企业叫SNTMNT，为散户投资者提供Twitter分析，目前正在与一家荷兰银行签署一项协议。范莱文表示，其他感兴趣的企业包括在线经纪公司。范莱文补充道：“他们总在寻找新花招来鼓励客户买卖股票。

Meanwhile in Paris, three traders with backgrounds in behavioural finance, which uses psychology to refine the decisions investors make, run IIBremans, a company offering sentiment analysis of the French CAC40 index.

同时，在巴黎，三位拥有行为金融学（利用心理学来改善投资者的决策）背景的交易员经营着IIBremans，这是一家对法国CAC 40指数提供情绪分析的企业。

For several years, Phillippe de Brem and Guillaume Dumans would spend two hours every morning before their day jobs as traders began, scanning the web for bullish or bearish signs on French stocks. They would send out a newsletter making a call on which way the market would move that day.

多年来，菲利普·德布雷姆(Phillippe de Brem)和纪尧姆·迪曼(Guillaume Dumans)每天早晨会在他们作为交易员的工作开始之前，花两个小时在网页上浏览法国股票的看涨或看跌迹象。他们会发布一份时事通讯，判断当天股市的可能走向。

Today the company has an algorithm-based bull-bear index called L’indicateur IIBremans.

现在，该公司提供一项基于算法的牛-熊市指数，叫做L’indicateur IIBremans。

Mr Dumans says fund managers who have suffered from poor returns through the financial crisis “want something new and different.

迪曼表示，在金融危机期间回报惨淡的基金经理，“想要一些新鲜、不同寻常的东西。

But if it all sounds like alchemy – turning junk on the internet into gold – that is because it is, say sceptics. Prof Bollen and Prof Huberman question whether there is much value in just watching a subset of the Twitterverse such as the financial sector.

不过怀疑者表示，如果这一切听起来像炼金术一样——把互联网上的垃圾变为金子，那是因为事实确实如此。博伦教授和休伯曼教授质疑，仅仅监测Twitter上的一个子集（如金融板块），到底有多大价值。

“It’s one of those things that seems obvious from a superficial point of view, says Prof Bollen. “But you have to ask: why would someone be tweeting about a stock and why would that have more value than other indicators?

博伦教授表示：“从表面的角度来看，这是一个显而易见的事情。但你必须问问：为什么有人要针对一支股票发微博，为什么微博比其他指标更有价值？

If you know something about the market, you are not going to share it with the world, he adds.

他补充道，如果你了解一点市场内幕，肯定不会和别人分享。

Prof Huberman echoes this: social media is useful as a gauge of public mood only in the broader sense. “Unless George Soros or Warren Buffett are tweeting, those who make up the Twitter population are not the ones moving the market.

休伯曼教授呼应了这一观点：用社交媒体衡量公共情绪，只在整体意义上有用。“除非乔治·索罗斯(George Soros)和沃伦·巴菲特(Warren Buffett)在发微博，否则Twitter用户并不是那些能够影响市场走向的人。