While the amount of data available on the internet has been exploding at an exponential rate in the past few years, many on Wall Street have been hesitant to adopt web-based information in their research or investment processes primarily because of the amount of noise surrounding this data, as well as valid compliance concerns.
The following blog is an excerpt from a recently released white paper by a “big data” based research and data provider called Eagle Alpha called Discovering the Web’s Hidden Alpha addressing how the buy-side is currently using the web to find unique and profitable investment ideas.
White Paper Excerpt
While Wall Street may be lagging behind other industries in making the most of online information, research by Gnip (a Twitter subsidiary) suggests that the adoption of social data analysis in the financial industry is at the beginning of an inflection point and is set to accelerate rapidly in the near future: “In the past 12 months, we’ve seen both an escalation in the number of new firms embracing and innovating, as well as early adoption by some of the larger somewhat risk-averse players in the industry”.
Seth Mc Guire, director of business development at Gnip said that they provide “over a dozen” large quantitative hedge funds (with minimum $1bn AUM each) with the entire Twitter firehose. Rob Bailey, CEO of Datasift (the only other authorized reseller of all of Twitter’s data), said that even before launching in 2011 they received a number of calls from hedge funds and investment banks who wanted access to social media feeds8.
Brunswick, the financial communications firm, conducted a 2014 survey; “Investor use of Digital and Social Media”. From a sample of 472 buy-side investors and sell-side analysts across the US, Europe and Asia they found that 70% of investors believe that digital media will play an increasing role in future investment strategy. Just over a quarter of respondents had based an investment decision on information sourced from a blog, and about 15% from micro-blogging sites like Twitter or its Asian equivalent, Sina Weibo9.
Clearly certain buyside firms are already making use of online sources of information to create competitive advantage but who are they and how are they doing so?
Only a few notable exceptions have broadcasted publicly how they have incorporated social media analytics or curated web content into their investment process, including Bridgewater Associates, Artemis, AKO Capital and Mediolanum Asset Management.
Bridgewater have publicly disclosed that they leverage web information for real-time economic modelling. This macro hedge fund uses all tools at their disposal to “track the economy on a day-to-day basis” and “to be really on the pulse of what’s going on”. This includes social media data, real-time internet price data and search engine data.
Analyzing web data they search for equivalents of traditional macro indicators. Greg Jensen, Bridgewater’s co-chief executive and co-chief investment officer has said that they use sites like Amazon India to track inflation “during a balance of payment crisis on a moment-to-moment basis” and thus can tell if any sharp currency moves have filtered down to end prices. Another application mentioned by Jensen is monitoring auto sales by listening for every time someone says that they buy a new car on Facebook or Twitter and comparing this to official statistics released periodically10.
Hedge funds are not the only economic agents using online data to gain a relevant and timely understanding of economies. Central banks are using Google search data in a similar way. A study published in 2009 by two MIT professors, Erik Brynjolfsson and Lynn Wu, found that it is possible to predict US house prices and sales with search volume data11. Brynjolfsson recognized the significance of this for policy makers: “When central bankers were looking at traditional data, they were essentially looking out the rear-view mirror.” Since their study, many central banks around the world have done their own studies and used web data to assess their national economies 12.
The Bank of England monitors online search data as part of the range of different indicators it considers in forming its view about the outlook for the economy of the United Kingdom, in particular for the housing and labour markets. They find that searches for “job seekers allowance” can help predict unemployment data.
The Bank of Israel was one of the first central banks to use search data for policy making. It analyses keyword counts to gauge consumer demand before official statistics are released. The bank computes a monthly index that reflects the health of the economy which is considered before setting Israel’s benchmark interest rate.
The Federal Reserve have researched how internet search data can forecast financial market data, finding it useful to “now-cast”, or forecast the trajectory of refinancing applications filed by homeowners through searches for “mortgage refinance”.
The Bank of Japan investigated using search data and point-of-sale records to create a new index of economic indicators that would be updated daily or weekly, instead of monthly.
The Banca d’Italia’s working paper deals with the predictive power of Google searches in forecasting unemployment.
The Banco de Espana used search data from the UK to predict tourism towards Spain by analysing travel-related queries.
Economists from the Central Bank of Chile found that an increase in people browsing for cars predicted an increase in auto-sales.
The applications of web data and information are in the early stages of discovery, but are set to be crucial to real-time understanding of economies.
Other hedge funds and asset managers are sourcing information from the web to gain a competitive advantage. Artemis, a UK-based fund manager with £18.6 billion in AUM, differentiates itself by its use of social media data when raising assets under management for the Artemis UK Growth Fund and the Pan Euro Hedge Fund. As we see in the slide below, to their traditional four pillars of portfolio and security selection they have added social media. They seek specific company colour insights from the web.
Tim Steer, Equity Fund manager at Artemis, remarked:
“Social media is an increasingly important part of understanding companies, particularly as traditional sources of information on companies have become quieter: Closer regulatory scrutiny means that companies are more cautious with information disclosure, and investment analysts are providing ever less insight. Adding this new element to my investment process has helped raise AUM”.
AKO Capital LLP ($9.4 billion AUM) broadcast on their website that social media research is incorporated into their investment strategy. In fact they specifically hired a “social media analyst” who performs in-depth equity analysis based on information from the web. Eagle Alpha currently employs 11 research analysts who can complement the work of an internal social media analyst.
Mediolanum Asset Management have similarly integrated social media into the investment process. This graphic shows how they leverage information from Google Trends, Twitter and investment blogs as an important step in the process of identifying opportunities.
A Senior Portfolio Manager of Mediolanum Asset Management explained further:
“Med3® utilizes a combination of fundamental and technical analysis combined with an appreciation of investor sentiment and positioning to determine where an asset is in its investment cycle. For the latter we invest with the momentum until the sentiment becomes extreme and this is where we take a contrarian position. We have a number of sources for determining investor positioning and sentiment including fund flows, institutional and retail surveys. We also leverage the web to determine sentiment in the markets through Twitter. We also utilize Google trends to analyses whether the frequency of news stories on a topic has become so extreme as to indicate a potential inflection point”.
High frequency traders leverage information from the web. As mentioned previously, the Associated Press “hash crash” revealed that, as well as scanning news sources, HFTs are scanning social media, like Twitter. In just two minutes the tweet drove 140 points off the Dow Jones Industrial Average.
Download Eagle Alpha’s complete white paper here http://eaglealpha.com/whitepaper_pdf.
About Eagle Alpha
Eagle Alpha (www.eaglealpha.com) was founded in 2012 by a former Morgan Stanley investment banker, Emmett Kilduff. Since 2012 Kilduff has built a world-class team of employees, investors and advisory panel members that brings together experience from companies including Barclays, Cairn Capital, Cantor, CQS, Credit Suisse, HSBC Asset Management, Jefferies, JP Morgan, Knight Capital, Macquarie, Markit, MergerMarket, Morgan Stanley, Oaktree and Schroders.
A key differentiator of Eagle Alpha is that they curate the entire web. While Twitter provides breaking news and insights from analysis of the 15 billion tweets each month, there are also great opportunities to find actionable insights elsewhere on the web. For example, Eagle Alpha sources intelligence from hundreds of forums, thousands of blogs, millions of websites, LinkedIn, Facebook, Sina Weibo and Tencent Weibo.