1. What are examples of alternative data?
A former chief economic adviser to Indian Prime Minister Narendra Modi crunched data such as vehicle sales and electricity consumption to show that the nation had overstated annual growth by about 2 percentage points on average from 2012 to 2017. Researcher and entrepreneur Apurv Jain found clues to where U.S. employment was headed by analyzing 1.2 billion tweets from 230,000 Twitter users who posted about losing or finding a job. The hedge fund Point72 Asset Management shorted Weight Watchers shares after reviews of social media, online search, and credit-card transaction data suggested that competitors were gaining momentum.
2. How is so much information available?
We all produce digital exhaust when we post on social media and “like” posts by others, search the internet, wear fitness trackers and stream television shows. Companies in the growing field of predictive analytics dig for useful signals amid the noise. Mobile-phone locations and card-swipe data offer a rich vein of information about, say, the popularity of a retailer or even refinery outages. A spike in online searches for coupons might signal growing economic uncertainty. Data gatherers can monitor employment-related websites like Glassdoor or dig through government-required filings on company benefit plans to get hints about new products or services in the works, or for early signals of corporate distress. Satellite imagery of nighttime lights can offer insights on political and economic conditions even in conflict zones.
3. Who uses the data?
Some of the world’s biggest hedge funds are leaders in snapping up large swaths of alternative data, many paying big money for it. Investment firms that use so-called quantitative strategies can pump the raw data directly into algorithmic trading models. Trying to get an edge is as old as investing itself, but the profusion of alternative data sources -- for those investors who can afford them -- can offer faster and more detailed analysis than the government economic reports released on a monthly or quarterly basis.
4. How big is this business?
The number of providers has tripled in three years to 1,126, according to Eagle Alpha Ltd., an alternative data provider that projects global spending will reach $900 million by 2021, nearly double the 2017 level. (AlternativeData.org, which collects information on the industry, puts the number of providers at 445.) Players include NPD Group Inc., which says it crunches millions of receipts from brick-and-mortar stores and e-commerce sites to analyze consumer trends; Quandl Inc., which used aircraft-tracking data to sniff out a deal in the works between Occidental Petroleum Corp. and Buffett’s Berkshire Hathaway Inc.; Thasos Group, which measured overnight smartphone activity inside Tesla Inc.’s headquarters to anticipate a surge in production of its Model 3; satellite tracking firms Orbital Insight Inc. and Ursa Space Systems Inc.; and Predata Inc., which vacuums up data from online conversations and comments to feed country-specific “geopolitical risk” indices. (Bloomberg LP, the parent of Bloomberg News, provides clients with access to alternative data.)
5. Where does this leave traditional government reports?
The Federal Reserve is using card-swipe data to supplement its economic forecasting and hosted a conference to investigate how other data can help it track the economy. The U.S. Labor Department has added more big-data readings to the consumer price index. But generally, governments are slow to adopt because so much depends on their data, and the perspective of having decades of history for indicators can outweigh immediate results. One pioneering exception is Estonia, where examples include the central bank publishing international travel statistics based on mobile-phone location tracking since 2012.
6. What are the risks?
Official data are still king, but JPMorgan Chase & Co. and Goldman Sachs Group Inc. both see pitfalls in addition to promise in alternative data. The lack of a long history is a big hurdle. Another is the reliability of the readings, which sometimes stem from opaque calculations. For government statistical authorities working to include corporate data in official indicators, there’s no guarantee that providers will stay in business or won’t change their methodology -- something that the Labor Department encountered when testing new data on apparel prices. And that’s not all: “Because these data scientists are being given free rein to use any tool, system, provider, database, platform, it does introduce the potential for hacking and unauthorized access -- especially with unconventional locations,” said Samer Ojjeh, Americas asset management advisory leader at Ernst & Young LLP.
To contact the reporter on this story: Jeff Kearns in Washington at firstname.lastname@example.org
To contact the editors responsible for this story: Scott Lanman at email@example.com, Laurence Arnold
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