1. What’s alternative data?
Basically anything beyond traditional sources of information like corporate filings or government-compiled statistics. Also referred to as high-frequency data because of the constant updates, they include such things as the TomTom Traffic measure of urban congestion, OpenTable’s restaurant trackers and the Moovit Public Transit Index, which shows changes in demand. Other data sets track such things as credit-card spending or airline passenger counts. When the pandemic shook labor markets in 2020, the U.S. Federal Reserve itself built a new gauge based on daily employment data from Homebase, a scheduling and time-tracking tool used by 60,000 businesses. It provides a real-time indicator of U.S. employment that has aligned well with the official reports that follow.
2. Is it new?
Not exactly. Well before the internet, things such as freight-car loadings or corrugated-box sales were watched for clues about the economy’s health. Advancing technology has brought more data troves to mine. The hedge fund Point72 Asset Management shorted Weight Watchers International Inc. shares in 2019 after reviews of social media, online search and credit-card transaction data suggested that competitors were gaining momentum. 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. In 2020 analysts turned their number-crunching skills to the pandemic, looking for clues about its progression in Covid-19 reproduction rates and hospital intensive-care unit capacity.
3. 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 or stream television shows -- oceans of information known as big data. Companies in the 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.
4. Who uses the data?
Some of the world’s biggest hedge funds snap up large swaths, many paying big money for it in the hope of gaining an edge. Investment firms that use so-called quantitative strategies can pump the raw data directly into computer programs that trade based on algorithms. Some results can be quite targeted. Hedge-fund clients of Thasos Group, a geolocation analytics firm, got a heads-up about a surge in production of Tesla Inc.’s Model 3 based on a measuring of smartphone signals from inside the carmaker’s factory in Fremont, Calif. The stock jumped when the numbers were officially released.
5. How big is this business?
There are hundreds of providers and the field is growing. One, Eagle Alpha Ltd., projected that investors globally would spend $900 million on alternative data by 2021, nearly double the 2017 level. 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 operates as a search portal, 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.
6. Where does this leave traditional sources?
They haven’t gone away. Investors still pore through company reports for insights other stock-pickers might have missed. As for governments, the U.S. Labor Department has added more big-data readings to the consumer price index and the Fed is using card-swipe data to supplements its economic forecasting. But generally, they are slow to change because their traditional indicators offer the benefit of decades of past data for comparative purposes. One pioneering exception is Estonia, where the central bank, for example, has been publishing statistics on foreign visitors and Estonians abroad based on mobile-phone location tracking since 2012.
7. What are the risks?
In addition to the lack of historical data, another hurdle is the reliability of the readings, which sometimes stem from opaque calculations. There’s also no guarantee that providers will stay in business or won’t change their methodology – something that the U.S. Labor Department encountered when testing new data on apparel prices. And since there are no regulations or restrictions on what tools or platforms the data scientists can use, the potential for hacking could be greater than with traditional sources.
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