Alternative Data, Coronavirus, COVID-19

Using Alternative Data to Track the Coronavirus (COVID-19)

In connection with the coronavirus (COVID-19) pandemic, the global markets are crashing. This type of event is really a sink-or-swim for hedge funds and other asset managers who may completely crumble from market fluctuation or find the undiscovered alpha and profit.

Investors are turning to alternative data to track things like how many people are testing positive, how many are hospitalized, whether the curve is flattening, how quickly Chinese workers are returning to work and factory/supply chains resuming to business-as-usual, to track bookings across hotels/airlines, consumer spending habits, food delivery demand, app data mobile tracking foot fall and migration, etc.

The most popular ways to track the mathematical progress of the pandemic includes:

  • created by high schooler, Avi Schiffmann which tracks all confirmed cases, changes, recovered, fatalities, etc.
  • John Hopkins Novel Coronavirus Visual Dashboard assembled by the John Hopkins University Center for Systems Science and Engineering. This map aggregates a bunch of sources in one place like WHO, European Centre for Disease Precention and Control, government websites. The map displays total cases by country, number of deaths and number of people who have recovered
  • Wolters Kluwer’s COVID-19 Search Intensity Monitoring platform
  • Morgan Stanley’s AlphaWise web platform, built by the bank’s research business, “is using artificial intelligence, traditional consumer surveys, and visualization techniques to monitor the impact of Covid-19.”
  • Covid-19 Tracker published by Benjamin Wissel, MD-PhD Candidate from the Dept. of Biomedical Informatics at the University of Cincinnati College of Medicine
  • The COVID Tracking Project, a volunteer effort led by The Atlantic‘s Alexis Madrigal which collects data from known state public health authority sources and reports the number of positive and negative tests, how many people have been hospitalized, how many have died in each state, etc.
  • government data collected via webscraping
    • federal government data (i.e. WHO, CDC)
    • state departments of health
    • news sources, blogs, any government data trackers
  • Womply’s Data dashboard: How coronavirus / COVID-19 is impacting local business revenue across the U.S.
  • Ohm Analytics Weekly Solar Activity Tracker used to ‘track solar activity on a more real-time basis to monitor the impact of the COVID virus
  • 91-DIVOC, created by University of Illinois associate computer science professor Wade Fagen-Ulmschneider, collects data from Standford’s dashboard and plot the data on charts comparing different countries or states with each timeline starting on the day it reported 100 cases
  • IHME COVID-19 PROJECTIONS models the growth of the virus across the next few weeks and months, showing how many hospital beds and ventilators each state will need, compared to how many they actually have
  • traffic congestion and coal consumption pollution data collected via satellite imagery and GPS navigation
  • hotel bookings data from sources like TravelClick
  • consumer spending data in key U.S. cities like Seattle, New York City, San Francisco with city and state geolocation breakdowns
  • digital trends in real-time using SimilarWeb to evaluate desktop and mobile traffic for things like online travel, hotels, cruise lines, airlines, rental car services, corporate travel, entertainment, grocery delivery, food delivery, webconferencing
  • real-time location intelligence to see if people are abiding by quarantine requirements from sources like Thasos Group
  • food delivery data using UberEats
  • credit card data from sources like Consumer Edge may track things like weekly sales, traffic, ticket trends
  • app data tracking mobile traffic usage and download metrics
  • online e-commerce retailers like, Tmall data to track sell-through product in China
  • web traffic data to identify engagement metrics, audience interests and sources of traffic to web domains
  • Google Trends analyzes Google searches to determine how often a search term or topic was entered relative to the total search volume across user defined regions
  • GDS (Global Distribution Systems) data to track airline bookings data
  • any social media platform data
  • online remote working apps or telecommunication apps like DingTalk or Zoom to track volume of remote connections established
  • Baidu search engine to track migration between cities in China
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