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Company ESG and Financial Sentiment Disclosures

Data Feed by Data Simply

Added to Marketplace: Aug. 29, 2019

  • Leverage quantified sentiment and frequency measures to easily integrate ESG and financial risks gleaned from text in company documents into your fundamental analysis. Rely on primary source information and avoid hearsay or social misinformation.
  • Correlate ESG with traditional financial investment signals. Discover how ESG complements standard fundamental factors for your portfolio or sector, and how companies are improving over time. Continuously track your portfolio, sector or keyword and be alerted when changes occur.
  • Deep dive into data on climate change, fossil fuels, governance, ATF, social workplace and more to screen and select the opportunities, sectors, and portfolios that matter to you. Incorporate financial sentiment to uncover positive and negative risks from company text. Data Simply uses over 200 keywords in their curated ontology to reveal important topics as well as frequency counts that help to identify trends and assign weightings.
Feed Coverage
Sectors CountTypeStart Date
Finance 790Companies2016
Healthcare 500Companies2016
Technology 320Companies2016
Industirals 310Companies2016
Consumer Cyclicals 180Companies2016
Non-Energy Materials 180Companies2016
Consumer Non-Cyclicals 160Companies2016
Feed Details
Data Simply collects, scrubs, verifies and continually updates data in near real-time from published company disclosures at the SEC for the Russell 3000 group of tickers. They distill ESG (environmental, social and governance) and financial signal data from the words in these documents using custom ontologies to create a consolidated and comprehensive dataset.
Firm Information
Data Simply provides investors better, faster ESG and financial signal data using data science. Quickly and easily extract meaningful insights from data by turning unstructured data (text) into investment signals. Leverage emerging technology around machine intelligence to drive growth. Reduce technology risk by letting Data Simply deliver both raw and processed data that can be seamlessly incorporated into existing models.