The ISS ESG Carbon & Climate Impact data feed is a comprehensive product incorporating carbon footprint, climate impact, scenario analysis, Carbon Risk Rating, energy & extractives involvement, and Potential Avoided Emissions data. The carbon data covers companies’ scope 1 (direct) & scope 2 (indirect) GHG emissions and intensity, scope 3 (other indirect emissions), and transitional and physical climate risks for 25,000+ global companies. The Energy & Extractives data set contains 200+ factors, including revenue share, capacity, output and volume. Users can evaluate 18,000 companies for detailed fossil fuel and power generation involvement to acquire a deeper climate risk understanding.
Smart Climate® E-Scores measure sensitivity to climate risk. Combining a top-down approach with an Integrated Assessment Model (IAM), Entelligent provides the next generation solution for low carbon impact investing. Entelligent’s proprietary research methodology integrates energy volatility, climate risk data and financial information of public equities to predict returns based on customizable global inputs. The Smart Climate® E-Scores use multiple future climate scenarios to compute the variance among Entelligent’s predicted returns as a climate risk indicator. Entelligent’s approach complements other ESG methodologies that collect and aggregate micro-level data to gauge risks and opportunities.
Access a consolidated source of 500,000+ corporate event audio recordings for 10,000+ companies globally, totaling over 7 TB. Uncover valuable insights, judge sentiment, and unlock alpha based on speakers' tone, manner of speaking, pauses, and more. Pair with our Document Distributor - XML Transcripts product to add a text-based layer to your analysis and to gain access to information about call participants, mapped to FactSet symbology for full connectivity with other content sets. The data is updated on an intraday basis and historical files are available from 2004.
Alexandria’s Global Commodity dataset is the application of their proprietary algorithms on commodity-related news. Each article is summarized into a record of structured data which includes the type of commodity, the topic or news event, and the overall sentiment of the article based on their AI analyst’s assessment on how it will affect that commodity (positive impact, negative impact or neutral/no impact).
Alexandria’s global ESG Sentiment and Topics dataset is the application of proprietary algorithms on ESG-related news. Each company news article is summarized into a record of structured data showing the company, the topic, and the overall sentiment for that article . Each record of data represents an ESG topic being present in a news story.
Alexandria’s global transcripts dataset is the application of proprietary algorithms on company transcripts; as well as on earnings, investor, and all public company calls. Each transcript is parsed into many sections of structured data, each showing detail on what was said in that section including the topic, the sentiment, the speaker and more.