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- StarMine Text Mining Credit Risk Model
An overview of StarMine Text Mining Credit Risk Model
StarMine Text Mining Credit Risk Model (TMCR) assesses the risk in publically traded companies by systematically evaluating the language in Reuters News, StreetEvents conference call transcripts, corporate filings (10-K, 10-Q, and 8-K), and select broker research reports to predict which firms are likely to come under financial distress and which are likely to thrive. It is a percentile ranking (1-100) of stocks, with 100 corresponding to the healthiest companies.
At the core of StarMine TMCR is a classic “bag of words” text mining algorithm. A bag of words text mining algorithm breaks a document into its constituent words and phrases and establishes relationships between the frequencies of these words and phrases and a known training variable, such as observed defaults.
Key Facts
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Geographical coverageGlobal
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HistoryFrom 1998
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Data formatCSVDelimitedGZIPJSONPythonSQLTextUser InterfaceXMLZip Archive
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Delivery mechanismAPIDeployed/Onsite ServersDesktopExcelFTPSFTP
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Data frequencyDaily
Features & Benefits
What you get with StarMine Text Mining Credit Risk Model
- TMCR identifies key language from multiple text sources to turn raw textual data into credit scores.
- TMCR model each document source independently and then combine to create an overall probability of default.
- TMCR applies sophisticated text mining algorithms to identify language that is predictive of credit risk.
How it works
Accessing the dataset
This dataset can be used by the following products. Talk to us to learn more about different packages and offerings.
Eikon
- Data Formats:
- CSV
- XML
- JSON
- User Interface
- Python
- Delivery Mechanisms:
- API
- Desktop
- Excel
- Service Frequencies:
- Daily
Refinitiv DataScope Select
- Data Formats:
- CSV
- XML
- Zip Archive
- GZIP
- Delimited
- Delivery Mechanisms:
- FTP
- API
- SFTP
- Service Frequencies:
- Real time
Refinitiv Quantitative Analytics
- Data Formats:
- SQL
- Delivery Mechanisms:
- Deployed/Onsite Servers
- Service Frequencies:
- Real time
- Real time delayed
LSEG Workspace
- Data Formats:
- CSV
- XML
- JSON
- User Interface
- Python
- Delivery Mechanisms:
- API
- Desktop
- Excel
- Service Frequencies:
- Daily
Request details
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