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   What is the Text Mining Credit Risk model (TMCR)?
   The StarMine Text Mining Credit Risk model (TMCR) is one component of the StarMine credit risk model suite.

StarMine 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. Although the StarMine TMCR algorithm and key words and phrases are proprietary, the TMCR components provide insight into the drivers on a stock:

  • Textual Components:
    StarMine TMCR evaluates each source of textual data independently, accounting for the unique structure and diction of each document type. The four StarMine TMCR components – Transcripts, News, Filings, and Broker Research – provide distinct and complimentary perspectives on company credit risk and are non-linearly combined to create the overall StarMine TMCR score.
  • Categorical Components:
    StarMine TMCR provides four "category" outputs - income statement related, balance sheet and debt structure related, legal obligations and terms, and external & market events – providing insight into the types of language that drive the StarMine TMCR score.
StarMine TMCR creates daily estimates of default probability, letter ratings, and 1-100 percentile ranks on over 23,000 securities globally. StarMine TMCR provides a quantitative measure of a large body of previously untapped qualitative data which is both useful for risk management and can be used to enhance equity selection performance.

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