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StarMine Sovereign Risk Model

An overview of StarMine Sovereign Risk Model 

The StarMine Sovereign Risk (SR) model evaluates a wide array of macroeconomic, market-based, and political data to estimate the probability that a sovereign government will default on its debt. The model produces estimates of the annualized probability of default for 150 countries at six-time horizons: 1, 2, 3, 5, 7, and 10 years. The default probabilities are also mapped to traditional letter grades and ranked to produce 1-100 percentile scores.
StarMine SR utilizes a logistic regression framework to estimate default likelihoods. The model was trained to over 30 years of sovereign credit event data. The data included actual defaults (missed payment), distressed restructurings (debt reissued in less favorable terms), and debt re-schedulings under the auspices of the Paris Club. The primary input drivers of the model are macroeconomic data. Additional market-based and political risk data inputs are also used to generate a comprehensive picture of sovereign risk.

Key Facts 

  • Geographical coverage
    Global
  • History
    From 1994
  • Data format
    CSV
    JSON
    Python
    User Interface
    XML
  • Delivery mechanism
    API
    Desktop
    Excel
  • Data frequency
    Daily

Features & Benefits

What you get with StarMine Sovereign Risk Model 

  • StarMine SR provides robust estimates of the probability of default of sovereign nations over multiple time horizons using a broad spectrum of data inputs.
  • Backtests of trading strategies in the CDS and fixed-income markets using StarMine SR show profitable strategies for forecasting one-month forward CDS price changes and for government bond yield spread changes.

How it works

 Accessing the dataset

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