Failure Rate

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Module: lib/failure_rate.py

Estimates the cumulative probability that a company fails (defaults) over the 10-year projection period. This probability is used to adjust the final DCF value downward.

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How it’s applied

$\text{Adjusted value} = \text{DCF value} \times (1 - \text{failure probability}) + \text{distress proceeds} \times \text{failure probability}$ Distress proceeds are typically estimated as a percentage of book value (default: 50% of book assets, though this varies by industry).

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Key functions

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failure_rate_by_rating(rating, horizon=10)

Uses historical cumulative default rates from Moody’s and S&P, indexed by credit rating. Parameters:

• rating — synthetic or actual credit rating (e.g., “BBB”, “B+”, “CCC”)
• horizon — years over which to measure default probability (default: 10)

Returns: Cumulative default probability as a decimal.

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failure_rate_by_age(company_age, sector)

Uses Bureau of Labor Statistics business survival data, indexed by company age and sector. Parameters:

• company_age — years since founding or incorporation
• sector — broad industry sector

Returns: Estimated failure probability over 10 years.

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Which method to use

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Data sources

• rating_default_probabilities.json — Moody’s/S&P historical cumulative defaults by rating over 1–10 year horizons
• bls_survival_rates.json — US Bureau of Labor Statistics corporate failure rates by sector and age (5-year, 10-year)