Bank default risk analysis using Merton's Distance-to-Default model. Computes PD scores from market and balance sheet data with solver validation and logging. Built in Python.
-
Updated
Oct 24, 2025 - Jupyter Notebook
#
merton-model
Here are 4 public repositories matching this topic...
Distressed-corporate turnaround simulator merging Merton distance-to-default, Altman Z-score and Bayesian lender belief into a 12-quarter decision engine. Python · Streamlit · Plotly.
python fintech bayesian-inference quantitative-finance corporate-finance credit-risk restructuring financial-modeling streamlit altman-z-score merton-model distressed-debt
-
Updated
May 31, 2026 - Python
A structural credit risk engine implementing the Merton (1974) model. Reverse-engineers Black-Scholes to calculate Distance-to-Default (DD) and Implied Default Probabilities (PD) using market equity data and balance sheet structures.
-
Updated
Jan 11, 2026 - Jupyter Notebook
Developed a quantitative credit risk assessment framework using Merton's Default Probability Model, Minsky's Financial Instability Hypothesis, and Markov Chains to classify companies into risk categories and analyze long-term investment risk.
python finance risk-analysis markov-chain data-analysis quantitative-finance investment-analysis credit-risk financial-modeling merton-model
-
Updated
Jun 4, 2026
Improve this page
Add a description, image, and links to the merton-model topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the merton-model topic, visit your repo's landing page and select "manage topics."