This repository contains the code and materials supporting a thesis on advanced credit risk modeling. The work focuses on pricing defaultable securities under varying informational environments.
The thesis develops a framework that accounts for:
- Partial vs. complete information, capturing the effect of unobserved economic states on pricing.
- Default contagion, using self-exciting intensities modeled with Hawkes processes to represent the influence of prior defaults.
- Economic regime dynamics, modeled via Markov chains and Hidden Markov Models.
The repository includes implementations for:
- Simulating default times under stochastic intensities.
- Applying filtering techniques to estimate hidden states.
- Pricing defaultable instruments under different information assumptions.
Overall, the project highlights how limited information and contagion effects impact the valuation of credit-sensitive assets.