Credit Default Swaps valuation with structural models

In this project, the concept of credit risk and, more specifically, the Credit Default Swaps (CDS), will be explored, with the objective of understanding how CDS work and how they are evaluated using different methods that use a great variety of mathematical concepts. To do that, two structural credit risk models were implemented: Merton model and First Passage model. These structural models are based on the capital structure of a firm, assets and liabilities, and the evolution of assets’ value over time. In addition, both models define that a default is endogenous, which means that it occurs when the value of the firm’s assets is not sufficient to cover the debt. Then, the same approach was used to compute the CDS spread, to understand the impact of using different models and how they fit with market data. To model these two approaches, Python was used since it is one of the most programming languages covered during my academic path and one of the most suitable to implement mathematical methods.