Tipo di tesi
Tesi di laurea magistrale
Titolo
Credit Risk Modelling in Application: Catastrophe Swaps and Deep Learning Approaches
Dipartimento
ECONOMIA E MANAGEMENT
Riassunto (Italiano)
This work begins with examining various structural models with machine learning extensions to analysing credit risk. This is followed by the applications of credit risk modelling in the form of CAT swaps and CD swaps. The study of catastrophe (CAT) swaps is relatively new in literature and has received very little scholarly attention despite its extensive usage in the financial market. Both pre and ex-ante pricing model for CAT swaps are thoroughly exhumed with a final culmination in fuzzy network modelled deep learning pricing strategies for CAT swaps is provided. Credit Default swaps are extensively analysed and thoroughly explained.