Tesi etd-04142021-113103 |
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Tipo di tesi
Tesi di laurea magistrale
Autore
VINOD, VIVIN
URN
etd-04142021-113103
Titolo
Credit Risk Modelling in Application: Catastrophe Swaps and Deep Learning Approaches
Dipartimento
ECONOMIA E MANAGEMENT
Corso di studi
ECONOMICS
Relatori
relatore Radi, Davide
Parole chiave
- Black Cox model
- catastrophe swap
- credit default swap
- credit risk
- deep learning
- fuzzy logic
- machine learning
- Merton model
- som
- stochastic models
Data inizio appello
12/07/2021
Consultabilità
Tesi non consultabile
Riassunto
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.
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