The PhD defence will be in Abels utsikt - Niels Henrik Abels hus. The host of the session will moderate the technicalities while the chair of the defence will moderate the disputation.
Ex auditorio questions: the chair of the defence will invite the audience to ask questions ex auditorio at the end of the defence.
Trial lecture
29th of January, time: 10:15 am, room 1259 (Abels utsikt).
Machine learning in insurance
Main research findings
Stochastic volatility models are used to describe the time evolution of financial assets, like stocks, in a random and dynamic way. Their motivation comes from the need to better capture market behaviors and improve the accuracy of option pricing.
In this thesis, we study a stochastic volatility model with self-exciting jumps. In more detail, we consider an extension of the Heston stochastic volatility model by adding Hawkes jumps to the volatility. We investigate the existence of equivalent martingale measures and the pricing of VIX options under this model. Additionally, we derive Thiele’s partial integro-differential equation for unit-linked policies where the benefit is linked to a stock that follows the aforementioned stochastic volatility model.
Furthermore, we derive Thiele’s path dependent partial differential equation for unit-linked policies that can depend pathwise on a general stock. To this end, we employ techniques from functional Itô calculus.
Adjudication committee
- Associate Professor Elisa Nicolato, Aarhus University
- Assistant Professor Heiðar Ingvi Eyjólfsson, Reykjavik University
- Professor Fred Espen Benth, University of Oslo
Supervisors
- Associate Professor David Ruiz Baños, University of Oslo
- Associate Professor Salvador Ortiz-Latorre, University of Oslo
Chair of defence
Head of Department Erlend Fornæss Wold.
Host of the session
Professor Fred Espen Benth, University of Oslo