Gamma approximation of stochastic integrals
Nicholas, Susanto Tjandra
Date of Issue2019
School of Physical and Mathematical Sciences
This project provides a way to model the distribution of random processes and their cumulative values, which have their applications, but not limited to, the pricing of actuarial and financial derivatives. Specifically, reinsurance Stop-Loss contracts depend on the terminal cumulative loss, where knowledge of the properties of their joint distribution is essential. Approximations based on Gamma distribution are explored. Thereafter, approximated joint distributions of the random processes and their respective cumulative values can be recovered.
Final Year Project (FYP)