Gamma approximation of stochastic integrals

Gamma approximation of stochastic integrals

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 kn...

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Main Author: Nicholas, Susanto Tjandra
Other Authors: Nicolas Privault
Format: Final Year Project
Language:English
Published: 2019
Subjects:
DRNTU::Science::Mathematics
Online Access:http://hdl.handle.net/10356/77151
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-771512023-02-28T23:16:52Z Gamma approximation of stochastic integrals Nicholas, Susanto Tjandra Nicolas Privault School of Physical and Mathematical Sciences DRNTU::Science::Mathematics 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. Bachelor of Science in Mathematical Sciences 2019-05-14T05:25:39Z 2019-05-14T05:25:39Z 2019 Final Year Project (FYP) http://hdl.handle.net/10356/77151 en 36 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Science::Mathematics
spellingShingle DRNTU::Science::Mathematics
Nicholas, Susanto Tjandra
Gamma approximation of stochastic integrals
description 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.
author2 Nicolas Privault
author_facet Nicolas Privault
Nicholas, Susanto Tjandra
format Final Year Project
author Nicholas, Susanto Tjandra
author_sort Nicholas, Susanto Tjandra
title Gamma approximation of stochastic integrals
title_short Gamma approximation of stochastic integrals
title_full Gamma approximation of stochastic integrals
title_fullStr Gamma approximation of stochastic integrals
title_full_unstemmed Gamma approximation of stochastic integrals
title_sort gamma approximation of stochastic integrals
publishDate 2019
url http://hdl.handle.net/10356/77151
_version_ 1759856819908378624

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