CALCULATING VaR AND ES ON HEAVY TAILED DISTRIBUTION OF A CLAIMS DATA

CALCULATING VaR AND ES ON HEAVY TAILED DISTRIBUTION OF A CLAIMS DATA

Risk measurement is one of many risk management ways. Value-at-Risk (VaR) and Expected Shortfall (ES) are two measuring risks which are commonly used in pre- dicting risks in the future. There are some methods which were used to calculate VaR and ES. These methods are classied to two kinds of det...

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Main Author: Rahmatika Maizar, Yeni
Format: Final Project
Language:Indonesia
Subjects:
Matematika
Online Access:https://digilib.itb.ac.id/gdl/view/34200
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Institution: Institut Teknologi Bandung
Language: Indonesia
id id-itb.:34200
spelling id-itb.:342002019-02-06T10:08:58ZCALCULATING VaR AND ES ON HEAVY TAILED DISTRIBUTION OF A CLAIMS DATA Rahmatika Maizar, Yeni Matematika Indonesia Final Project Generalized Pareto Distribution (GPD), Normal Conditional Distri- bution (NCD), Historical Simulation (HS), Filtered Historical Simulation (FHS). INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/34200 Risk measurement is one of many risk management ways. Value-at-Risk (VaR) and Expected Shortfall (ES) are two measuring risks which are commonly used in pre- dicting risks in the future. There are some methods which were used to calculate VaR and ES. These methods are classied to two kinds of determination which are distribution-based and non distribution-based VaR and ES. The distribution-based VaR and ES methods are Normal Conditional Distribution (NCD) and GPD-based method. And the non distribution-based VaR and ES methods are Historical Simu- lation (HS) and Filtered Historical Simulation (FHS). The purpose of this thesis is to compare the risk measurement results from every methods with considering the validity results from VaR and ES of those methods. text
institution Institut Teknologi Bandung
building Institut Teknologi Bandung Library
continent Asia
country Indonesia
Indonesia
content_provider Institut Teknologi Bandung
collection Digital ITB
language Indonesia
topic Matematika
spellingShingle Matematika
Rahmatika Maizar, Yeni
CALCULATING VaR AND ES ON HEAVY TAILED DISTRIBUTION OF A CLAIMS DATA
description Risk measurement is one of many risk management ways. Value-at-Risk (VaR) and Expected Shortfall (ES) are two measuring risks which are commonly used in pre- dicting risks in the future. There are some methods which were used to calculate VaR and ES. These methods are classied to two kinds of determination which are distribution-based and non distribution-based VaR and ES. The distribution-based VaR and ES methods are Normal Conditional Distribution (NCD) and GPD-based method. And the non distribution-based VaR and ES methods are Historical Simu- lation (HS) and Filtered Historical Simulation (FHS). The purpose of this thesis is to compare the risk measurement results from every methods with considering the validity results from VaR and ES of those methods.
format Final Project
author Rahmatika Maizar, Yeni
author_facet Rahmatika Maizar, Yeni
author_sort Rahmatika Maizar, Yeni
title CALCULATING VaR AND ES ON HEAVY TAILED DISTRIBUTION OF A CLAIMS DATA
title_short CALCULATING VaR AND ES ON HEAVY TAILED DISTRIBUTION OF A CLAIMS DATA
title_full CALCULATING VaR AND ES ON HEAVY TAILED DISTRIBUTION OF A CLAIMS DATA
title_fullStr CALCULATING VaR AND ES ON HEAVY TAILED DISTRIBUTION OF A CLAIMS DATA
title_full_unstemmed CALCULATING VaR AND ES ON HEAVY TAILED DISTRIBUTION OF A CLAIMS DATA
title_sort calculating var and es on heavy tailed distribution of a claims data
url https://digilib.itb.ac.id/gdl/view/34200
_version_ 1822924195899637760

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