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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| Format: | Final Project |
| Language: | Indonesia |
| Subjects: | |
| Online Access: | https://digilib.itb.ac.id/gdl/view/34200 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | 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. |
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