VALUE AT RISK NONPARAMETRIK UNTUK CLAIM SEVERITY PADA ASURANSI KERUGIAN MENGGUNAKAN ESTIMASI KERNEL BERTRANSFORMASI GANDA
Insurance involves two parties namely the insured and the insured (insurance company). The insurer must pay some amounts to cover insured when they have a loss, while the insured is obliged pay a premium as a compensation. This makes insurance companies should determine the price of premium. One mea...
محفوظ في:
| المؤلفون الرئيسيون: | , |
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| التنسيق: | Theses and Dissertations NonPeerReviewed |
| منشور في: |
[Yogyakarta] : Universitas Gadjah Mada
2014
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://repository.ugm.ac.id/131385/ http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=71843 |
| الوسوم: |
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| المؤسسة: | Universitas Gadjah Mada |
| الملخص: | Insurance involves two parties namely the insured and the insured (insurance
company). The insurer must pay some amounts to cover insured when they have a
loss, while the insured is obliged pay a premium as a compensation. This makes
insurance companies should determine the price of premium. One measure that is
used as a benchmark is a measure of risk, and one way to calculate the risk is
Value at Risk method from a loss function. Value at risk is one of the method to
measure the risk from a loss function. But It should be modeled as fit as possible
with the distribution of the data. For the insurance data with heavy tail, Double
Transformed Kernel Estimation for Value at Risk can be used |
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