VALUE AT RISK NONPARAMETRIK UNTUK CLAIM SEVERITY PADA ASURANSI KERUGIAN MENGGUNAKAN ESTIMASI KERNEL BERTRANSFORMASI GANDA

• Main Authors: , DIAH PUTRI RAMADHANI, , Prof. Dr.rer.nat. Dedi Rosadi,S.Si.,M.Sc.
• Format: Theses and Dissertations NonPeerReviewed
• Published: [Yogyakarta] : Universitas Gadjah Mada 2014
• Subjects: ETD
• Online Access: 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
• Institution: Universitas Gadjah Mada

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