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Single Earthquake Bond Pricing Framework With Double Trigger Parameters Based On Multi Regional Seismic Information
Journal
mathematics
Date Issued
2023
Author(s)
Wulan Anggraeni
Sudradjat Supian
Sukono
Nurfadhlina Abdul Halim
DOI
10.3390/math11030689
Abstract
: The investor interest in multi-regional earthquake bonds may drop because high-risk locations are less appealing to investors than low-risk ones. Furthermore, a single parameter (earthquake
magnitude) cannot accurately express the severity due to an earthquake. Therefore, the aim of this
research is to propose valuing a framework for single earthquake bonds (SEB) using a double parameter trigger type, namely magnitude and depth of earthquakes, based on zone division according to
seismic information. The zone division stage is divided into two stages. The first stage is to divide the
covered area based on regional administrative boundaries and clustering based on the earthquake
disaster risk index (EDRI), and the second stage involves clustering based on magnitude and depth of
earthquakes and distance between earthquake events using the K-Means and K-Medoids algorithms.
The distribution of double parameter triggers is modeled using the Archimedean copula. The result
obtained is that the price of SEB based on the clustering result of EDRI categories and K-Means
is higher than the price obtained by clustering EDRI categories and K-Medoids with maturities of
less than 5 years. The result of this research is expected to assist the Special Purpose Vehicle in
determining the price of SEB.
magnitude) cannot accurately express the severity due to an earthquake. Therefore, the aim of this
research is to propose valuing a framework for single earthquake bonds (SEB) using a double parameter trigger type, namely magnitude and depth of earthquakes, based on zone division according to
seismic information. The zone division stage is divided into two stages. The first stage is to divide the
covered area based on regional administrative boundaries and clustering based on the earthquake
disaster risk index (EDRI), and the second stage involves clustering based on magnitude and depth of
earthquakes and distance between earthquake events using the K-Means and K-Medoids algorithms.
The distribution of double parameter triggers is modeled using the Archimedean copula. The result
obtained is that the price of SEB based on the clustering result of EDRI categories and K-Means
is higher than the price obtained by clustering EDRI categories and K-Medoids with maturities of
less than 5 years. The result of this research is expected to assist the Special Purpose Vehicle in
determining the price of SEB.
Subjects
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