2023
DOI: 10.5267/j.dsl.2023.3.001
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Estimating flood catastrophe bond prices using approximation method of the loss aggregate distribution: Evidence from Indonesia

Abstract: Losses experienced by the Indonesian government due to floods are predicted. It is because of the significance of population growth, closure of water catchment areas, and climate change in many regions in Indonesia. The government has tried to reduce the risk but faces insufficient funds. Therefore, new innovative funding sources are essential to overcome these limitations. One way to obtain it is through issuing Flood Catastrophe Bonds (FCB). Unfortunately, Indonesia has had no FCB price estimate until now. O… Show more

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Cited by 7 publications
(5 citation statements)
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“…Consequently, the methods used to model the index are very similar for each type of catastrophe [56,57]. For example, Deng et al [26] and Ibrahim et al [29], respectively, modeled drought and flood catastrophe bond prices with an indemnity index. However, even though the types of catastrophes are different, the method used to model the index is the same, namely, a homogeneous compound Poisson process.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…Consequently, the methods used to model the index are very similar for each type of catastrophe [56,57]. For example, Deng et al [26] and Ibrahim et al [29], respectively, modeled drought and flood catastrophe bond prices with an indemnity index. However, even though the types of catastrophes are different, the method used to model the index is the same, namely, a homogeneous compound Poisson process.…”
Section: Discussionmentioning
confidence: 99%
“…Therefore, under these conditions, ECB will be more attractive to investors. Even though several countries have issued ECBs, there are fundamental obstacles at the issuance stage that must be continuously studied, namely, the fair price setting stage [14,29]. This is a tricky stage because the pricing framework integrates financial and earthquake risk variables.…”
Section: Type Of Catastrophementioning
confidence: 99%
“…Data clustering using the K-means algorithm is based on the closest distance to a particular centroid [56]. The K-means algorithm is carried out iteratively until there is no change between the new and old centroids [57,58]. In other words, the iteration stops when the members of each current cluster are equal to the members of each previous cluster.…”
Section: Stock Clustering With Two-dimensional K-meansmentioning
confidence: 99%
“…At a time when the risk of catastrophic losses increases, the chances of claims occurring and investors losing their capital in bonds also increase. Thus, the shortfall in this country's catastrophe bonds must be overcome as soon as possible [6,7]. and storms [4,5] as seen in Figure 1 (the increasing tendency can be seen from the area under the curve, which tends to get bigger yearly).…”
Section: Introductionmentioning
confidence: 99%
“…At a time when the risk of catastrophic losses increases, the chances of claims occurring and investors losing their capital in bonds also increase. Thus, the shortfall in this country's catastrophe bonds must be overcome as soon as possible [6,7]. One of the solutions to overcome the problem of too large an area scale in the SCB is to make it into a smaller regional scale.…”
Section: Introductionmentioning
confidence: 99%