@inproceedings{839cddba00e84466a0d669a3a19370b5,
title = "Tail risk measures-based optimal reinsurance model for quota-share reinsurance",
abstract = "Optimal reinsurance model becomes a popular research area in both academicians and practitioners. Essentially, an optimal reinsurance model is to determine the optimal partitioning of a risk between insurer and reinsurer. In this research, the structure of optimal reinsurance is from the insurer's perspective. Reinsurance is an insurance for the insurers. Meanwhile, the insurer's risk are determined by some tail risk measures, such as Value-at-Risk (VaR), Tail VaR (TVaR), and Modified Tail VaR (MTVaR). We propose parametric and non-parametric estimators of these risk measures. To illustrate the applicability of our results, we derive the optimal reinsurance explicitly for Quota-share reinsurance.",
author = "Sari, {Suci Fratama} and Syuhada, {Khreshna I.A.}",
note = "Funding Information: This research was supported by Student Activity Support from Faculty of Mathematics and Natural Sciences, Institut Teknologi Bandung, Indonesia. Publisher Copyright: {\textcopyright} 2022 Author(s).; 2021 Asia-Pacific Conference on Applied Mathematics and Statistics, AMS 2021 ; Conference date: 20-02-2021 Through 22-02-2021",
year = "2022",
month = jun,
day = "16",
doi = "10.1063/5.0082753",
language = "English",
series = "AIP Conference Proceedings",
publisher = "American Institute of Physics Inc.",
editor = "Carlo Cattani",
booktitle = "2021 Asia-Pacific Conference on Applied Mathematics and Statistics",
address = "United States",
}