請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/81170完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 許耀文(Yao-Wen Hsu) | |
| dc.contributor.author | Chia-Hung Lee | en |
| dc.contributor.author | 李家宏 | zh_TW |
| dc.date.accessioned | 2022-11-24T03:34:09Z | - |
| dc.date.available | 2021-08-13 | |
| dc.date.available | 2022-11-24T03:34:09Z | - |
| dc.date.copyright | 2021-08-13 | |
| dc.date.issued | 2021 | |
| dc.date.submitted | 2021-08-10 | |
| dc.identifier.citation | Alberto, R. (2019). Pricing Catastrophe Bonds Using Extreme Value Theory. University of Zurich, Bader, B., Yan, J., Zhang, X. (2018). Automated threshold selection for extreme value analysis via ordered goodness-of-fit tests with adjustment for false discovery rate. The Annals of Applied Statistics, 12(1), 310-329. Bodoff, N., Gan, Y. (2009). An Analysis of the Market Price of CAT Bonds. Casualty Actuarial Society E-Forum. Paper presented at the URL: https://www.casact.org/pubs/forum/09spforum/02Bodoff.pdf. Braun, A. (2016). Pricing in the primary market for cat bonds: new empirical evidence. Journal of Risk and Insurance, 83(4), 811-847. Caires, S. (2009). A comparative simulation study of the annual maxima and the peaks-over-threshold methods. Deltares report 1200264-002 for Rijkswaterstaat, Waterdienst. Castillo, E. (2012). Extreme value theory in engineering: Elsevier. Coles, S., Bawa, J., Trenner, L., Dorazio, P. (2001). An introduction to statistical modeling of extreme values (Vol. 208): Springer. Cox, J. C., Ingersoll Jr, J. E., Ross, S. A. (2005). A theory of the term structure of interest rates. In Theory of valuation (pp. 129-164): World Scientific. Cox, S. H., Pedersen, H. W. (2000). Catastrophe risk bonds. North American Actuarial Journal, 4(4), 56-82. Fisher, R. A., Tippett, L. H. C. (1928). Limiting forms of the frequency distribution of the largest or smallest member of a sample. Paper presented at the Mathematical proceedings of the Cambridge philosophical society. G'Sell, M. G., Wager, S., Chouldechova, A., Tibshirani, R. (2016). Sequential selection procedures and false discovery rate control. Journal of the Royal Statistical Society: Series B: Statistical Methodology, 423-444. Galeotti, M., Gürtler, M., Winkelvos, C. (2013). Accuracy of premium calculation models for CAT bonds—an empirical analysis. Journal of Risk and Insurance, 80(2), 401-421. Gnedenko, B. (1943). Sur La Distribution Limite Du Terme Maximum D'Une Serie Aleatoire. Annals of Mathematics, 44, 423. Gnedenko, B. (1943). Sur la distribution limite du terme maximum d'une serie aleatoire. Annals of Mathematics, 423-453. Hull, J. (2015). Options, futures, and other derivatives Ninth edition. In: Boston: Pearson. Jha, A. K., Bloch, R., Lamond, J. (2012). Cities and Flooding: A Guide to Integrated Urban Flood Risk Management for the 21st Century. Jonkman, S. (2005). Global Perspectives on Loss of Human Life Caused by Floods. Natural Hazards, 34, 151-175. Kladívko, K. (2007). Maximum likelihood estimation of the Cox-Ingersoll-Ross process: the Matlab implementation. Technical Computing Prague, 7(8). Lomba, J. S., Alves, M. I. F. (2020). L-moments for automatic threshold selection in extreme value analysis. Stochastic Environmental Research and Risk Assessment, 34(3), 465-491. Longin, F. (2016). Extreme Events in Finance : A Handbook of Extreme Value Theory and Its Applications. Ma, Z.-G., Ma, C.-Q. (2013). Pricing catastrophe risk bonds: A mixed approximation method. Insurance: Mathematics and Economics, 52(2), 243-254. Northrop, P. J., Coleman, C. L. (2014). Improved threshold diagnostic plots for extreme value analyses. Extremes, 17(2), 289-303. Von Mises, R. (1936). La distribution de la plus grande de n valuers. Rev. math. Union interbalcanique, 1, 141-160. Wadsworth, J., Tawn, J. (2012). Likelihood‐based procedures for threshold diagnostics and uncertainty in extreme value modelling. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 74(3), 543-567. Wang, Q. (1991). The POT model described by the generalized Pareto distribution with Poisson arrival rate. Journal of Hydrology, 129(1-4), 263-280. Wilbanks, T. J., Lankao, P. R., Bao, M., Berkhout, F., Cairncross, S., Ceron, J.-P., . . . Zapata-Marti, R. (2007). Industry, settlement and society. In Climate Change 2007: Impacts, Adaptation and Vulnerability, Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (pp. 357-390): Cambridge University Press. Zimbidis, A. A., Frangos, N. E., Pantelous, A. A. (2007). Modeling earthquake risk via extreme value theory and pricing the respective catastrophe bonds. ASTIN Bulletin: The Journal of the IAA, 37(1), 163-183. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/81170 | - |
| dc.description.abstract | 隨著氣候變遷的嚴重加劇，金融市場需要有效的對更加頻繁發生的極端洪水災害避險，有鑒於此需求，本研究有兩個目的，一是探討洪水巨災債券可以如何幫助保險公司將巨災風險轉移到證券市場的機制，二是使用極值理論對美國聯邦緊急事務管理局的開放資料集進行數值分析與模擬，並於本文最後利用蒙地卡羅方法，設計出完整的巨災債券定價模型，計算在不完全市場下，洪水巨災債券的預期價格及相關風險度量，使保險公司、再保險公司及投資人有更多樣化的金融避險工具。 本研究基於極值理論，透過廣義柏拉圖(Generalized Pareto)分配參數模擬洪水巨災的索賠金額，並採用計分檢定選擇法(score test selection method)及連續適合度檢定選擇法(sequential goodness-of-fit selection method)兩種方法決定廣義柏拉圖分配的最適門檻值，由此可得到模擬索賠金額的最佳分配，使得債券定價模型更精準。 | zh_TW |
| dc.description.provenance | Made available in DSpace on 2022-11-24T03:34:09Z (GMT). No. of bitstreams: 1 U0001-0508202112212000.pdf: 1735356 bytes, checksum: 653bb2fab75f7595934074c64d46c94e (MD5) Previous issue date: 2021 | en |
| dc.description.tableofcontents | "謝辭 i 摘要 ii Abstract iii 第一章 緒論 1 1.1 研究動機與目的 1 1.2 本文架構 2 第二章 文獻回顧 3 第三章 巨災債券 5 3.1 損失起賠觸發方式 5 3.2 結構 6 第四章 研究方法 8 4.1 巨災債券定價模型 8 4.1.1 機率測度空間 8 4.1.2 巨災零息債券 8 4.1.3 巨災附息債券 10 4.1.4 蒙地卡羅定價 12 4.1.5 廣義柏拉圖分配 12 4.1.6 The Cox-Ingersoll-Ross 模型 12 第五章 極值理論 16 5.1 確定極端值 17 5.2 一般化極值分配 18 5.2.1 Fisher–Tippett–Gnedenko定理： 18 5.3 廣義柏拉圖分配 19 5.4 選取門檻值 20 5.4.1 計分檢定選擇法(score test selection method , STSM) 20 5.4.2 連續適合度檢定選擇法(sequential goodness-of-fit selection method , SGFSM) 21 第六章 資料及實證研究 23 6.1 資料描述 23 6.1.1 巨災債券 23 6.1.2 FEMA資料集 24 6.2 分析步驟及數值計算 26 6.2.1 資料前處理 26 6.2.2 模擬廣義柏拉圖分配並估計參數 28 6.2.3 巨災債券定價 31 6.2.4 巨災風險計算 33 第七章 結論 37 參考文獻 37 " | |
| dc.language.iso | zh-TW | |
| dc.subject | 蒙地卡羅法 | zh_TW |
| dc.subject | 越檻高峰 | zh_TW |
| dc.subject | 廣義柏拉圖分配 | zh_TW |
| dc.subject | 極值理論 | zh_TW |
| dc.subject | 洪水巨災債券 | zh_TW |
| dc.subject | Peaks-over-Threshold | en |
| dc.subject | Generalized Pareto Distribution | en |
| dc.subject | Extreme Value Theory (EVT) | en |
| dc.subject | Monte Carlo method | en |
| dc.subject | flood catastrophe bond | en |
| dc.title | 廣義柏拉圖分配與洪水巨災債券之定價模型 | zh_TW |
| dc.title | Pricing Flood Catastrophe Bonds: Using the Generalized Pareto Distribution | en |
| dc.date.schoolyear | 109-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 蔡宛珊(Hsin-Tsai Liu),荷世平(Chih-Yang Tseng) | |
| dc.subject.keyword | 極值理論,廣義柏拉圖分配,越檻高峰,蒙地卡羅法,洪水巨災債券, | zh_TW |
| dc.subject.keyword | Extreme Value Theory (EVT),Generalized Pareto Distribution,Peaks-over-Threshold,Monte Carlo method,flood catastrophe bond, | en |
| dc.relation.page | 39 | |
| dc.identifier.doi | 10.6342/NTU202102103 | |
| dc.rights.note | 同意授權(限校園內公開) | |
| dc.date.accepted | 2021-08-11 | |
| dc.contributor.author-dept | 共同教育中心 | zh_TW |
| dc.contributor.author-dept | 統計碩士學位學程 | zh_TW |
| 顯示於系所單位： | 統計碩士學位學程 | |
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