(3.235.191.87) 您好!臺灣時間:2021/05/14 20:59
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果

詳目顯示:::

我願授權國圖
: 
twitterline
研究生:翁銘鴻
研究生(外文):Ming-Hong Wong
論文名稱:極值理論於附保證投資型商品之應用
論文名稱(外文):The Application of Extreme Value Theory To Investment Guarantees Insurance
指導教授:楊曉文楊曉文引用關係張揖平張揖平引用關係
指導教授(外文):Sharon S. YangYi-Ping Chang
學位類別:碩士
校院名稱:東吳大學
系所名稱:財務工程與精算數學系
學門:數學及統計學門
學類:其他數學及統計學類
論文種類:學術論文
畢業學年度:97
語文別:中文
論文頁數:30
中文關鍵詞:權益風險時間序列極值模型附保證投資型商品準備金風險管理
外文關鍵詞:Equity RiskEVT-based Time SeriesInvestment Guaranteed InsuranceReservingRisk Management
相關次數:
  • 被引用被引用:0
  • 點閱點閱:148
  • 評分評分:
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
隨著投資型保險商品的開發與創新,保險公司為了擴展銷售之業務,紛紛推出附保證投資型商品,藉此以吸引更多投保人加入。雖然附保證型態的設計可以增加保險商品的競爭力,但其潛藏的風險可能致使保險公司發生財務上的問題。然而在附保證投資型商品中,其主要風險來源為權益風險,且由於其風險特性並無法藉由大數法則加以分散,因此在準備金提存規範上,皆為建議採用隨機模型描述權益報酬風險。因此保險公司所面臨的便是該如何選定合適的模型,以對權益報酬風險做管理。以往常見的模型包括常態模型、狀態轉移對數常態模型以及時間序列相關模型等。本文考慮了由McNeil(2000)所提出之時間序列極值模型,並以台股加權指數為資料,比較在不同模型下對附保證型商品其準備金提存的影響。
In this article, we present several equity return models, like Lognormal, Regime-Switching Lognormal, and different innovation-based time series models, to compare the effect of model selection in reserving of investment guarantee insurance. In the beginning, we demonstrate how to use the EVT-based time series model, and then we apply this model to modeling TAIEX index (Taiwan Stock Exchange Index). After that, we start to compare EVT-based model with other models. The result shows that TAIEX is indeed a time series correlated market and EVT-based model would be more pessimistic than other models in prediction. At the end of this article, we analyze the reserve under different models when insurers issue GMMB or GMDB. Therefore, by the introduction of EVT-based model, we may widen the set of candidate models.
中文摘要 ……………………………………………………………………………IV
英文摘要 …………………………………………………………………………… V
壹、序論 …………………………………………………………………………… 1
貳、文獻回顧 ……………………………………………………………………… 3
參、極值理論與權益報酬時間序列模型 ………………………………………… 5
第一節、極值理論介紹………………………………………………………… 5
第二節、時間序列極值模型…………………………………………………… 8
肆、時間序列極值模型於附保證投資型商品權益風險之評估………………… 10
第一節、附保證投資型商品及權益風險………………………………………10
第二節、GMMB及GMDB保證之現金流量模型………………………………… 11
第三節、準備金及RBC之監理規定……………………………………………13
伍、時間序列極值模型於權益風險之應用……………………………………… 14
第一節、時間序列模型之配適分析 …………………………………………15
第二節、時間序列極值模型之配適分析………………………………………19
第三節、考慮極值效果下權益報酬之模擬比較………………………………22
第四節、附保證變額年金之準備金分析………………………………………24
陸、結論與建議 ……………………………………………………………………26
參考文獻 ……………………………………………………………………………28
附錄 …………………………………………………………………………………30
1.Barone-Adesi, G., F.(1998). “Don’t look back. Risk”, 11(8)
2.Bollerslev, T. (1986) "Generalized autoregressive conditional heteroskedasticity.", Journal of Econometrics, 31, 307-327..
3.Boudreault, M. (2009), “Multivariate Models of Equity Returns for Investment Guarantees Valuation”, North American Actuarial Journal, 13(1), 36-53
4.Coles, S. (2001). "An Introduction to Statistical Modeling of Extreme Values." Springer.
5.Danielsson, J.and de Vries, C. (1997a). "Beyond the sample: extreme quantile and probability estimation. ", Tinbergen Institute, Rotterdam.
6.Danielsson, J.and de Vries, C., (1997b). “Tail index and quantile estimation with very high frequency data” , Journal of Empirical Finance, 4, 241–257.
7.Danielsson, J.and de Vries, C., (1997c). ”Value-at-Risk and extreme returns”, FMG-Discussion Paper NO 23, Financial Markets Group, London School of Economics
8.Dupuis, D. (2004). "Multivariate Extreme Value Theory and Its Usefulness in Understanding Risk", North American Actuarial Journal, 10, 1-27
9.Embrechts, P. (1999) "Extreme value theory as a risk management tool. ", North American Actuarial Journal, 3(2), 30-41
10.Engle, R. F. (1982) "Autoregressive conditional heteroscedasticity with estimates of the variance of united kingdom inflation.", Econometrica, 50, 987-1006.
11.Hamilton, J. D. (1989). "A new approach to the economic analysis of non-stationary time series." Econometrica, 57, 357-384.
12.Hardy, M. R. (2001). "A regime switching model of long term stock returns.", North American Actuarial Journal, 5, 41-53.
13.Hardy, M. R. (2003). "Investment Guarantees: Modeling and Risk Management for Equity-Linked Life Insurance.", New York: John Wiley&Sons.
14.Hardy, M. R. (2006). “Validation of long-term equity return models for equity-linked guarantees”, North American Actuarial Journal, 10, 28-47
15.Junus, N. (2009). “A discussion of actuarial guideline 43 for variable annuities”, Milliman Research Report.
16.Longin, F. (1997). "From value at risk to stress testing, the extreme value approach.", Discussion Paper 97-1004, CERESSEC
17.McNeil, A. (1997), "Estimating the tails of loss severity distributions using extreme value theory," ASTIN Bulletin, 27, 117-137
18.McNeil, A. (1998). "Calculating Quantile Risk Measures for Financial Return Series using Extreme Value Theory.", ETH Zu¨rich.
19.McNeil, A. (2000), "Estimation of tail-related risk measures for heterosccedastic financial time series: an extreme value approach.", Journal of Empirical Finance, 7, 271-300
20.Sanders, D. (2005), "The Modeling of Extreme Events.", Institute of Actuaries, 11, 552-572
21.Tsay, T. (2005), "Analysis of Financial Time Series.", John Wiley & Sons
22.Wong, A. (2005), “Mixture Gaussian time series modeling of long-term market returns.”, North American Actuarial Journal, 9(4), 83-94.
23.楊曉文、汪信君等人(2008),「附保證給付投資型保險商品監理之研究」,金管會保險局委託研究計畫。
24.林昆毅(2005),投資模型在附保證給付投資型保險之比較與應用,台灣大學財務金融研究所碩士論文。
25.黃克威(2008),隨機投資模型在精算上的應用,東吳大學財務工程與精算數學研究所碩士論文
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top