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姓名 呂敏嘉(Ming-Chia Lu) 查詢紙本館藏 畢業系所 財務金融學系 論文名稱 反向抵押貸款採用隨機房價模型之分析
(The Application of Stochastic Models in Reserve Mortgage Analysis)相關論文 檔案 [Endnote RIS 格式]
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至系統瀏覽論文 ( 永不開放)
摘要(中) 隨著生活品質的改善,對於許多老年人來說,退休帳戶裡的錢,並不足以維持各種生活需要,因此「以房養老」的新型衍生性金融商品反向房屋抵押貸款興起,用來讓屋主可以以退休年金的形式來獲得貸款,利用他們擁有的住宅當作抵押品,並且死後將房屋賣出加以償還。發行機構在推出反向房屋抵押貸款時,在經濟層面所面臨最大的風險為臨界風險,當反向房屋抵押貸款最終出售房屋時,可能會隨著當時的房價導致面對不同的損失,若出售房價低於貸款的本金加累積利息時,貸款人最大清償部分為房屋之最大價值,未清償的部分即為貸款機構如保險公司以及金融機構所面臨的臨界風險。
此篇研究最主要是想探討英國的金融機構或者保險公司推出反向抵押商品時,其面臨的風險並量化之。透過建立不同的房價隨機模型比較最適的房價模型,以經驗解構法分解總體因子加入房價模型並且模擬房價加以分析,最後利用風險衡量指標VaR與CTE檢視其潛在的嚴重風險。摘要(英)
With the improvement in the quality of life, the money in retirement accounts are not to enough to sustain life for many older people. So, there are new derivative financial products called “House Reverse Mortgage”, which a homeowner can borrow money against the value of his or her home, receiving funds in the form of a fixed monthly payment. When
issuer release this products, they may face the greatest economic risk is “Critical Risk”. When the house value lower than the loan debt in the end of selling the house, the maximum repayment part of the lender is the maximum value of the house, and the unliquidated part is the critical risk faced by the issuer institution such as the insurance company and the financial institution.
The main purpose of this study is to quantify the risks when issuer institution issue house reverse mortgage. Through build differently house price stochastic model to compare the optimal housing price model and use empirical mode decomposition to analyze GDP and CPI influence in the house price. Finally, use the risk measure VaR and CTE examine the potentially serious risks.關鍵字(中) ★ 反向房屋抵押貸款 關鍵字(英) 論文目次
摘要 v
Abstract vi
目錄 vii
圖目錄 ix
表目錄 x
第一章、緒論 1
1-1研究動機 1
1-2 研究架構 4
第二章、反向抵押貸款 5
2-1起源 5
2-2英國制度介紹 6
2-3面臨之風險 7
2-4文獻回顧 9
第三章、房價模型 11
3-1 房價模型動態介紹 11
3-2 總體指標考慮經驗解構法 14
3-3 模型參數估計方法 17
第四章、房價模型配適分析方法 21
4-1 資料來源 21
4-2 模型配適 23
4-3 模型選擇 32
第五章、NNEG風險評估 36
5-1 模型基本假設 36
5-2 結果分析 38
5-3 VaR與CTE 風險衡量值 41
第六章、結論 44
附錄 46
附錄一、選擇模型準則 46
1-1 AIC(Akaike information criterion) 46
1-2 BIC(Bayesian information criterion) 46
1-3 Shibata 47
1-4 HQC (Hannan and Quinn Criterion): 47
附錄二、EGARCH 49
參考文獻 51參考文獻
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2. Donald F. Cunningham, Patric H. Hendershott, “Pricing FHA Mortgage Default Insurance”, Housing Finance Review, Vol. 3, No. 4, pp. 373-392, October 1984.
3. Hosios, A. J., & Pesando, J. E.,“Measuring prices in retransaction housing markets in Canada: evidence and implications”. Journal of Housing Economics, 1(1), 1–15, 1991.
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6. Johnny Siu-Hang, Li Mary R. Hardy, Ken Seng Tan,“ On pricing and hedging the no-negative-equity guarantee in equity release mechanisms”, The Journal of Risk and Insurance, Vol. 77, No. 2, 499-522,2010.
7. Karl E. Case, Robert J. Shiller. “The Efficiency of the Market for Single-Family Homes”, American Economic Review, Vol. 79, No. 1, pp. 125-137, March 1989.
8. Kau, James B., Donald C. Keenan, and T. Kim,“Transaction Costs, Suboptimal Termination, and Default Probabilities for Mortgages,” AREUEA Journal 21(3), 247-63., 1993.
9. Nelson, D.B., 1991, Conditional Heteroskedasticity in Asset Returns: A New Approach, Econometrica, 59: 347-370.
10. Nothaft, F. E., Lekkas, V. & Wang, G. H. K., “The Failure of the Mortgage-Backed Futures Contract”. Journal of Futures Markets, 15 (5), 585-603, 1995.
11. Safe Home Income Plans, SHIP Full Year Results 2007. World Wide Web: http://www.ship-ltd.org/bm doc/04-jan-08-02.pdf ,2008
12. . Wirch, J. L. and Hardy, M. R., A Synthesis of Risk Measures for 326, Capital Adequacy, Insurance: Mathematics and Economics, 25, 337-347, 1999.
13. 葉錦輝等, 「經驗解構法與台灣經濟成長之預測」, 經濟論文, 中央研究院經濟研究所, 559-598, 2012.指導教授 楊曉文 審核日期 2017-7-5 推文 plurk
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