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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 王之彥(Jr-Yan Wang) | |
| dc.contributor.author | Hsin-Ying Tseng | en |
| dc.contributor.author | 曾欣穎 | zh_TW |
| dc.date.accessioned | 2021-06-16T23:12:55Z | - |
| dc.date.available | 2015-08-17 | |
| dc.date.copyright | 2012-08-17 | |
| dc.date.issued | 2012 | |
| dc.date.submitted | 2012-08-02 | |
| dc.identifier.citation | [1] Bandreddi, S., S. Das, and R. Fan (2007). “Correlated Default Modeling with a Forest of BinomialTrees,” Journal of Fixed Income, Vol. 17, No. 3, pp.38–56.
[2] Black, F. and J. C. Cox (1976). “Valuing Corporate Securities: Some Effects of Bond Indenture Provisions,” Journal of Finance, Vol. 31, No. 2, pp. 351–367. [3] Burtschell, X., J. Gregory, and J. P. Laurent (2008). “A Comparative Analysis of CDO Pricing Models,” working paper. [4] Wu S.-H. (2010). ”A Bivariate Tree Approach for Pricing CDOs: Combination of a Defaultable Tree Model and the Hull White Interest Rate Model,” Master thesis, National Taiwan University. [5] Charles R. Nelson, Andrew F. Siegel (1987), “Parsimonious Modeling of Yield Curves,” The Journal of Business, Volume 60, Issue 4, 473~489. [6] Lin Y.-C. (2010). “Pricing CDOs with Defaultable Trinomial Trees under GARCH Processes,” Master thesis, National Taiwan University. [7] Huang S.-C. (2012). “Pricing CDOs with Defaultable Trinomial Trees under Different GARCH Processes,” Master thesis, National Taiwan University. [8] Chambers, D. R. and Q. Lu (2007). “A Tree Model for Pricing Convertible Bonds with Equity,Interest Rate, and Default Risk,” Journal of Derivatives, Vol. 14, No. 4, pp. 25–47. [9] Cox, J., S. Ross, and M. Rubinstein (1979). “Option Pricing: a Simplified Approach,” Journal of Financial Economics, Vol. 7, pp. 229–264. [10] Dai, T. S. (2009). “Efficient Option Pricing on Stocks Paying Discrete or Path-Dependent Dividends with the Stair Tree,' Quantitative Finance, Vol. 9, No. 7, pp. 827–838. [11] Das, S. and R. Sundaram (2004). “A Simple Model for Pricing Derivative Securities with Equity, Interest-rate and Default Risk,” Working paper. [12] Davis, M. and V. Lo (2001). “Infectious Defaults,” Quantitative Finance, Vol. 1, pp. 382–387. [13] Duffie, D. and N. Garleanu (2001). “Risk and Valuation of Collateralized Debt Obligations,” Financial Analysts Journal, Vol. 57, pp. 41–59. [14] Duffie, D. and K. J. Singleton (1999). “Modeling Term Structures of Defaultable Bonds,” Review of Financial Studies, Vol. 12, No.4, pp. 687–720. [15] Frey, R., A. J. McNeil, and M. Nyfeler (2001). “Copulas and Credit Models,” RISK, Vol. 13, 111– 114. [16] Giesecke, K. (2004). “Correlated Default with Incomplete Information,” Journal of Banking and Finance, Vol. 28, pp. 1521–1545. [17] John C. Hull (2011), “Options, Futures and Other Derivatives, 8th Edition,” Prentice Hall . [18] Hull, J. and A. White (2004). “Valuation of a CDO and an n-th to Default CDS Without Monte Carlo Simulation,” Journal of Derivatives, Vol. 12, No. 2, pp. 8–23. [19] Hull, J. and A. White (1994). “Numerical Procedures for Implementing Term Structure Model I: Single Factor Models,” Journal of Derivatives, Vol. 2, pp. 7–16. [20] Hull, J. and A. White (1996). “Hull-White on Derivatives-A compilation of articles,” published by Risk Books. [21] Hull, J. and A. White (2001). “Valuing Credit Default Swaps II: Modeling Default Correlations,” Journal of Derivatives, Vol. 8, No. 3, pp. 12–21. [22] Jarrow, R. A. and S. M. Turnbull (1995). “Pricing Derivatives on Financial Securities Subject to Credit Risk,” Journal of Finance, Vol. 50, No. 1, pp. 53–85. [23] Jarrow, R. A. and P. Protter (2004). “Structural Versus Reduced Form Models: A New Information Based Perspective,” Journal of Investment Management, Vol. 2, No. 2, pp. 1–10. [24] Li, D. X. (2000). “On Default Correlation: A Copula Function Approach,” Journal of Fixed Income, Vol. 9, No. 4, pp. 43–54. [25] Meneguzzo, D. and W. Vecchiato (2004). “Copula Sensitivity in Collateralized Debt Obligations and Basket Default Swaps,” Journal of Futures Markets, Vol. 24, No. 1, pp. 37–70. [26] Merton, R. (1974). “On the Pricing of Corporate Debt: The Risk Structure of Interest Rates,” Journal of Finance, Vol. 29, pp. 449–470. [27] Ritchken, P. and R. Trevor (1999). “Pricing Options under Generalized GARCH and Stochastic Volatility Processes,” Journal of Finance, Vol. 54, pp. 377–402. [28] Zhou, C. (2001). “An Analysis of Default Correlation and Multiple Defaults,” Review of Financial Studies, Vol. 14, pp. 555–576. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/64989 | - |
| dc.description.abstract | 本文章建構結合股價與利率的可違約立體樹狀模型，用以模擬CDS指數分券的價格，並且與市場價格比較驗證。
模型考慮隨機股價以及隨機利率，並採用均值追蹤演算法結合立體樹上分支機率限制 [0,1]，求得立體樹上由期初至到期日的路徑。相較於過往的立體樹模型，本文將股價的隨機過程與利率隨機過程的相關性、公司期間所配置的股利納入考量，立體樹上的各節點數據都可以透過對數轉換成同一時間點相對應的股票價格; 違約強度公式配置也有所更動，本論文將Nelson和Siegel於1987年發表的簡化殖利率曲線模型加入違約強度公式，以反映市場殖利率環境對公司違約機率的影響。 文章後半部，應用蒙地卡羅模擬iTraxx歐洲指數中114家公司的CDS價差分券。首先從期初開始，在每一期的計算過程中，同時產生累積機率與違約機率相比較，判斷該時間點立體樹狀模型違約與否以及立體樹上X值的路徑，直到到期日模擬數據告一段落，將數值轉換成股價，再將各公司發行之CDS價差按比例建立CDO分券。接著從到期日開始，將立體樹上之各節點之分券價值，回溯折現加總得到所有公司分券的價格的現值，並與實際市場價格相比較。 | zh_TW |
| dc.description.abstract | A defaultable bivariate tree approach is introduced to simulate the value of CDX and compare with real market price.
The stochastic processes of both stock prices and interest rates are considered in my bivariate model. The model also took the dividends and the correlation between two stochastic variables into account. I also adopted Dai’s mean tracking algorithm to improve the stability of probabilities and improved the default intensity formula by Nelson, Siegel’s (1987) parsimonious yield curve model. I used the corresponding data of iTaxx index and applied Monte Carlo simulation to simulate the spread of the iTraxx tranches. On the first stage, the model is calibrated to the current CDS market. Then I output the cumulated probability and compare with default probability. The default event is identified and the route on the bivariate tree is decided during the process. One the second stage, the tranche structure is created and the spread value is evaluated. I adopted the backward induction during the process for calculating the present discounted value. The above procedures were repeated twice under two assumptions: (1) The stochastic processes of interest rates and stock prices are independent. (2) The stochastic processes of interest rates and stock prices are dependent by considering the correlation coefficients between interest rates and each company. Finally, I compared the absolute errors between independent case and dependent case. The result shows that the independent case was slightly closer to the dependent case. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-16T23:12:55Z (GMT). No. of bitstreams: 1 ntu-101-R99724056-1.pdf: 2802761 bytes, checksum: 9baf0ad049142e4de0a2ef02b12e9f66 (MD5) Previous issue date: 2012 | en |
| dc.description.tableofcontents | List of Contents
謝辭 I 摘要 II Abstract III CHAPTER 1 INTRODUCTION 1 CHAPTER 2 METHODOLOGY 6 2.1 Defaultable CRR tree model 6 2.2 Mean tracking algorithm 13 2.3 Hull and White tree model 15 2.4 Parsimonious term structure 18 CHAPTER 3 BIVARIATE TREE MODELING 20 3.1 Components of the Bivariate Tree Model 20 3.2 Cholesky Decomposition 21 3.3 The revised default intensity function 27 CHAPTER 4 DEFAULT BEHAVIOR SIMULATION AND CORRELATION 28 4.1 Defaultable Bivariate Forest 28 4.2 Default Simulation Procedures 29 CHAPTER 5 NUMERICAL RESULTS 34 5.1 Calibration 34 5.2 Compare Result 40 5.3 Simulation and Market Fitness 42 CHAPTER 6 CONCLUSIONS 46 APPENDIX 48 REFERENCE 67 | |
| dc.language.iso | en | |
| dc.subject | CDO分券 | zh_TW |
| dc.subject | 違約強度 | zh_TW |
| dc.subject | iTraxx指數 | zh_TW |
| dc.subject | 隨機利率 | zh_TW |
| dc.subject | CRR模型 | zh_TW |
| dc.subject | Hull-White利率模型 | zh_TW |
| dc.subject | 正交化 | zh_TW |
| dc.subject | Cholesky 分解法 | zh_TW |
| dc.subject | 均值追蹤演算法 | zh_TW |
| dc.subject | CRR tree model | en |
| dc.subject | CDO Tranche | en |
| dc.subject | iTraxx index | en |
| dc.subject | Default Intensity | en |
| dc.subject | Stochastic process of Interest rate | en |
| dc.subject | Cholesky Decomposition | en |
| dc.subject | mean-tracking algorithm | en |
| dc.subject | Hull-White model | en |
| dc.title | CDO評價－考慮隨機利率與股價間相關性之雙變數樹狀評價模型 | zh_TW |
| dc.title | A CDO Pricing Model with Bivariate Tree Approach: Considering the Correlation between Stochastic Interest Rate and Stock Price | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 100-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 戴天時(Tian-Shyr Dai),郭家豪(Jia-hau Guo),張龍福(Lung-fu Chang) | |
| dc.subject.keyword | CRR模型,Hull-White利率模型,均值追蹤演算法,Cholesky 分解法,正交化,隨機利率,違約強度,iTraxx指數,CDO分券, | zh_TW |
| dc.subject.keyword | CRR tree model,Hull-White model,mean-tracking algorithm,Cholesky Decomposition,Stochastic process of Interest rate,Default Intensity,iTraxx index,CDO Tranche, | en |
| dc.relation.page | 68 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2012-08-03 | |
| dc.contributor.author-college | 管理學院 | zh_TW |
| dc.contributor.author-dept | 國際企業學研究所 | zh_TW |
| 顯示於系所單位： | 國際企業學系 | |
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