跳到主要內容

臺灣博碩士論文加值系統

(35.174.62.102) 您好!臺灣時間:2021/07/25 04:00
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:黃琮凱
研究生(外文):Tsung-Kai Huang
論文名稱:利用具相關性之二元樹模型做信用組合違約模擬
論文名稱(外文):Credit Portfolio Simulation Using Correlated Binomial Lattices
指導教授:呂育道呂育道引用關係
學位類別:碩士
校院名稱:國立臺灣大學
系所名稱:財務金融學研究所
學門:商業及管理學門
學類:財務金融學類
論文種類:學術論文
論文出版年:2009
畢業學年度:97
語文別:英文
論文頁數:50
中文關鍵詞:二元樹信用組合違約交換擔保債務憑證槓桿效果
外文關鍵詞:binomial latticebasket default swapscollateralized debt obligationsleverage effect
相關次數:
  • 被引用被引用:0
  • 點閱點閱:173
  • 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
本文中我們首先回顧Das and Sundaram (2004)與Bandreddi, et al. (2007)所提出的模型。Das and Sundaram (2004)提出了一個考量股價、利率、及信用風險的簡易二元樹模型,應用在可轉換債券之評價。Bandreddi, et al. (2007)利用該模型之簡化版來模擬具相關性的信用組合之違約行為。在我們的研究當中發現,於他們的模型設定之下會使得建立的二元樹上有不合理之風險中立機率值,而這些問題機率將使得模擬出的違約結果以及計算出之衍生性商品價格有偏誤。我們提出另一個模型,稱做D-CEV模型,用以替代原先之模型及解決該機率問題。該模型是傳統上考量股價槓桿效果(leverage effect)的二元樹模型之延伸,並且容易實作。我們更研究了我們所提出之模型的許多特性,發現我們的新模型不但能減緩Bandreddi, et al. (2007)之模型的許多缺陷,也能保留其良好屬性。我們更指出這樣的架構下如何滿足實證上能觀察到的許多現象,並且比較兩模型用以評價擔保債務憑證(Collateralized Debt Obligation)的結果。設定不同情境之下,Bandreddi, et al. (2007)之模型所評價出之價格皆低於我們提出之模型所得到的價格,且在不合理機率越多之下差異越顯著。
We revisit the models developed in Das and Sundaram (2004) and Bandreddi, et al. (2007). Bandreddi, et al. (2007) use a simplified version of the model developed by Das and Sundaram for correlated default simulation. We find that in their setting, problematic probabilities may arise which may cause biased results for the purpose of default simulation and the pricing of derivative products. We suggest an alternative model — the D-CEV model, as an alternative to address this problem. The new model is an extension of a popular binomial model and is easy to implement. We further explore the natural characteristics of our method with several numerical experiments. Our proposed model is found to resolve the unpleasant flaws in the model of Bandreddi, et al. (2007) while preserving its desirable properties. We also show how this framework accounts for several empirical features.
TABLE OF CONTENTS

I. INTRODUCTION 1
II. LITERATURE REVIEW 5
2.1 THE DEFAULTABLE CRR MODEL 5
2.2 CALIBRATING PARAMETERS 6
2.3 SIMULATING CORRELATED DEFAULT 8
III. AN ALTERNATIVE MODEL: THE DEFAULTABLE CEV MODEL 11
3.1 PROBLEMS WITH THE D-CRR MODEL 11
3.2 THE DEFAUTABLE CEV MODEL 12
IV. NUMERICAL EVALUATIONS 17
4.1 BASE CASE DATA 17
4.2 THE IMPACT OF EQUITY CORRELATION 19
4.3 THE IMPACT OF EQUITY VOLATILITY 20
4.4 THE IMPACT OF INTENSITY FUNCTION PARAMETERS 25
V. FURTHER RESEARCH AND APPLICATIONS 30
5.1 BASKET DEFAULT SWAPS 30
5.2 INTENSITY CORRELATION VS. CONDITIONAL CORRELATION 30
5.3 RESULTS FOR NTH-TO-DEFAULT CONTRACTS 34
5.4 THE VALUATION OF CDO TRANCHES 39
5.5 RESULTS FOR CDO TRANCHES 41
VI. CONCLUSIONS 44
REFERENCES 45
APPENDIX A 47
APPENDIX B 49
[1]Altman, E., Brady, B., Resti, A., and Sironi, A. (2005). “The Link between Default and Recovery Rates: Theory, Empirical Evidence and Implications,” Journal of Business, Vol. 78, No. 6, pp. 2203–2228.
[2]Bandreddi, S., Das, S., and Fan, R. (2007). “Correlated Default Modeling with a Forest of Binomial Trees,” Journal of Fixed Income, Vol. 17, No. 3, pp. 38–56.
[3]Beckers, S. (1980). “The Constant Elasticity of Variance Model and Its Implications For Option Pricing.” The Journal of Finance, Vol. 35, No. 3, pp. 661–673.
[4]Carayannopoulos, P., and Kalimipalli M. (2003). “Convertible Bonds Pricing and Inherent Biases,” Journal of Fixed Income, Vol. 13, No. 3, pp. 64–73.
[5]Carr, P., and Wu L. (2006). “Stock Options and Credit Default Swaps: A Joint Framework for Valuation and Estimation,” Working Paper, Baruch College, New York, New York.
[6]Cox, J., Ross, S., and Rubenstein M. (1979). “Option Pricing: A simplified Approach,” Journal of Financial Economics, Vol. 7, No. 3, pp. 229–263.
[7]Das, S., Duffie, D., Kapadia, N., and Saita, L. (2007). “Common Failings: How Corporate Defaults are Correlated,” Journal of Finance, Vol. 62, No.1, pp. 93–117.
[8]Das, S., and Sundaram R. (2004). “A Simple Model for Pricing Securities with Equity, Interest-Rate, and Default Risk,” Working Paper, Santa Clara University, Santa Clara, California.
[9]Das, S., and Sundaram R. (2007). “An Integrated Model for Hybrid Securities,” Management Science, Vol. 53, No. 9, pp. 1439–1451.
[10]Duffie, D., and Singleton, K. (1999). “Modeling Term Structures of Defaultable Bonds,” Review of Financial Studies, Vol. 12, No.4, pp. 687–720.
[11]Giesecke, K. (2004). “Credit Risk Modeling and Valuation: An Introduction,” Working Paper, Cornell University, Ithaca, New York.
[12]Gregory, J., and Laurent, J-P (2004). “In the Core of Correlation,” Risk, October 2004, pp. 87–91.
[13]Hull, J., Predescu M., White A. (2005). “The Valuation of Correlation- Dependent Credit Derivatives Using a Structural Model,” Working Paper, University of Toronto, Toronto.
[14]Hull, J., and White, A., (2004). “Valuation of a CDO and an nth to Default CDS Without Monte Carlo Simulation,” Journal of Derivatives, Vol. 12, No. 2, pp. 8–23.
[15]Jarrow, R. and Protter, P. (2004). “Structural Versus Reduced Form Models: A New Information Based Perspective,” Journal of Investment Management, Vol. 2, No. 2, pp. 1–10.
[16]Jarrow, R. and Rudd, A. (1983). Option Pricing. Homewood, Illinois: R.D. Irwin, Inc.
[17]Jarrow, R. and Turnbull, S. (1995). “Pricing Derivatives of Financial Securities Subject to Credit Risk,” Journal of Finance, Vol. 50, No. 1, pp. 53–85.
[18]Li, D. (2000). “On Default Correlation: A Copula Function Approach,” Journal of Fixed Income, Vol. 9, No. 4, pp. 43–54.
[19]Lyuu, Y-D. (2002). Financial Engineering and Computation: Principles, Mathematics, Algorithms. Cambridge: Cambridge University Press.
[20]Merton, R. (1974). “On the Pricing of Corporate Debt: The Risk Structure of Interest Rates.” Journal of Finance, Vol. 29, No. 2, pp.449–470.
[21]Nelson, D., and Ramaswamy, K. (1990). “Simple Binomial Processes as Diffusion Approximations in Financial Models,” The Review of Financial Studies, Vol. 3, No. 3, pp. 393–430.
[22]Schönbucher, P. (2003). Credit Derivatives Pricing Models: Models, Pricing and Implementation. Hoboken, New Jersey: Wiley Finance.
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top