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研究生:蘇雍智
研究生(外文):Yong-Jhih Su
論文名稱:相關性微笑曲線模型之比較分析
論文名稱(外文):Comparative Analyses of Correlation Skew Models
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:2008
畢業學年度:96
語文別:英文
論文頁數:44
中文關鍵詞:合成型擔保債券憑證相關性微笑曲線機率杓斗法則因子關聯結構
外文關鍵詞:synthetic CDOcorrelation smileprobability bucketingNIG copulastochastic correlationlocal correlation
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本文旨在提供擔保債權憑證評價模型的比較分析。所比較的評價模型都建構在單因子關聯結構的架構下,並利用Hull and White (2004)所提出之機率杓斗法則(probability bucketing method)建構標的資產之違約損失分配,進而求算分券之信用價差。所考慮的模型有NIG copula,隨機相關模型(stochastic correlation model),局部相關模型(local correlation model)。此分析會對各個模型的市場配適度進行比較。有鑑於次級房貸風暴對於信用衍生性商品市場造成巨大的衝擊,該風暴對模型配適度的影響也會在本文中討論。最後,本文也會對各模型參數的穩定性進行比較。
In this work, we present a comparative analysis of correlation skew models for pricing of CDOs. All of these models are based on the factor copula pricing framework
and can generate correlation skews. The models compared are normal inverse Gaussian copula, stochastic correlation model and local correlation model. By using Gaussian copula as benchmark, the fitness of these models to market data will be tested. Because the subprime mortgage crisis causes structural changes on the credit derivatives market,
the fitness before the crisis and after the crisis is compared. Finally, the stability of parameter values over time will be given.
口試委員會審定書........................................................................................i
誌謝...............................................................................................................ii
摘要..............................................................................................................iii
Abstract ........................................................................................................iv
Chapter 1 Introduction ..................................................................................1
Chapter 2 Valuation of CDOs .......................................................................3
2.1 CDS, CDOs, and Index Tranches ....................................................3
2.2 General Pricing Formula for CDOs .................................................8
2.3 Review of Copula...........................................................................10
2.4 The Factor Copula Pricing Framework..........................................13
Chapter 3 Correlation Skew........................................................................22
3.1 Standard Market Model..................................................................22
3.2 Correlation Skew............................................................................23
3.3 Problems of Correlation Skew .......................................................27
Chapter 4 Correlation Skew Modeling .......................................................29
4.1 Normal Inverse Gaussian Copula...................................................29
4.2 Stochastic Correlation Model.........................................................32
4.3 Local Correlation Model ................................................................34
Chapter 5 Numerical Results ......................................................................37
5.1 Data and Model Calibration ...........................................................37
5.2 Market Fitness ................................................................................38
5.3 Stability of Parameters ...................................................................41
Chapter 6 Conclusions ................................................................................44
Bibliography................................................................................................45
Appendix .....................................................................................................46
[1] Andersen, L., J. Sidenius and S. Basu (2003) All Your Hedges in One Basket. RISK, November, pp. 67–72.
[2] Andersen, L and J. Sidenius (2004) Extensions to the Gaussian Copula: Random Recovery and Random Factor Loadings. Journal of Credit Risk, 1 No.1, pp. 29–70.
[3] Brigo, D. and F. Mercurio (2006) Interest Rate Models — Theory and Practice: With Smile, Inflation and Credit, 2nd ed., Springer, Berlin, pp. 724–737.
[4] Burtschell, X., J. Gregory and J.-P. Laurent (2007) Beyond the Gaussian Copula: Stochastic and Local Correlation. Journal of Credit Risk, Vol. 3, No. 1, pp. 31–62.
[5] Burtschell, X., J. Gregory and J.-P. Laurent (2005) A Comparative Analysis of CDO Pricing Models. Working paper, ISFA Actuarial School and BNP Parisbas, Paris.
[6] Hull, John C. and White, A. (2004) Valuation of n-th to Default CDS Without Monte Carlo Simulation. Journal of Derivatives, pp. 8–23.
[7] Kalemanova, A., B. Schmid, and R. Werner (2007) The Normal Inverse Gaussian Distribution for Synthetic CDO Pricing. Journal of Derivatives, Vol. 14, Iss. 3, pp.
80–93.
[8] Li, D. (2000) On Default Correlation: A Copula Approach. Journal of Fixed Income, Vol. 9, pp. 43–54.
[9] McGinty, L., E. Beinstein, R. Ahluwalia and M. Watts (2004) Introducing Base Correlations. Credit Derivatives Strategy, JPMorgan, London.
[10] Turc, J., P. Very and D. Benhamou (2005) Pricing CDOs with a Smile. SG Credit Research, Paris.
[11] Vasicek, O. (1987) Probability of Loss on Loan Portfolio. Technical report, KMV Corporation, San Francisco.
[12] Walker, M. (2005) Risk-neutral correlations in the pricing and hedging of basket credit derivatives. Journal of Credit Risk, Vol. 1, No. 1, pp. 131–139.
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