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題名 具提前解約權之聯貸信用違約交換及其指數型擔保債權憑證的評價與避險
Pricing and Hedging of Loan CDS and CDX with Cancellable Rights
作者 楊文瀚
Yang, Wen Han
貢獻者 江彌修
Chiang, Mi Hsiu
楊文瀚
Yang, Wen Han
關鍵詞 聯貸信用違約交換
提前解約權
違約強度模型
因子聯繫模型
分券避險參數
loan CDS
cancellable rights
intensity-based model
factor copula
tranche Deltas
日期 2013
上傳時間 21-Jul-2014 15:38:37 (UTC+8)
摘要 本文利用隨機違約強度模型 (stochastic intensity-based model) 和擴展的高斯一因子聯繫模型 (extended one factor Gaussian copula model) 分別來探討具提前解約權之聯貸信用違約交換 (LCDS) 的單一資產和其指數型擔保債權憑證 (LCDX tranche swap) 的評價和避險。以上所有用到的兩個模型都是以外生給定的違約強度和可取消性的強度來決定違約和提前解約的事件的發生機率。
本文將針對具提前解約權之聯貸信用違約交換 (Legacy LCDS) 以及沒有提前解約權之聯貸信用違約交換 (Bullet LCDS) 兩者進行比較，藉此觀察提前解約權 (Cancellable Rights) 對於此商品的信用價差之影響。同樣地，此一比較也會延伸至對於其指數型擔保債權憑證的部分的探討。另外，本文也將透過敏感度分析，來觀察參數φ (違約和可取性之間的相關性) 在模型中扮演的腳色。
最後，本文利用風險衡量指標以及Delta避險的方式，將可以清楚看到模擬的結果中，其指數型擔保債權憑證在不同分券底下所具有的風險特徵和其避險所需負擔的成本，希望藉此提供投資人和後續研究者一些參考和方向。
In this paper we investigate the pricing and hedging issues of Loan CDS (LCDS) and its index product, the Loan CDX (LCDX) tranche swap under intensity-based model and extended one factor Gaussian copula, respectively. Although market today has developed the bullet LCDS to remove the cancellation feature from syndicated loan derivatives expecting to improve the liquidity of the loan market, still a great proportion is traded on the Legacy LCDS with early termination.
Here, we first address on the difference between the spread for Legacy LCDS and Bullet LCDS (LCDS with and without a cancellation feature), then we go further to consider the index product LCDX tranche swap to test the difference of the spread under different subordination levels. Consequently, our results suggest that the computed spread is generally higher for the Bullet LCDS and Bullet LCDX tranche swap; however, we find it really interesting that the super senior tranche for the cancellable Legacy LCDX tranche swap is possible to have a higher spread than the non-cancellable Bullet LCDX tranche swap when there is strong negative correlation between default and cancellation.
Besides, we try to find out the role of the correlation parameter φ (correlation between default time and cancellation time) in both models using sensitivity analysis. Furthermore, using risk measures that consider expected loss and unexpected loss, we examine the risk characteristics of such products. Finally, we delve into the hedging issue for the LCDX tranche swap, again comparing results of the Legacy and Bullet version of the instrument. Efficient calculations for the hedging parameters and hedging costs are demonstrated, and we provide an in-depth analysis for the relevant hedging implications followed from our numerical results.
參考文獻 1. Bandreddi, S., Kakodkar, A., Shi, R.,Tanna, S., and Shchuchinov,Y. (2007). “A barrier model to price cancellation in LCDS. Credit Derivatives Strategy”, Merrill Lynch.
2. Benzschawel, T., DaGraca, J., Kamra, A., and Yu, J. (2008). “Valuing loan credit default swap cancellability”. The Journal of Credit Risk 4(3), 21–38.
3. Chiang, M., Yueh, M., and Lin, A. (2009). “The Pricing and Hedging of Synthetic CDOs Under the Conditional Independence Assumption”, The Official Publication of Taiwan Finance Association, volume 17, number 1, March 2009.
4. Duffie, D., D. Filipovi´c, and W. Schachermayer (2003). “Affine Processes and Applications in Finance”, Annals of Applied Probability 13, 984.1053.
5. Duffie, D., J. Pan, and K. Singleton (2000). “Transform Analysis and Asset Pricing for Affine Jump Diffusions”, Econometrica 68, 1343.1376.
6. Dobranszky, P. and Schoutens, W. (2009). “Do not forget the cancellation: Marking-to-market and hedging LCDX tranches”, Working Paper.
7. Dobranszky, P. (2008). “Joint modeling of CDS and LCDS spreads with correlated default and prepayment intensities and with stochastic recovery rate”, Tech. Rep. 08-04, Statistics Section, K.U. Leuven
8. Elizalde, A., Jonsson, J., Gallo, A., Kakodkar A., and Bandreddi, S. (2007). Pricing cancellable LCDS. Credit Derivatives Strategy, Merrill Lynch.
9. Gibson, M. (2004). “Understanding the risk of synthetic CDOs”, FEDS Discussion Papers, no. 2004-36, Board of Governors of the Federal Reserve System.
10. Hull, J., and White, A. (2000).“Valuing credit default swaps: no counterparty default risk”, Journal of Derivatives 8(1), 29–40.
11. Jarrow, R. and F. Yu (2001). “Counterparty Risk and the Pricing of Defaultable Securities”, Journal of Finance 56, 1765.1800.
12. JP Morgan (2006). Credit derivatives handbook. Corporate Quantitative Research.
13. Lando, D. (2004). Credit Risk Modeling. Princeton, NJ, Princeton University Press.
14. Li, D. X. (2000). On default correlation: A copula function approach (working paper, The RiskMetrics Group), 99-07
15. Liang, Michael (2009). “Valuation of Loan CDS and Synthetic Loan CDS with Prepayment Risk”, Financial Markets, Industrial Bank (China) Co.,Ltd
16. Markit (2014). Markit Credit Indices: A Primer, January 2014.
17. Markit (2010). One in the chamber: the new North American bullet LCDS contract and its impact on Markit LCDX indices and tranches.Web Resource, Markit.
18. Markit. Markit LCDX Primer.
19. Morgan, S., and Zheng, Z. (2007). From CDS to LCDS: accounting for cancellation. Quantitative Credit Research, Lehman Brothers.
20. Ong, M., Li., D., Lu, D. (2012), “A survey of loan credit default swap pricing models”, Journal of Credit Risk Volume 8/Number 3, Fall 2012 (67–96).
21. Scott, A., Beinstein, E., and Le, K. (2007), “Loan CDS: valuing the cancellable feature”, Corporate Quantitative Research, JP Morgan.
22. Shek, H., Shunichiro, U., and Wei, Z. (2007), “Valuation of Loan CDS and CDX”, Working Paper, Stanford University.
23. Wei, Z. (2007). “Valuation of loan CDS under intensity-based model”, Working Paper, Department of Statistics, Stanford University.
描述 碩士
國立政治大學
金融研究所
101352025
102
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0101352025
資料類型 thesis
dc.contributor.advisor 江彌修zh_TW
dc.contributor.advisor Chiang, Mi Hsiuen_US
dc.contributor.author (Authors) 楊文瀚zh_TW
dc.contributor.author (Authors) Yang, Wen Hanen_US
dc.creator (作者) 楊文瀚zh_TW
dc.creator (作者) Yang, Wen Hanen_US
dc.date (日期) 2013en_US
dc.date.accessioned 21-Jul-2014 15:38:37 (UTC+8)-
dc.date.available 21-Jul-2014 15:38:37 (UTC+8)-
dc.date.issued (上傳時間) 21-Jul-2014 15:38:37 (UTC+8)-
dc.identifier (Other Identifiers) G0101352025en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/67602-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 金融研究所zh_TW
dc.description (描述) 101352025zh_TW
dc.description (描述) 102zh_TW
dc.description.abstract (摘要) 本文利用隨機違約強度模型 (stochastic intensity-based model) 和擴展的高斯一因子聯繫模型 (extended one factor Gaussian copula model) 分別來探討具提前解約權之聯貸信用違約交換 (LCDS) 的單一資產和其指數型擔保債權憑證 (LCDX tranche swap) 的評價和避險。以上所有用到的兩個模型都是以外生給定的違約強度和可取消性的強度來決定違約和提前解約的事件的發生機率。
本文將針對具提前解約權之聯貸信用違約交換 (Legacy LCDS) 以及沒有提前解約權之聯貸信用違約交換 (Bullet LCDS) 兩者進行比較，藉此觀察提前解約權 (Cancellable Rights) 對於此商品的信用價差之影響。同樣地，此一比較也會延伸至對於其指數型擔保債權憑證的部分的探討。另外，本文也將透過敏感度分析，來觀察參數φ (違約和可取性之間的相關性) 在模型中扮演的腳色。
最後，本文利用風險衡量指標以及Delta避險的方式，將可以清楚看到模擬的結果中，其指數型擔保債權憑證在不同分券底下所具有的風險特徵和其避險所需負擔的成本，希望藉此提供投資人和後續研究者一些參考和方向。		zh_TW
dc.description.abstract (摘要) In this paper we investigate the pricing and hedging issues of Loan CDS (LCDS) and its index product, the Loan CDX (LCDX) tranche swap under intensity-based model and extended one factor Gaussian copula, respectively. Although market today has developed the bullet LCDS to remove the cancellation feature from syndicated loan derivatives expecting to improve the liquidity of the loan market, still a great proportion is traded on the Legacy LCDS with early termination.
Here, we first address on the difference between the spread for Legacy LCDS and Bullet LCDS (LCDS with and without a cancellation feature), then we go further to consider the index product LCDX tranche swap to test the difference of the spread under different subordination levels. Consequently, our results suggest that the computed spread is generally higher for the Bullet LCDS and Bullet LCDX tranche swap; however, we find it really interesting that the super senior tranche for the cancellable Legacy LCDX tranche swap is possible to have a higher spread than the non-cancellable Bullet LCDX tranche swap when there is strong negative correlation between default and cancellation.
Besides, we try to find out the role of the correlation parameter φ (correlation between default time and cancellation time) in both models using sensitivity analysis. Furthermore, using risk measures that consider expected loss and unexpected loss, we examine the risk characteristics of such products. Finally, we delve into the hedging issue for the LCDX tranche swap, again comparing results of the Legacy and Bullet version of the instrument. Efficient calculations for the hedging parameters and hedging costs are demonstrated, and we provide an in-depth analysis for the relevant hedging implications followed from our numerical results.		en_US
dc.description.tableofcontents Contents
1 Introduction 1
1.1 Background 1
1.2 Research targets 3
1.3 Organization 4
2 Literature Review 5
3 Valuation Framework 8
3.1 Product Outline 8
3.1.1 Loan Credit Default Swap 8
3.1.2 Comparison of Standard CDS and Loan CDS 9
3.1.3 LCDX index 10
3.1.4 Tranched LCDX 11
3.2 Modeling Loan CDS 14
3.2.1 Intensity-based model 17
3.2.2 Affine model for LCDS 20
3.2.3 Model Solution with CIR intensities 23
3.3 Modeling Loan CDX tranche swap 26
3.3.1 One factor Gaussian copula model 30
3.3.2 Extended double barrier one factor 31
4 Credit Risk Measurement and Hedging 34
4.1 Credit Risk Measures—Expected loss 34
4.2 Credit Risk Measures—Unexpected loss 35
4.3 Hedge Ratios 35
5 Numerical Results 38
5.1 Model Settings 38
5.1.1 Loan CDS 38
5.1.2 Loan CDX tranche swap 38
5.2 Sensitivity Analysis 39
5.2.1 Loan CDS 39
5.2.2 Loan CDX tranche swap 43
5.3 Risk Measurement and Hedging 54
5.3.1 Expected Loss Measurement 54
5.3.2 Unexpected Loss Measurement 57
5.3.3 Hedging Analysis 60
6 Conclusion 66
Reference 68		zh_TW
dc.format.extent 1306651 bytes-
dc.format.mimetype application/pdf-
dc.language.iso en_US-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0101352025en_US
dc.subject (關鍵詞) 聯貸信用違約交換zh_TW
dc.subject (關鍵詞) 提前解約權zh_TW
dc.subject (關鍵詞) 違約強度模型zh_TW
dc.subject (關鍵詞) 因子聯繫模型zh_TW
dc.subject (關鍵詞) 分券避險參數zh_TW
dc.subject (關鍵詞) loan CDSen_US
dc.subject (關鍵詞) cancellable rightsen_US
dc.subject (關鍵詞) intensity-based modelen_US
dc.subject (關鍵詞) factor copulaen_US
dc.subject (關鍵詞) tranche Deltasen_US
dc.title (題名) 具提前解約權之聯貸信用違約交換及其指數型擔保債權憑證的評價與避險zh_TW
dc.title (題名) Pricing and Hedging of Loan CDS and CDX with Cancellable Rightsen_US
dc.type (資料類型) thesisen
dc.relation.reference (參考文獻) 1. Bandreddi, S., Kakodkar, A., Shi, R.,Tanna, S., and Shchuchinov,Y. (2007). “A barrier model to price cancellation in LCDS. Credit Derivatives Strategy”, Merrill Lynch.
2. Benzschawel, T., DaGraca, J., Kamra, A., and Yu, J. (2008). “Valuing loan credit default swap cancellability”. The Journal of Credit Risk 4(3), 21–38.
3. Chiang, M., Yueh, M., and Lin, A. (2009). “The Pricing and Hedging of Synthetic CDOs Under the Conditional Independence Assumption”, The Official Publication of Taiwan Finance Association, volume 17, number 1, March 2009.
4. Duffie, D., D. Filipovi´c, and W. Schachermayer (2003). “Affine Processes and Applications in Finance”, Annals of Applied Probability 13, 984.1053.
5. Duffie, D., J. Pan, and K. Singleton (2000). “Transform Analysis and Asset Pricing for Affine Jump Diffusions”, Econometrica 68, 1343.1376.
6. Dobranszky, P. and Schoutens, W. (2009). “Do not forget the cancellation: Marking-to-market and hedging LCDX tranches”, Working Paper.
7. Dobranszky, P. (2008). “Joint modeling of CDS and LCDS spreads with correlated default and prepayment intensities and with stochastic recovery rate”, Tech. Rep. 08-04, Statistics Section, K.U. Leuven
8. Elizalde, A., Jonsson, J., Gallo, A., Kakodkar A., and Bandreddi, S. (2007). Pricing cancellable LCDS. Credit Derivatives Strategy, Merrill Lynch.
9. Gibson, M. (2004). “Understanding the risk of synthetic CDOs”, FEDS Discussion Papers, no. 2004-36, Board of Governors of the Federal Reserve System.
10. Hull, J., and White, A. (2000).“Valuing credit default swaps: no counterparty default risk”, Journal of Derivatives 8(1), 29–40.
11. Jarrow, R. and F. Yu (2001). “Counterparty Risk and the Pricing of Defaultable Securities”, Journal of Finance 56, 1765.1800.
12. JP Morgan (2006). Credit derivatives handbook. Corporate Quantitative Research.
13. Lando, D. (2004). Credit Risk Modeling. Princeton, NJ, Princeton University Press.
14. Li, D. X. (2000). On default correlation: A copula function approach (working paper, The RiskMetrics Group), 99-07
15. Liang, Michael (2009). “Valuation of Loan CDS and Synthetic Loan CDS with Prepayment Risk”, Financial Markets, Industrial Bank (China) Co.,Ltd
16. Markit (2014). Markit Credit Indices: A Primer, January 2014.
17. Markit (2010). One in the chamber: the new North American bullet LCDS contract and its impact on Markit LCDX indices and tranches.Web Resource, Markit.
18. Markit. Markit LCDX Primer.
19. Morgan, S., and Zheng, Z. (2007). From CDS to LCDS: accounting for cancellation. Quantitative Credit Research, Lehman Brothers.
20. Ong, M., Li., D., Lu, D. (2012), “A survey of loan credit default swap pricing models”, Journal of Credit Risk Volume 8/Number 3, Fall 2012 (67–96).
21. Scott, A., Beinstein, E., and Le, K. (2007), “Loan CDS: valuing the cancellable feature”, Corporate Quantitative Research, JP Morgan.
22. Shek, H., Shunichiro, U., and Wei, Z. (2007), “Valuation of Loan CDS and CDX”, Working Paper, Stanford University.
23. Wei, Z. (2007). “Valuation of loan CDS under intensity-based model”, Working Paper, Department of Statistics, Stanford University.		zh_TW