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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 呂育道(Yuh-Dauh Lyuu) | |
| dc.contributor.author | Sheng-Hsuan Lin | en |
| dc.contributor.author | 林聖軒 | zh_TW |
| dc.date.accessioned | 2021-06-16T09:18:18Z | - |
| dc.date.available | 2018-07-20 | |
| dc.date.copyright | 2017-07-20 | |
| dc.date.issued | 2017 | |
| dc.date.submitted | 2017-07-08 | |
| dc.identifier.citation | [1] V.V.Acharya, S.R.Das, and R.K.Sundaram. Pricing credit derivatives with rating transitions. Financial Analysts Journal, 58(3):28–44, 2002.
[2] E. I. Altman and D. L. Kao. Corporate bond rating drift: An examination of credit quality rating changes over time. Technical report, CFA Institute, 1991. [3] L. V. Carty and J. S. Fons. Measuring changes in corporate credit quality. Journal of Fixed Income, 4(1):27–41, 1994. [4] T. Chordia, R. Roll, and A. Subrahmanyam. Evidence on the speed of convergence to market efficiency. Journal of Financial Economics, 76(2):271–292, 2005. [5] W. G. Cochran. Sampling Techniques. John Wiley & Sons, New York, 2007. [6] A. Damodaran. What is the riskfree rate? a search for the basic building block. Technical report, Stern School of Business, New York University, 2008. [7] S. R. Das and P. Tufano. Pricing credit sensitive debt when interest rates, credit ratings and credit spreads are stochastic. Journal of Financial Engineering, 5(2):161– 198, 1997. [8] M. Davis and A. Etheridge. Louis Bachelier’s Theory of Speculation: The Origins of Modern Finance. Princeton University Press, Princeton, NJ, 2011. [9] E. Derman, I. Kani, and N. Chriss. Implied trinomial tress of the volatility smile. Journal of Derivatives, 3(4):7–22, 1996. [10] A. Doucet, S. Godsill, and C. Andrieu. On sequential Monte Carlo sampling methods for Bayesian filtering. Statistics and Computing, 10(3):197–208, 2000. [11] D.Duffieand K.J.Singleton.Modeling term structures of defaultable bonds.Review of Financial Studies, 12(4):687–720, 1999. [12] P.H.Dybvig and S.A.Ross. Arbitrage.In: John Eatwell, Murray Milgate and Peter Newman, eds. Finance. Palgrave Macmillan, London, 1989. [13] H. Frydman and T. Schuermann. Credit rating dynamics and Markov mixture models. Journal of Banking & Finance, 32(6):1062–1075, 2008. [14] J. E. G´omez-Gonz´alez and N. M. Kiefer. Evidence of non-Markovian behavior in the process of bank rating migrations. Cuadernos de Econom´ıa, 46(133):33–50, 2009. [15] M. H. Hansen, W. N. Hurwitz, and W. G. Madow. Sample Survey Methods and Theory. John Wiley & Sons, New York, 1953. [16] W. K. Hastings. Monte Carlo sampling methods using markov chains and their applications. Biometrika, 57(1):97–109, 1970. [17] J. C. Hull. Options, Futures, and Other Derivatives (8th Edition). Prentice Hall, Boston, 2011. [18] R. E. Kass, B. P. Carlin, A. Gelman, and R. M. Neal. Markov chain Monte Carlo in practice: a roundtable discussion. American Statistician, 52(2):93–100, 1998. [19] O. Knill. Probability and Stochastic Processes with Applications. Overseas Press, New Delhi, 2009. [20] S.Kotz, N.Balakrishnan, and N.L.Johnson. Continuous Multivariate Distributions, Models and Applications. John Wiley & Sons, New York, 2004. [21] D. Lando. On Cox processes and credit risky securities. Review of Derivatives Research, 2(2-3):99–120, 1998. [22] A. Lucas, A. A. Monteiro, and G. V. Smirnov. Nonparametric estimation for nonhomogeneous semi-Markov processes: An application to credit risk. Technical report, Tinbergen Institute, Amsterdam, 2006. [23] D. J. Lucas and J. G. Lonski. Changes in corporate credit quality 1970–1990. Journal of Fixed Income, 1(4):7–14, 1992. [24] G. Manso, B. Strulovici, and A. Tchistyi. Performance-sensitive debt. Review of Financial Studies, 23(5):1819–1854, 2010. [25] T. Minka. Estimating a Dirichlet distribution. Technical report, Department of Electrical Engineering and Computer Science, MIT, 2000. [26] P. G. Moschopoulos. The distribution of the sum of independent gamma random variables. Annals of the Institute of Statistical Mathematics, 37(1):541–544, 1985. [27] K. Nishiguchi, H. Kawai, and T. Sazaki. Capital allocation and bank management based on the quantification of credit risk. Economic Policy Review, 4(3):83–94, 1998. [28] W.P.Poonand M.Firth. Are unsolicited credit ratings lower? International evidence from bank ratings. Journal of Business Finance & Accounting,32(9-10):1741–1771, 2005. [29] A.Shleifer and R.W.Vishny. The limits of arbitrage. Journal of Finance,52(1):35– 55, 1997. [30] S. E. Shreve. Stochastic Calculus for Finance II: Continuous-Time Models. Springer, New York, 2004. [31] T. A. Snijders. Markov chain Monte Carlo estimation of exponential random graph models. Journal of Social Structure, 3(2):1–40, 2002. [32] P. R. Tadikamalla. Computer generation of gamma random variables—II. Communications of ACM, 21(11):925–928, 1978. [33] J. Tennant, K. Emery, and R. Cantor. Corporate one-to-five-year rating transition rates. Technical report, Moody’s Investor Services, 2008. [34] D. Vazza and N. Kraemer. 2015 annual global corporate default study and rating transitions. Technical report, Global Fixed Income Research, Standard & Poor’s, 2015. [35] C.-J.Wang,T.-S.Dai,and Y.-D.Lyuu. Evaluating corporate bonds with complicated liability structures and bond provisions. European Journal of Operational Research, 237(2):749–757, September 1, 2014. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/59229 | - |
| dc.description.abstract | 信用連結債券 (CSN) 是一種浮動收益債券與信用違約互換相結合的 信用衍生產品，Acharya，Das 和 Sundaram 提出可計算在不同信用評等之下 CSN 價格的定價模型。此模型使用的是固定信用評等轉移矩陣。其中信用評等轉移矩陣裡的元素代表的是不同信用評等之間的轉移機率。然而，在市場中信用評等的轉移機率並非定值。這篇論文主要探討的是轉移機率的不確定性對於 CSN 價格造成的差異及影響，進而提出一個基於非固定信用評等轉移矩陣來定價的模型。Acharya 等人提出之模型的複雜度為指數時間。這篇論文使用蒙地卡羅演算法來降低其時間複雜度。 | zh_TW |
| dc.description.abstract | A credit-sensitive note (CSN) is a corporate coupon bond linked to the credit rating of the corporation. Acharya, Das and Sundaram present a model to price CSNs of different rating classes. Their model uses a fixed credit rating transition matrix whose elements are the probabilities of rating transitions. However, the transition probabilities should not be constant. Uncertainty in the transition probabilities will change CSN’s prices. To study the difference, the thesis proposes an approach to incorporate a non-constant credit rating transition matrix into Acharya et al.’s model. The time complexity of Acharya et al.’s model is exponential. The thesis proposes a method to reduce the time complexity with Monte Carlo simulation. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-16T09:18:18Z (GMT). No. of bitstreams: 1 ntu-106-R04922059-1.pdf: 876926 bytes, checksum: 718071a2be623bdaa873baf88854cdca (MD5) Previous issue date: 2017 | en |
| dc.description.tableofcontents | Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v
List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xii Chapter 1: Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.1 Credit Rating and Its Transitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Our approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.3 Basic Concepts and Terminologies . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.3.1 Stochastic Process and Martingale . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.3.2 Risk-Free Rate and Spread . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.3.3 Arbitrage-Free Pricing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1.4 Structures of Thesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Chapter 2: The ADS Model and Its Extension . . . . . . . . . . . . . . . . . . . . . 7 2.1 Equations and Descriptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.2 Lattice Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 2.3 A Corrected Algorithm for the ADS Model . . . . . . . . . . . . . . . . . . . . 12 2.4 The Role of a Dynamic Credit Rating Transition Matrix . . . . . . . . . . 16 Chapter 3: Our New Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 3.1 The Dirichlet Distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 3.1.1 Introduction to the Dirichlet Distribution . . . . . . . . . . . . . . . . . . . . . 19 3.1.2 The Concentration Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 3.2 Monte Carlo Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 3.2.1 Introduction to Monte Carlo Simulation . . . . . . . . . . . . . . . . . . . . . . 22 3.2.2 Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 Chapter 4: Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 4.1 Comparison of Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 4.2 Numerical Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 4.3 Time Complexity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 Chapter 5: Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 Appendix A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 Appendix B . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 | |
| dc.language.iso | en | |
| dc.title | 動態信用評等轉移矩陣與選擇權定價 | zh_TW |
| dc.title | A Pricing Model with Dynamic Credit Rating Transition Matrix | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 105-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 趙坤茂(Kun-Mao Chao),蔡芸琤(Yun-Cheng Tsai),張經略(Ching-Luei Chang) | |
| dc.subject.keyword | 信用評等,轉移矩陣,衍伸性商品,定價模型, | zh_TW |
| dc.subject.keyword | Credit rating,transition matrix,derivatives,pricing model, | en |
| dc.relation.page | 42 | |
| dc.identifier.doi | 10.6342/NTU201701354 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2017-07-10 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 資訊工程學研究所 | zh_TW |
| 顯示於系所單位： | 資訊工程學系 | |
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