Please use this identifier to cite or link to this item:
標題: 具脆弱相關之違約模型 - 台灣上市櫃公司之應用
Default Model with Frailty : An Application to Public Firm on Taiwan Stock Market
作者: 黃皇銘
Huang, Huang-Mine
關鍵字: 脆弱因子;frailty;馬可夫鏈蒙地卡羅;違約強度;縮減式模型;MCMC;default intensity;reduced-form model
出版社: 財務金融系所
引用: Altman, E. I., Haldeman, G. G., and Narayanan, P. (1977), “Zeta analysis: A new model to identify the bankruptcy risk of corporations”, Journal of Banking and Finance, 1, 29–54. Altman, Edward I. (1968), “Financial ratios, discriminant analysis and the prediction of corporate bankruptcy”, Journal of Finance, 22, 589–609. Amemiya, T. (1985), “Advanced econometrics”, Harvard University Press, Cambridge, MA. Anderson, Mike (2010), “Contagion and excess correlation in credit default swaps”,George Mason University. Aoyama, H., Nagahara, Y., Okazaki, M. P., Souma, W.,Takayasu, H., and Takayasu,M. (2000), “Paretos law for income of individuals and debt of bankrupt companies”, Fractals, 8(3), 293–300. Beaver, William H. (1966), “Financial ratios as predictors of failure”, Journal of Accounting Research, 4, 71–111. Black, F. and Scholes, M. (1973), “The pricing of options and corporate liabilities”, Journal of Political Economy, 81, 637–654. Das, Sanjiv R., Freed, Laurence, Geng, Gary, and Kapadia, Nikunj (2006), “Corre- lated default risk”, The Journal of Fixed Income, 1–26. Duan, J.C. (2010), “Clustered defaults”, National University of Singapore (NUS) - Business School and Risk Management Institute. Duffie, D., Das, S., Kapadia, N., and Saita, L. (2007), “Common failings: How corporate defaults are correlated”, The Journal of Finance, 62, 93–118. Duffie, D., Eckner, A., Horel, G., and Saita, L. (2009), “Frailty correlated default”, The Journal of Finance, 64, 2089–2123. Duffie, D. and Singleton, Kenneth J. (1999), “Modeling term structures of default- able bonds”, The Review of Financial Studies, 12, 687–720. Focardi, S. M. and Fabozzi, F. J. (2005), “An autoregressive conditional duration model of credit-risk contagion”, The Journal of Risk Finance, 6(3), 208–225. Frey, R. and Bachkaus, J. (2003), “Interacting defaults and counterparty risk: A markovian approach”, Working paperpaper, University of Leipzig, Leipzig. Gelfand, A. E. and Smith, A. F. M. (1990), “Sampling-based approaches to calcu- lating marginal densities”, Journal of the American Statistical Association, 85, 398–409. Geman, Stuart and Geman, Donald (1984), “Stochastic relaxation, gibbs distribu- tions, and the bayesian restoration of images”, IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI-6, No. 6, 721–741. Giesecke, K. and Weber, S. (2004), “Cyclical correlations, credit contagion, and portfolio losses”, Journal of Banking and Finance, 28(12), 3009–3036. Halaj, G. (2006), “Contagion effect in banking system - measures based on ran- domised loss scenarios”, MPRA Paper, 525. Hastings, W. K. (1970), “Monte carlo sampling methods using markov chains and their applications”, Biometrika, 57, 97–109. Horst, U. (2007), “Stochastic cascades, credit contagion, and large portfolio losses”, Journal of Economic Behavior and Organization, 63(1), 25–54. Jarrow, Robert A. and Turnbull, Stuart M. (1995), “Pricing derivatives on financial securities subject to credit risk”, The Journal of Finance, 50, 53–85. Jarrow, Robert A. and Yu, Fan (2001), “Counterparty risk and the pricing of de- faultable securities”, The Journal of Finance, 56, 1765–1799. Kraft, H. and Steffensen, M. (2006), “Bankruptcy, counterparty risk, and conta- gion”, FRU Working Papers. Lando, D. (1998), “On cox proceses and credit risky securities”, Review of Deriva- tives Research, 2, 99–120. Martin, D. (1977), “Early warning of banking failure”, Journal of Banking and Finance, 249–276. Merton, Robert C. (1974), “On the pricing of corporate debt: The risk structure of interest rates”, Journal of Finance, 29. Neal, Radford (1993), “Probabilistic inference using markov chain monte carlo”, Computer and Information Science, 62. Ohlson, James A. (1980), “Financial ratios, discriminant analysis and the prediction of corporate bankruptcy”, Journal of Accounting Research, 18, 109–131. Pesaran, M. H. and Pick, A. (2004), “Econometric issues in the analysis of conta- gion”, Working paper, University of Cambridge, Cambridge, UK. Shumway, Tyler (2001), “Forecasting bankruptcy more accurately: A simple hazard model”, Journal of Business, 74, 101–124. Vassalou, M. and Xing, Y (2004), “Default risk in equity returns”, The Journal of Finance, 59, 831–868. Zmijewski, Mark E. (1984), “Methodological issues related to the estimation of financial distress prediction models”, Journal of Accounting Research, 22, 59–82.
本文首先介紹財務預警模型的主要類型, 其中包括評分模型、 結構式模型以及縮減式
模型, 接著是過去文獻對於違約相關性的探討。 最後根據 Duffie et al. (2009) 所建構之
脆弱相關違約強度模型, 對台灣上市櫃公司進行預測其違約機率。 該模型利用了馬可夫鏈
蒙地卡羅法產生脆弱因子, 其目的為有效捕捉公司間連續大規模違約情形, 即違約叢聚現
象, 以便能夠更精確預測出違約機率, 並且對該模型進行是否在台灣上市櫃公司有效之檢
定。 最後本研究的實證結果顯示, 脆弱相關違約強度模型並無法有效捕捉台灣上市櫃公司

This paper first introduces the main types of financial warning models, includ-
ing Credit Scoring Models, Structural models and Reduced form models, and the
literature of default correlation. Finally, according to Duffie et al. (2009) we used
frailty-intensity model to predict the default probability of public companies in Tai-
wan. The model uses a Markov chain Monte Carlo method to generate frailty aiming
to capture the default clustering so that we are able to predict the probability of
default more precisely. And we make a test on if this model is applicable to the
publicly-traded firms in Taiwan later. At last, the empirical results of this study
show that frailty-intensity model cannot effectively predict public companies for
default clustering situation.
其他識別: U0005-1807201219205400
Appears in Collections:財務金融學系所

Show full item record

Google ScholarTM


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.