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    Title: 違約機率與違約損失率相關之下的CreditRisk+模型
    The CreditRisk+ Model with the Correlated PD and LGD
    Authors: 陳漢鐘
    Chen, han jhong
    Contributors: 鍾經樊
    Chung,ching fan
    陳漢鐘
    Chen,han jhong
    Keywords: CreditRisk+
    風險值
    違約相關性
    損失分配
    Date: 2009
    Issue Date: 2016-05-09 16:53:43 (UTC+8)
    Abstract: 本文修改信用風險商業化模型CreditRisk+, 以蒙地卡羅模擬的方式探
    討若修改其中的兩個假設, 將對組合損失分配帶來何種影響。一、本文認
    為不同產業間的違約不是獨立, 而應具有相關性。我們以4大產業的季違
    約廠商數為應變數, 景氣因子作為自變數估計各產業違約情形與總體經
    濟間的關係。二、個別公司違約損失率是一與違約機率相關的隨機變數,
    而不再是常數。本文提出利用財報試算各公司、產業LGD 的方法, 並假
    設產業違約損失率為Beta 隨機變數, 而其中的參數會受總體因子影響。
    如此一來, 產業間的違約機率與違約損失率因總體因子的關係不再獨立,
    於是個別公司的違約機率、違約損失率將具有相關性。
    最後, 我們以台灣上市櫃公司中同時具有TCRI 評等資訊以及財報
    的561家公司作為虛擬的放款組合, 模擬在不同總體條件下的信用損失分
    配。結果顯示, 在考慮了產業間違約相關性後的損失將大於產業獨立時的
    損失, 而進一步納入違約機率和損失率的相關性後, 放款組合的預期損失
    與風險值也隨之提高。
    Reference: 沈大白、敬永康、蔡嘉倩(2003), “運用TEJ 資料庫計算台灣債務償還率(回收率) 之研究”, 《金融業風險管理實證研究論文集》。
    沈中華、林昆立(2007), “台灣金融機構適足資本之壓力測試”, 《金融風險管理季刊》, 3(1), 27–61。
    沈中華、張家華(2005), “產業違約率與景氣循環”, 《金融風險管理季刊》,1(4), 91–105。
    沈中華(2005), “資產組合風險預測”, 《金融風險管理季刊》, 1(1), 102–110。
    徐中敏(2004), “國內企業戶違約損失率研究”, 《信用資訊》, 10, 25–39。
    黃嘉龍(2008), “組合資產之信用風險管理:理論與應用”, 博士論文, 國立臺灣大學經濟學系。
    Acharya, V. V., S. Bharath and A. Srinivasan (2007), “Does industrywide
    distress affect defaulted firms? Evidence from creditor recoveries”,Journal of Financial Economics, 85(3), 787–821.
    Altman, E. I. (1968), “Financial ratios, discriminant analysis and the prediction of corporate bankruptcy”, Journal of Finance, 23(4), 589–609.
    Altman, E. I., B. Brady, A. Resti, and A. Sironi (2005), “The link between default and recovery rates: Theory, empirical evidence, and implications”,Journal of Business, 78(6), 2203–2228.
    Avesani, R. G., K. Liu, A. Mirestean, and J. Salvati (2006), “Review and implementation of credit risk models of the financial sector assessment program”, IMF Working Paper.
    Bluhm, C., L. Overbeck and C. Wagner (2003), An introduction to credit risk modeling.
    B¨urgisser, P., A. Kurth, A. Wagner, and M. Wolf (1999), “Integratingcorrelations”, Risk, 12(7), 57–60.
    Crouhy, M., D. Galai and R. Mark (2000), “A comparative analysis of
    current credit risk models”, Journal of Banking and Finance, 24(1-2), 59–117.
    Giese, G. (2003), “Enhancing creditrisk+”, Risk, 16(4), 73–77.
    Giesecke, K. (2004), “Correlated default with incomplete information”, Journal of Banking and Finance, 28(7), 1521–1545.
    Gordy, M. B. (2002), “Saddlepoint approximation of creditrisk+”, Journal of Banking and Finance, 26(7), 1335–1353.
    Gundlach, M. and F. Lehrbass (2004), CreditRisk+ in the Banking Industry.
    Gupton, G. M. (2005), “Advancing loss given default prediction models:How the quiet have quickened”, Economic Notes, 34(2), 185–230.
    Jokivuolle, E. and S. Peura (2000), “A model for estimating recovery rates and collateral haircuts for bank loans”, Working Paper.
    Kupiec, P. (2007), “Estimating recovery discount rates: A methodological note”, Journal of Risk Management in Financial Institutions, 1(1), 17–24.
    Miu, P. and B. Ozdemir (2005), “Basel Requirement of Downturn LGD: Modeling and Estimating PD and LGD Correlations”, Journal of Credit Risk, 2, 43–68.
    Panjer, H. H. and G. E. Willmot (1992), Insurance Risk Models, Society of Actuaries.
    Schuermann, T. (2004), “What do we know about loss given default?”, Working Paper.
    Wilde, T. (1997), “Creditrisk+: A credit risk management framework”, Technical report, Credit Suisse Financial Products.
    Wilson, T. (1998), “Portfolio credit risk”, Economic Policy Review, 4(3), 71–82.
    Description: 碩士
    國立政治大學
    經濟學系
    95258014
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0095258014
    Data Type: thesis
    Appears in Collections:[經濟學系] 學位論文

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