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題名 台灣上市上櫃公司發行可轉換債券之存活分析研究
Survival analysis for convertible bonds of listed companies in Taiwan作者 戴誠蔚 貢獻者 陳麗霞
戴誠蔚關鍵詞 可轉換公司債
存活分析
Cox模式
再發事件
分層模式
convertible bonds
survival analysis
Cox model
recurrent events
stratified model日期 2010 上傳時間 5-九月-2013 15:13:32 (UTC+8) 摘要 可轉換公司債為複合式證券，除了具有債券性質外，並給予持有者於債券流通期間內行使轉換為股票之權利。以存活分析方法探討可轉債之研究尚屬少見，本論文乃以台灣上市櫃公司發行之5年期可轉債為研究資料，先整理出與公司經營有關的變數，再分別以Cox模式與再發事件之兩種邊際模型(marginal model)：A-G (Anderson-Gill) 模式、PWP-TT (Prentice-Williams-Petersen)模式為研究分析方法，探討可轉債之流通時間及大量交易時間的問題。本論文並將可轉債分類為債券類型、混合類型和權益類型，且由於不同類型可轉債之流通時間有所差異，因此以其為分層條件加入模式中進行分析。研究結果發現，資產總額、總負債率、TCRI評等及董監持股率等變數，具有顯著解釋可轉債流通時間的能力，可見公司財務負債狀況與穩定性與流通期間有關；而最高差價(當月最高股價與轉換價之相對差價)、長期負債率、總負債率及股價報酬率等變數，則可顯著解釋大量交易的發生時間，表示公司財務負債狀況與股價利潤差與大量交易發生之快慢有關，其中資產總額、最高差價、TCRI評等及股價報酬率之係數均顯著為正，長期負債率、總負債率及董監持股率之係數則顯著為負。由於平均表現之存活曲線與經驗存活曲線相當接近，以Kolmogorov-Smirnov檢定多無顯著差異，顯示這些模式有不錯的配適能力；至於對個別公司估計出之存活曲線，則或有與經驗存活曲線相差較多的現象，顯示所建立的模式可對個別公司提供可轉債即將結束流通或發生大量交易之預警。
Convertible bonds are hybrid securities that possess the properties of bonds and the right to convert bonds into shocks. Few articles employed survival analysis to analyze the characteristics of convertible bonds. To investigate the effects of the issuer’s financial information to the duration of circulation and the timing of the massive trading about convertible bonds, Taiwan’s 5-year convertible bonds were collected, and three methods of survival analysis were employed：Cox model、A-G (Anderson-Gill) model and PWP-TT(Prentice-Williams-Petersen) model. We classified convertible bonds as debt-like, equity-like, and hedge-like, and then make the classification as a stratification condition later. In summary, total Assets, total debt ratio, TCRI, and the proportion of holding share in supervisors and directors are significant variables on circulation period of convertible bonds. Apparently, the extent of debt and financial stability of issuers have significant effects on circulation period; the difference between stock price and conversion price, long-term debt ratio, total debt ratio and stock return rate contribute significantly on the timing of massive trading of convertible bonds. While the extent of debt and the return of stock hasten the hazard of the timing of massive trading. Furthermore, there are no significant differences between the survival curves evaluated at the average performance levels and the corresponding empirical survival curves, according to the results of Kolmogorov-Smirnov test. However, the differences between individual survival probabilities and overall empirical survival probabilities might be large, which indicates that the models incorporate companies’ performance overtime may provide a warning message for the termination of circulation or the timing of massive trading for a particular convertible bond.參考文獻 [中文文獻][1]王麗芬(民95).再發事件之存活分析之研究，政治大學統計研究所碩士 論文。[2]洪秀莉(民95).台灣上市公司可交易公司債發行動機之研究—二階段估 計法之應用，朝陽科技大學財務金融研究所碩士論文。[3]郭志安(民86).以Cox 模型建立財務危機預警模式,逢甲大學統計與精算 研究所碩士論文。[4]陳志豪(民93).Cox模式有時間相依共變數下預測問題之研究，政治大學 統計研究所碩士論文。[5]陳俞方(民99).公司治理與可轉債交易策略，中央大學財務金融學系碩 士論文。[6]陳家豪(民92).存活分析方法應用於汽車貸款客戶信用風險管理之研 究，成功大學統計學系碩士班碩士論文。[7]張輔仁(民97).時間相依共變數之雙重存活時間分析—台灣愛滋病病患 存活時間與 CD4 / CD8 比值關係之案例研究，中央大學統計研究所碩 士論文。[8]蔡政哲(民92).公司財務特質、交易機率與可交易公司債融資決策之研 究，中原大學國際貿易學系碩士學位論文。[9]楊朝成、陳宏銓、劉任昌 (民95)。臺灣可交易公司債市場異常報酬之 研究。朝陽商管評論，5，2，1-20。[英文文獻][1]Altman, E.I. (1968). Financial ratios, discriminant analysis, and the prediction of corporate bankruptcy. Journal of Finance, 23, pp.589-609.[2]Andersen, P.K. and Gill, R.D. (1982). Cox’s regression model for counting processes: A large sample study. Annals of Statistics 10, 1100-1120.[3]Beaver,W.H.,(1966). Financial Ratios as Predictors of Failure, Journal of Accounting Researck, Vol. 4,71-102.[4]Black, F., and Scholes, S.,(1973). The pricing of options and corporate liabilities. Journal of Political Economy, 81: 637-659.[5]Boher, J. and Cook, R.J. (2004). Implications of model misspecification among robust test for recurrent events. Working Paper Series and Technical Reports, 2005.05. [6]Box-Steffensmeier, J.M., and DeBoef, S. (2006). Repeated event survival models: The conditional frailty model. Statistics in Medicine,25, pp.3518-3533.[7]Brennan, M. J., and Schwartz, E. S., (1977). Convertible bonds: Valuation and optimal strategies for call and conversion.Journal of Finance, 32(5): 1699-1715.[8]Breslow, N.E. (1974). Covariance analysis of censored survival data, Biometrics, 30, pp.89-99.[9]Cook, R.J., Lawless, J.F. (2007). The Statistical Analysis of Recurrent Events. Springer.[10]Efron, B. (1977). The efficiency of Cox’s likelihood function for censored data. Journal of the American Statistical Association, 72, pp.557-565.[11]Green, R. C.,(1984). Investment incentives, debt and warrants. Journal of Financial Economics 13(1): 115-136. [12]Hoffmeister, J.R.,(1977). Use of convertible debt in the early 1970s: A reevaluation of corporate motives. Quarterly Review of Economics and Business, 17:23-32. [13]Kaplan, E.L. and Meier, P. (1958). Nonparametric estimation from iIncomplete observations. Journal of the American Statistical Association, 53, pp.457-481.[14]Kelly, P.J., Lim, L.L. (2000). Survival analysis for recurrent event data: an application to childhood infectious disease. Statistics in Medicine, 19(1):13-33.[15]King, R.,(1986). Convertible bond valuation: An empirical test. Journal of Financial Research, 9(1):53-69. [16]Klein, J.P., Moeschberger, M.L. (1997). Survival Analysis Techniques for Censored and Truncated Data. Springer.[17]Lane, W.R., Looney, S.W., and Wansley, J.W. (1986). An application of the Cox proportional hazards model to bank failure. Journal of Banking and Finance, 10, pp.511- 531.[18]Lawless, J.F. (1995). The analysis of recurrent events for multiple subjects. Journal of the Royal Statistical Society. Series C (Applied Statistics), 44(4), pp.487-498.[19]Lee, E. W., Wei, L. J., and Amato, D. A. (1992). Cox- type tegression analysis for large numbers of small groups of correlated failure time observations. In: Survival Analysis: State of the Art (J.P. Klein, P.K. Goel, Eds.),237-247. Dordrecht: Kluwer Academic Publishers. [20]Lewis, C., Rogalski, R., and Seward, J. (2003). Industry conditions, growth opportunities and market reactions to convertible debt financing decisions? Journal of Banking and Finance, 28, 5-27.[21]Merton, R. C., (1974). On the pricing of corporate debt: The risk structure of interest rates. Journal of Finance, 29(2): 449-469.[22]Ohlson, J. (1980). Financial ratios and the probabilistic prediction of bankruptcy. Journal of Accounting Research, 18, pp.109-131.[23]Prentice, R.L., Williams, B.J., and Peterson, A.V. (1981). On the regression analysis of multivariate failure time data. Biometrika, 68, pp.373-379.[24]Wei, L.J., Lin, D.Y., and Weissfeld, L. (1989). Regression analysis of multivariate incomplete failure time data by modeling marginal distributions, Journal of the American Statistical Association, 84(408):1065-1073. 描述 碩士
國立政治大學
統計研究所
98354019
99資料來源 http://thesis.lib.nccu.edu.tw/record/#G0098354019 資料類型 thesis dc.contributor.advisor 陳麗霞 zh_TW dc.contributor.author (作者) 戴誠蔚 zh_TW dc.creator (作者) 戴誠蔚 zh_TW dc.date (日期) 2010 en_US dc.date.accessioned 5-九月-2013 15:13:32 (UTC+8) - dc.date.available 5-九月-2013 15:13:32 (UTC+8) - dc.date.issued (上傳時間) 5-九月-2013 15:13:32 (UTC+8) - dc.identifier (其他 識別碼) G0098354019 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/60445 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 統計研究所 zh_TW dc.description (描述) 98354019 zh_TW dc.description (描述) 99 zh_TW dc.description.abstract (摘要) 可轉換公司債為複合式證券，除了具有債券性質外，並給予持有者於債券流通期間內行使轉換為股票之權利。以存活分析方法探討可轉債之研究尚屬少見，本論文乃以台灣上市櫃公司發行之5年期可轉債為研究資料，先整理出與公司經營有關的變數，再分別以Cox模式與再發事件之兩種邊際模型(marginal model)：A-G (Anderson-Gill) 模式、PWP-TT (Prentice-Williams-Petersen)模式為研究分析方法，探討可轉債之流通時間及大量交易時間的問題。本論文並將可轉債分類為債券類型、混合類型和權益類型，且由於不同類型可轉債之流通時間有所差異，因此以其為分層條件加入模式中進行分析。研究結果發現，資產總額、總負債率、TCRI評等及董監持股率等變數，具有顯著解釋可轉債流通時間的能力，可見公司財務負債狀況與穩定性與流通期間有關；而最高差價(當月最高股價與轉換價之相對差價)、長期負債率、總負債率及股價報酬率等變數，則可顯著解釋大量交易的發生時間，表示公司財務負債狀況與股價利潤差與大量交易發生之快慢有關，其中資產總額、最高差價、TCRI評等及股價報酬率之係數均顯著為正，長期負債率、總負債率及董監持股率之係數則顯著為負。由於平均表現之存活曲線與經驗存活曲線相當接近，以Kolmogorov-Smirnov檢定多無顯著差異，顯示這些模式有不錯的配適能力；至於對個別公司估計出之存活曲線，則或有與經驗存活曲線相差較多的現象，顯示所建立的模式可對個別公司提供可轉債即將結束流通或發生大量交易之預警。 zh_TW dc.description.abstract (摘要) Convertible bonds are hybrid securities that possess the properties of bonds and the right to convert bonds into shocks. Few articles employed survival analysis to analyze the characteristics of convertible bonds. To investigate the effects of the issuer’s financial information to the duration of circulation and the timing of the massive trading about convertible bonds, Taiwan’s 5-year convertible bonds were collected, and three methods of survival analysis were employed：Cox model、A-G (Anderson-Gill) model and PWP-TT(Prentice-Williams-Petersen) model. We classified convertible bonds as debt-like, equity-like, and hedge-like, and then make the classification as a stratification condition later. In summary, total Assets, total debt ratio, TCRI, and the proportion of holding share in supervisors and directors are significant variables on circulation period of convertible bonds. Apparently, the extent of debt and financial stability of issuers have significant effects on circulation period; the difference between stock price and conversion price, long-term debt ratio, total debt ratio and stock return rate contribute significantly on the timing of massive trading of convertible bonds. While the extent of debt and the return of stock hasten the hazard of the timing of massive trading. Furthermore, there are no significant differences between the survival curves evaluated at the average performance levels and the corresponding empirical survival curves, according to the results of Kolmogorov-Smirnov test. However, the differences between individual survival probabilities and overall empirical survival probabilities might be large, which indicates that the models incorporate companies’ performance overtime may provide a warning message for the termination of circulation or the timing of massive trading for a particular convertible bond. en_US dc.description.tableofcontents 表目錄.................................................. I圖目錄..................................................II第一章 緒論............................................1 第一節 研究動機與目的.................................1 第二節 研究架構 ......................................2第二章 文獻探討 ........................................3 第一節 可轉換公司債....................................3 第二節 文獻探討........................................7第三章 研究方法........................................12 第一節 預計轉換機率....................................12 第二節 Cox迴歸模式.....................................14 第三節 再發事件之存活分析...............................17第四章 實證分析........................................24 第一節 資料來源........................................24 第二節 敘述統計分析....................................27 第三節 統計估計結果....................................32第五章 結論與建議......................................48參考文獻................................................50附錄....................................................53 zh_TW dc.format.extent 1304546 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/#G0098354019 en_US dc.subject (關鍵詞) 可轉換公司債 zh_TW dc.subject (關鍵詞) 存活分析 zh_TW dc.subject (關鍵詞) Cox模式 zh_TW dc.subject (關鍵詞) 再發事件 zh_TW dc.subject (關鍵詞) 分層模式 zh_TW dc.subject (關鍵詞) convertible bonds en_US dc.subject (關鍵詞) survival analysis en_US dc.subject (關鍵詞) Cox model en_US dc.subject (關鍵詞) recurrent events en_US dc.subject (關鍵詞) stratified model en_US dc.title (題名) 台灣上市上櫃公司發行可轉換債券之存活分析研究 zh_TW dc.title (題名) Survival analysis for convertible bonds of listed companies in Taiwan en_US dc.type (資料類型) thesis en dc.relation.reference (參考文獻) [中文文獻][1]王麗芬(民95).再發事件之存活分析之研究，政治大學統計研究所碩士 論文。[2]洪秀莉(民95).台灣上市公司可交易公司債發行動機之研究—二階段估 計法之應用，朝陽科技大學財務金融研究所碩士論文。[3]郭志安(民86).以Cox 模型建立財務危機預警模式,逢甲大學統計與精算 研究所碩士論文。[4]陳志豪(民93).Cox模式有時間相依共變數下預測問題之研究，政治大學 統計研究所碩士論文。[5]陳俞方(民99).公司治理與可轉債交易策略，中央大學財務金融學系碩 士論文。[6]陳家豪(民92).存活分析方法應用於汽車貸款客戶信用風險管理之研 究，成功大學統計學系碩士班碩士論文。[7]張輔仁(民97).時間相依共變數之雙重存活時間分析—台灣愛滋病病患 存活時間與 CD4 / CD8 比值關係之案例研究，中央大學統計研究所碩 士論文。[8]蔡政哲(民92).公司財務特質、交易機率與可交易公司債融資決策之研 究，中原大學國際貿易學系碩士學位論文。[9]楊朝成、陳宏銓、劉任昌 (民95)。臺灣可交易公司債市場異常報酬之 研究。朝陽商管評論，5，2，1-20。[英文文獻][1]Altman, E.I. (1968). Financial ratios, discriminant analysis, and the prediction of corporate bankruptcy. Journal of Finance, 23, pp.589-609.[2]Andersen, P.K. and Gill, R.D. (1982). Cox’s regression model for counting processes: A large sample study. Annals of Statistics 10, 1100-1120.[3]Beaver,W.H.,(1966). Financial Ratios as Predictors of Failure, Journal of Accounting Researck, Vol. 4,71-102.[4]Black, F., and Scholes, S.,(1973). The pricing of options and corporate liabilities. Journal of Political Economy, 81: 637-659.[5]Boher, J. and Cook, R.J. (2004). Implications of model misspecification among robust test for recurrent events. Working Paper Series and Technical Reports, 2005.05. [6]Box-Steffensmeier, J.M., and DeBoef, S. (2006). Repeated event survival models: The conditional frailty model. Statistics in Medicine,25, pp.3518-3533.[7]Brennan, M. J., and Schwartz, E. S., (1977). Convertible bonds: Valuation and optimal strategies for call and conversion.Journal of Finance, 32(5): 1699-1715.[8]Breslow, N.E. (1974). Covariance analysis of censored survival data, Biometrics, 30, pp.89-99.[9]Cook, R.J., Lawless, J.F. (2007). The Statistical Analysis of Recurrent Events. Springer.[10]Efron, B. (1977). The efficiency of Cox’s likelihood function for censored data. Journal of the American Statistical Association, 72, pp.557-565.[11]Green, R. C.,(1984). Investment incentives, debt and warrants. Journal of Financial Economics 13(1): 115-136. [12]Hoffmeister, J.R.,(1977). Use of convertible debt in the early 1970s: A reevaluation of corporate motives. Quarterly Review of Economics and Business, 17:23-32. [13]Kaplan, E.L. and Meier, P. (1958). Nonparametric estimation from iIncomplete observations. Journal of the American Statistical Association, 53, pp.457-481.[14]Kelly, P.J., Lim, L.L. (2000). Survival analysis for recurrent event data: an application to childhood infectious disease. Statistics in Medicine, 19(1):13-33.[15]King, R.,(1986). Convertible bond valuation: An empirical test. Journal of Financial Research, 9(1):53-69. [16]Klein, J.P., Moeschberger, M.L. (1997). Survival Analysis Techniques for Censored and Truncated Data. Springer.[17]Lane, W.R., Looney, S.W., and Wansley, J.W. (1986). An application of the Cox proportional hazards model to bank failure. Journal of Banking and Finance, 10, pp.511- 531.[18]Lawless, J.F. (1995). The analysis of recurrent events for multiple subjects. Journal of the Royal Statistical Society. Series C (Applied Statistics), 44(4), pp.487-498.[19]Lee, E. W., Wei, L. J., and Amato, D. A. (1992). Cox- type tegression analysis for large numbers of small groups of correlated failure time observations. In: Survival Analysis: State of the Art (J.P. Klein, P.K. Goel, Eds.),237-247. Dordrecht: Kluwer Academic Publishers. [20]Lewis, C., Rogalski, R., and Seward, J. (2003). Industry conditions, growth opportunities and market reactions to convertible debt financing decisions? Journal of Banking and Finance, 28, 5-27.[21]Merton, R. C., (1974). On the pricing of corporate debt: The risk structure of interest rates. Journal of Finance, 29(2): 449-469.[22]Ohlson, J. (1980). Financial ratios and the probabilistic prediction of bankruptcy. Journal of Accounting Research, 18, pp.109-131.[23]Prentice, R.L., Williams, B.J., and Peterson, A.V. (1981). On the regression analysis of multivariate failure time data. Biometrika, 68, pp.373-379.[24]Wei, L.J., Lin, D.Y., and Weissfeld, L. (1989). Regression analysis of multivariate incomplete failure time data by modeling marginal distributions, Journal of the American Statistical Association, 84(408):1065-1073. zh_TW
