English  |  正體中文  |  简体中文  |  Post-Print筆數 : 20 |  Items with full text/Total items : 90058/119991 (75%)
Visitors : 24150589      Online Users : 1585
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/36879

    Title: 以重複事件模型分析破產機率
    Recurrent Event Analysis of Bankruptcy Probability
    Authors: 曾士懷
    Tseng,Shih Huai
    Contributors: 謝淑貞
    Shieh,Shwu Jane
    Tseng,Shih Huai
    Keywords: 重複事件
    Recurrent Event
    Bankruptcy Probability
    Date: 2007
    Issue Date: 2009-09-18 20:01:11 (UTC+8)
    Abstract: Bankruptcy prediction has been of great interest to academics in the fields of accounting and finance for decades. Prior literatures focus mostly on investigating the covariates that lead to bankruptcy. In this thesis, however, we extend the issue of interest to what are the possible covariates that cause significant jumps in bankruptcy probability for a company.
    We consider the BSM-probability measure examined by Hillegeist, Keating, Cram, and Lundsedt (2004) to help us calculate the variation in bankruptcy probabilities for companies. In addition, recurrent event data analysis is applied to explore these jumps in bankruptcy intensity.
    By investigating the S&P500 constituents with sample consists of 343 S&P500-listed companies and 17,836 quarter observations starting from 1994 to 2007, we find that, in three of our models, all of these six covariates are negatively related to the recurrences of event that a company will suffer significant jumps in its bankruptcy probability during the next quarter. Additionally, macroeconomic covariates have greater explanatory power as factors affecting the probability of these jumps, while company-specific covariates contribute less to these recurrences of events. In comparison, we conduct another estimation based on the observation of slight increases in bankruptcy probability for companies. Contrary to what we find on the prior dataset, our empirical results suggest the factors that evoke these events are less prominent and their influences on the event recurrence are mixed.
    Reference: Altman, E.I., 1968. Financial ratios, discriminant analysis, and the prediction of corporate bankruptcy. Journal of Finance 23, 589-609
    Beaver, B., 1966. Financial ratios as predictors of failure. Journal of Accounting Research Autumn, 91–101, Empirical Research in Accounting: Selected Studies, Supplement.
    Beaver, B., 1968a. Alternative accounting measures as predictors of failure. Accounting Review January, 113–122.
    Beaver, B., 1968b. Market prices, financial ratios, and the prediction of failure. Journal of Accounting Research Autumn, 170–192.
    Beaver, W., McNichols, M., Rhie, J.-W., 2005. Have financial statements become less informative?—Evidence from the Ability of Financial Ratios to Predict Bankruptcy. Review of Accounting Studies 10, 93–122.
    Bharath, S., Shumway, T., 2004. Forecasting default with the KMV-merton model. Working paper, University of Michigan.
    Crosbie, P.J., Bohn, J.R., 2002. Modeling default risk. Technical Report, KMV, LLC.
    Das, S.R., Duffie, D., Kapadia, N., Saita, L., 2006. Common failings: how corporate defaults are correlated, Journal of Finance.
    Duffie, D., Lando, D., 2001. Term structures of credit spreads with incomplete accounting information. Econometrica 69, 633–664.
    Hillegeist, S.A., Keating, E.K., Cram, D.P., Lundstedt, K.G., 2004. Assessing the Probability of Bankruptcy. Review of Accounting Studies 9, 5–34.
    Jones, F., 1987. Current techniques in bankruptcy prediction. Journal of Accounting Literature 6, 131–164.
    Kealhofer, S., 2003. Quantifying credit risk I: default prediction. Financial Analysts Journal, January–February, 30–44.
    Lin, D. Y., and Wei, L. J., 1989. The robust inference for the Cox proportional hazards model. Journal of the American Statistical Association.
    McDonald, C.G., Van de Gucht, L.M., 1999. High-yield bond default and call risks. Review of Economics and Statistics 81, 409–419.
    Ohlson, J., 1980. Financial ratios and the probabilistic prediction of bankruptcy. Journal of Accounting Research 19, 109–131.
    Pena, E. A., Hollander, M., 2004. Models for recurrent events in reliability and survival analysis. Kluwer Academic Publishers, 105-123
    Pena, E. A., Slate, E. H., and Gonzalez, J. R., 2006. Semiparametric inference for a general calss of models for recurrent events. Journal of Statistical Planning and Inference, 137, 1727-1747
    Pesaran, M.H., Schuermann, T., Treutler, B.-J., Weiner, S.M., 2006. Macroeconomic dynamics and credit risk: a global perspective. Journal of Money, Credit, and Banking 38, 1211–1262.
    Ripatti, S., and Palmgren, J., 2000. Estimation of multivariate frailty models using penalized partial likelihood. Biometrics, 1016-1022
    Shumway, T., 2001. Forecasting bankruptcy more accurately: a simple hazard model. Journal of Business 74, 101–124.
    Therneau, T. M., and Hamilton, S. A., 1997. rhDNase as an example of recurrent event analysis. Statistics in Medicine 16, 2029-2047
    Therneau, T. M., and Grambsch, P. M., 2000. Modeling survival data: extending the Cox model
    Rondeau, V., Commenges, D., and Joly, P., 2003. Maximun penalized likihood estimation in a gamma-frailty model. Lifetime Data Analysis 9, 139-153
    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, 1065-1073
    Description: 碩士
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0953510131
    Data Type: thesis
    Appears in Collections:[國際經營與貿易學系 ] 學位論文

    Files in This Item:

    File Description SizeFormat
    013101.pdf40KbAdobe PDF883View/Open
    013102.pdf12KbAdobe PDF720View/Open
    013103.pdf21KbAdobe PDF831View/Open
    013104.pdf23KbAdobe PDF913View/Open
    013105.pdf69KbAdobe PDF1187View/Open
    013106.pdf45KbAdobe PDF1013View/Open
    013107.pdf172KbAdobe PDF792View/Open
    013108.pdf19KbAdobe PDF1127View/Open

    All items in 政大典藏 are protected by copyright, with all rights reserved.

    社群 sharing

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback