IDEAS home Printed from https://ideas.repec.org/p/ioe/doctra/336.html
   My bibliography  Save this paper

La Predicción de la Insolvencia de Empresas Chilenas

Author

Listed:
  • Felipe Zurita

    (Instituto de Economía. Pontificia Universidad Católica de Chile.)

Abstract

Este trabajo compara modelos de inestabilidad financiera de naturaleza estadística y basados en la teoría de opciones, para el conjunto de sociedades anónimas abiertas chilenas. Los modelos estadísticos tienen un ajuste adecuado, aunque la peculiar historia de las quiebras en el período considerado, a saber, su aglomeración al inicio, pone en duda su utilidad como herramienta predictiva. En el segundo caso, en cambio, el promedio de probabilidades de quiebra muestra una alta correlación con indicadores de riesgo bancarios, y los precede hasta en tres trimestres. En suma, este primer esfuerzo de medición es de un éxito moderado, pero señala una serie de caminos cuya exploración aparece promisoria.

Suggested Citation

  • Felipe Zurita, 2008. "La Predicción de la Insolvencia de Empresas Chilenas," Documentos de Trabajo 336, Instituto de Economia. Pontificia Universidad Católica de Chile..
  • Handle: RePEc:ioe:doctra:336
    as

    Download full text from publisher

    File URL: https://www.economia.uc.cl/docs/doctra/dt-336.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Cheng Hsiao & M. Hashem Pesaran, 2004. "Random Coefficient Panel Data Models," CESifo Working Paper Series 1233, CESifo.
    2. Duffie, Darrell & Saita, Leandro & Wang, Ke, 2007. "Multi-period corporate default prediction with stochastic covariates," Journal of Financial Economics, Elsevier, vol. 83(3), pages 635-665, March.
    3. William W. Gould & Jeffrey Pitblado & Brian Poi, 2010. "Maximum Likelihood Estimation with Stata," Stata Press books, StataCorp LP, edition 4, number ml4, March.
    4. Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
    5. Merton, Robert C, 1974. "On the Pricing of Corporate Debt: The Risk Structure of Interest Rates," Journal of Finance, American Finance Association, vol. 29(2), pages 449-470, May.
    6. Ke Wang & Darrell Duffie, 2004. "Multi-Period Corporate Failure Prediction With Stochastic Covariates," Econometric Society 2004 Far Eastern Meetings 747, Econometric Society.
    7. Zmijewski, Me, 1984. "Methodological Issues Related To The Estimation Of Financial Distress Prediction Models," Journal of Accounting Research, Wiley Blackwell, vol. 22, pages 59-82.
    8. Sanjiv R. Das & Darrell Duffie & Nikunj Kapadia & Leandro Saita, 2007. "Common Failings: How Corporate Defaults Are Correlated," Journal of Finance, American Finance Association, vol. 62(1), pages 93-117, February.
    9. Sudheer Chava & Robert A. Jarrow, 2008. "Bankruptcy Prediction with Industry Effects," World Scientific Book Chapters, in: Financial Derivatives Pricing Selected Works of Robert Jarrow, chapter 21, pages 517-549, World Scientific Publishing Co. Pte. Ltd..
    10. Shumway, Tyler, 2001. "Forecasting Bankruptcy More Accurately: A Simple Hazard Model," The Journal of Business, University of Chicago Press, vol. 74(1), pages 101-124, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Rodrigo Alfaro A. & Natalia Gallardo S. & Camilo Vio G., 2010. "Análisis de Derechos Contingentes: Aplicación a Casas Comerciales," Notas de Investigación Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 13(1), pages 73-82, April.
    2. Rodrigo A. Alfaro & Rodrigo Cifuentes S., 2011. "Financial Stability, Monetary Policy, and Central Banking: An Overview," Central Banking, Analysis, and Economic Policies Book Series, in: Rodrigo Alfaro (ed.),Financial Stability, Monetary Policy, and Central Banking, edition 1, volume 15, chapter 1, pages 001-010, Central Bank of Chile.
    3. Caro, Norma Patricia & Arias, Ver—nica & Ortiz, Pablo, 2017. "Predicci—n de fracaso en empresas latinoamericanas utilizando el mŽtodo del vecino más cercano para predecir efectos aleatorios en modelos mixtos || Prediction of Failure in Latin-American Companies U," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 24(1), pages 5-24, Diciembre.
    4. Caro, Norma Patricia, 2016. "Predicción de fracaso empresarial en empresas de Argentina, Chile y Perú a través de indicadores contables," Revista de Dirección y Administración de Empresas, Universidad del País Vasco - Escuela Universitaria de Estudios Empresariales de San Sebastián.
    5. Felipe Zurita L., 2008. "Bankruptcy Prediction for Chilean Companies," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 11(1), pages 93-116, April.
    6. Erdely, Arturo, 2017. "Value at Risk and the Diversification Dogma || Valor en riesgo y el dogma de la diversificación," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 24(1), pages 209-219, Diciembre.
    7. Rodrigo A. Alfaro. & Andrés Sagner & Carmen G. Silva, 2011. "Aplicaciones del Modelo Binomial para el Análisis de Riesgo," Working Papers Central Bank of Chile 631, Central Bank of Chile.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. John Y. Campbell & Jens Hilscher & Jan Szilagyi, 2008. "In Search of Distress Risk," Journal of Finance, American Finance Association, vol. 63(6), pages 2899-2939, December.
    2. Anand Deo & Sandeep Juneja, 2021. "Credit Risk: Simple Closed-Form Approximate Maximum Likelihood Estimator," Operations Research, INFORMS, vol. 69(2), pages 361-379, March.
    3. Deniz Anginer & Çelim Yıldızhan, 2018. "Is There a Distress Risk Anomaly? Pricing of Systematic Default Risk in the Cross-section of Equity Returns [The risk-adjusted cost of financial distress]," Review of Finance, European Finance Association, vol. 22(2), pages 633-660.
    4. Anand Deo & Sandeep Juneja, 2019. "Credit Risk: Simple Closed Form Approximate Maximum Likelihood Estimator," Papers 1912.12611, arXiv.org.
    5. Tomasz Berent & Radosław Rejman, 2021. "Bankruptcy Prediction with a Doubly Stochastic Poisson Forward Intensity Model and Low-Quality Data," Risks, MDPI, vol. 9(12), pages 1-24, December.
    6. Felipe Zurita L., 2008. "Bankruptcy Prediction for Chilean Companies," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 11(1), pages 93-116, April.
    7. Koresh Galil & Neta Gilat, 2019. "Predicting Default More Accurately: To Proxy or Not to Proxy for Default?," International Review of Finance, International Review of Finance Ltd., vol. 19(4), pages 731-758, December.
    8. Huang, Hsing-Hua & Lee, Han-Hsing, 2013. "Product market competition and credit risk," Journal of Banking & Finance, Elsevier, vol. 37(2), pages 324-340.
    9. Ruey-Ching Hwang & Huimin Chung & Jiun-Yi Ku, 2013. "Predicting Recurrent Financial Distresses with Autocorrelation Structure: An Empirical Analysis from an Emerging Market," Journal of Financial Services Research, Springer;Western Finance Association, vol. 43(3), pages 321-341, June.
    10. Filipe, Sara Ferreira & Grammatikos, Theoharry & Michala, Dimitra, 2016. "Forecasting distress in European SME portfolios," Journal of Banking & Finance, Elsevier, vol. 64(C), pages 112-135.
    11. Asis, Gonzalo & Chari, Anusha & Haas, Adam, 2021. "In search of distress risk in emerging markets," Journal of International Economics, Elsevier, vol. 131(C).
    12. Sigrist, Fabio & Leuenberger, Nicola, 2023. "Machine learning for corporate default risk: Multi-period prediction, frailty correlation, loan portfolios, and tail probabilities," European Journal of Operational Research, Elsevier, vol. 305(3), pages 1390-1406.
    13. Nguyen, Ha, 2023. "An empirical application of Particle Markov Chain Monte Carlo to frailty correlated default models," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 103-121.
    14. Hwang, Ruey-Ching, 2012. "A varying-coefficient default model," International Journal of Forecasting, Elsevier, vol. 28(3), pages 675-688.
    15. Zhou, Ping, 2007. "Forecasting bankruptcy and physical default intensity," LSE Research Online Documents on Economics 24434, London School of Economics and Political Science, LSE Library.
    16. Hyeongjun Kim & Hoon Cho & Doojin Ryu, 2020. "Corporate Default Predictions Using Machine Learning: Literature Review," Sustainability, MDPI, vol. 12(16), pages 1-11, August.
    17. Krüger, Steffen & Oehme, Toni & Rösch, Daniel & Scheule, Harald, 2018. "A copula sample selection model for predicting multi-year LGDs and Lifetime Expected Losses," Journal of Empirical Finance, Elsevier, vol. 47(C), pages 246-262.
    18. Ruey-Ching Hwang & Jhao-Siang Siao & Huimin Chung & C. Chu, 2011. "Assessing bankruptcy prediction models via information content of technical inefficiency," Journal of Productivity Analysis, Springer, vol. 36(3), pages 263-273, December.
    19. Ruey-Ching Hwang & Chih-Kang Chu, 2013. "Forecasting forward defaults: a simple hazard model with competing risks," Quantitative Finance, Taylor & Francis Journals, vol. 14(8), pages 1467-1477, August.
    20. Alam, Nurul & Gao, Junbin & Jones, Stewart, 2021. "Corporate failure prediction: An evaluation of deep learning vs discrete hazard models," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).

    More about this item

    Keywords

    Insolvencia; riesgo de crédito;

    JEL classification:

    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ioe:doctra:336. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Jaime Casassus (email available below). General contact details of provider: https://edirc.repec.org/data/iepuccl.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.