IDEAS home Printed from https://ideas.repec.org/a/spr/finsto/v24y2020i3d10.1007_s00780-020-00423-6.html
   My bibliography  Save this article

Time reversal and last passage time of diffusions with applications to credit risk management

Author

Listed:
  • Masahiko Egami

    (Kyoto University)

  • Rusudan Kevkhishvili

    (Kyoto University)

Abstract

We study time reversal, last passage time and h $h$ -transform of linear diffusions. For general diffusions with killing, we obtain the probability density of the last passage time to an arbitrary level and analyse the distribution of the time left until killing after the last passage time. With these tools, we develop a new risk management framework for companies based on the leverage process (the ratio of a company asset process over its debt) and its corresponding alarming level. We also suggest how a company can determine the alarming level for the leverage process by constructing a relevant optimisation problem.

Suggested Citation

  • Masahiko Egami & Rusudan Kevkhishvili, 2020. "Time reversal and last passage time of diffusions with applications to credit risk management," Finance and Stochastics, Springer, vol. 24(3), pages 795-825, July.
  • Handle: RePEc:spr:finsto:v:24:y:2020:i:3:d:10.1007_s00780-020-00423-6
    DOI: 10.1007/s00780-020-00423-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00780-020-00423-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s00780-020-00423-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. Alexander J. McNeil & Rüdiger Frey & Paul Embrechts, 2015. "Quantitative Risk Management: Concepts, Techniques and Tools Revised edition," Economics Books, Princeton University Press, edition 2, number 10496.
    3. R. J. Elliott & M. Jeanblanc & M. Yor, 2000. "On Models of Default Risk," Mathematical Finance, Wiley Blackwell, vol. 10(2), pages 179-195, April.
    4. Ross Williams, 2013. "Introduction," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 46(4), pages 460-461, December.
    5. Lehar, Alfred, 2005. "Measuring systemic risk: A risk management approach," Journal of Banking & Finance, Elsevier, vol. 29(10), pages 2577-2603, October.
    6. Jin‐Chuan Duan, 1994. "Maximum Likelihood Estimation Using Price Data Of The Derivative Contract," Mathematical Finance, Wiley Blackwell, vol. 4(2), pages 155-167, April.
    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. Landriault, David & Li, Bin & Lkabous, Mohamed Amine & Wang, Zijia, 2023. "Bridging the first and last passage times for Lévy models," Stochastic Processes and their Applications, Elsevier, vol. 157(C), pages 308-334.
    2. Baurdoux, Erik J. & Pedraza, José M., 2024. "Lp optimal prediction of the last zero of a spectrally negative Lévy process," LSE Research Online Documents on Economics 119468, London School of Economics and Political Science, LSE Library.
    3. Masahiko Egami & Rusudan Kevkhishvili, 2020. "Post-Last Exit Time Process and its Application to Loss-Given-Default Distribution," Papers 2009.00868, arXiv.org, revised Mar 2024.

    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. Sangwon Suh & Inwon Jang & Misun Ahn, 2013. "A Simple Method For Measuring Systemic Risk Using Credit Default Swap Market Data," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 38(4), pages 75-100, December.
    2. Egami, M. & Kevkhishvili, R., 2017. "An analysis of simultaneous company defaults using a shot noise process," Journal of Banking & Finance, Elsevier, vol. 80(C), pages 135-161.
    3. Turalay Kenc & Emrah Ismail Cevik, 2021. "Estimating volatility clustering and variance risk premium effects on bank default indicators," Review of Quantitative Finance and Accounting, Springer, vol. 57(4), pages 1373-1392, November.
    4. Brana, Sophie & Campmas, Alexandra & Lapteacru, Ion, 2019. "(Un)Conventional monetary policy and bank risk-taking: A nonlinear relationship," Economic Modelling, Elsevier, vol. 81(C), pages 576-593.
    5. Wan†Chien Chiu & Juan Ignacio Peña & Chih†Wei Wang, 2015. "Measuring Systemic Risk: Common Factor Exposures and Tail Dependence Effects," European Financial Management, European Financial Management Association, vol. 21(5), pages 833-866, November.
    6. Helmut Elsinger & Alfred Lehar & Martin Summer, 2006. "Using Market Information for Banking System Risk Assessment," International Journal of Central Banking, International Journal of Central Banking, vol. 2(1), March.
    7. Duan, Jin-Chuan & Fulop, Andras, 2009. "Estimating the structural credit risk model when equity prices are contaminated by trading noises," Journal of Econometrics, Elsevier, vol. 150(2), pages 288-296, June.
    8. Ion Lapteacru, 2016. "Bank Risk in Central and Eastern European Countries: Does Ownership Matter?," Working Papers hal-01338767, HAL.
    9. Saidane, Dhafer & Sène, Babacar & Désiré Kanga, Kouamé, 2021. "Pan-African banks, banking interconnectivity: A new systemic risk measure in the WAEMU," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    10. Turalay Kenc & Emrah Ismail Cevik & Sel Dibooglu, 2021. "Bank default indicators with volatility clustering," Annals of Finance, Springer, vol. 17(1), pages 127-151, March.
    11. Masahiko Egami & Tadao Oryu, 2015. "An Excursion-Theoretic Approach to Regulator’s Bank Reorganization Problem," Operations Research, INFORMS, vol. 63(3), pages 527-539, June.
    12. Wan-Chien Chiu & Juan Ignacio Pe~na & Chih-Wei Wang, 2022. "Measuring Systemic Risk: Common Factor Exposures and Tail Dependence Effects," Papers 2202.02276, arXiv.org.
    13. Van Son Lai & Xiaoxia Ye, 2020. "How Does the Stock Market View Bank Regulatory Capital Forbearance Policies?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 52(8), pages 1873-1907, December.
    14. Daniel Dimitrov & Sweder van Wijnbergen, 2022. "Quantifying Systemic Risk in the Presence of Unlisted Banks: Application to the Dutch Financial Sector," Tinbergen Institute Discussion Papers 22-034/VI, Tinbergen Institute.
    15. Jin-Chuan Duan & Andras Fulop, 2005. "Estimating the Structural Credit Risk Model When Equity Prices Are Contaminated by Trading Noises," CERS-IE WORKING PAPERS 0517, Institute of Economics, Centre for Economic and Regional Studies.
    16. Marcelo Yoshio Takami & Benjamin Miranda Tabak, 2006. "Avaliação Do Risco Sistêmico Do Setor Bancário Brasileiro," Anais do XXXIV Encontro Nacional de Economia [Proceedings of the 34th Brazilian Economics Meeting] 96, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    17. Ion Lapteacru, 2016. "Income and funding structures, banking regulation and bank risk-taking: The role of ownership in Central and Eastern European banks," Working Papers hal-01301825, HAL.
    18. Duan, Jin-Chuan & Fulop, Andras, 2006. "Estimating the Structural Credit Risk Model When Equity Prices Are Contaminated by Trading Noises," ESSEC Working Papers DR 06015, ESSEC Research Center, ESSEC Business School.
    19. Suh, Sangwon, 2012. "Measuring systemic risk: A factor-augmented correlated default approach," Journal of Financial Intermediation, Elsevier, vol. 21(2), pages 341-358.
    20. Lapteacru, Ion, 2017. "Market power and risk of Central and Eastern European banks: Does more powerful mean safer?," Economic Modelling, Elsevier, vol. 63(C), pages 46-59.

    More about this item

    Keywords

    Time reversal; Linear diffusion; Last passage time; h $h$ -transform; Risk management;
    All these keywords.

    JEL classification:

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

    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:spr:finsto:v:24:y:2020:i:3:d:10.1007_s00780-020-00423-6. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.