IDEAS home Printed from https://ideas.repec.org/a/fan/frfrfr/vhtml10.3280-fr2020-002002.html
   My bibliography  Save this article

Can a quantitative approach be mitigated? Proposals for the application of the "early warnings" required by the new Italian Insolvency Code

Author

Listed:
  • Fabrizio Bava
  • Massimo Cane
  • Melchior Gromis di Trana

Abstract

In compliance with European regulations, the new Italian "Insolvency Code" introduced new tools to prevent future financial crises in businesses ("early warn-ings"). Their aim is to highlight future insolvency issues, to enable timely action in order to avert the potential crisis for as long as possible.V This mechanism will come into force on 15 August 2020. Based on a previous investigation that identified the most sensitive financial ratios for evaluating a go-ing concern, this study proposes and tests a possible approach which combines generic quantitative indicators with a case-by-case solution. A discriminant analysis was made on a pairwise sample of Italian non-listed small and medium-sized companies (SMEs). The proposed model overcomes the problem that arose from a combined interpretation of the indicators, and also it acts as a tool that can deter-mine the level of risk within each situation. This approach aims to limit the rigidity produced by common quantitative thresholds, thereby reducing false positives and negatives, ensuring an automatic reporting process that can preserve the efficiency of the early warning mechanism. Furthermore, our proposal is better suited to SMEs, since it is based on financial statements rather than forecasts.

Suggested Citation

  • Fabrizio Bava & Massimo Cane & Melchior Gromis di Trana, 2020. "Can a quantitative approach be mitigated? Proposals for the application of the "early warnings" required by the new Italian Insolvency Code," FINANCIAL REPORTING, FrancoAngeli Editore, vol. 2020(2), pages 33-61.
    • Handle: RePEc:fan:frfrfr:v:html10.3280/fr2020-002002
    as

    Download full text from publisher

    File URL: http://www.francoangeli.it/riviste/Scheda_Rivista.aspx?IDArticolo=67239&Tipo=ArticoloPDF
    Download Restriction: Single articles can be downloaded buying download credits, for info: https://www.francoangeli.it/DownloadCredit
    ---><---

    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. Edmister, Robert O., 1972. "An Empirical Test of Financial Ratio Analysis for Small Business Failure Prediction," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 7(2), pages 1477-1493, March.
    2. Edward I. Altman, 1968. "The Prediction Of Corporate Bankruptcy: A Discriminant Analysis," Journal of Finance, American Finance Association, vol. 23(1), pages 193-194, March.
    3. Frost, Carol A., 1997. "Disclosure policy choices of UK firms receiving modified audit reports," Journal of Accounting and Economics, Elsevier, vol. 23(2), pages 163-187, July.
    4. Laura Bini & Francesco Dainelli & Francesco Giunta, 2011. "Country effects on European mandatory disclosure of financial key performance indicators," FINANCIAL REPORTING, FrancoAngeli Editore, vol. 2011(1), pages 73-91.
    5. Edward I. Altman & Alessandro Danovi & Alberto Falini, 2013. "Z-Score Models’ application to Italian companies subject to extraordinary administration," BANCARIA, Bancaria Editrice, vol. 4, pages 24-37, April.
    6. 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.
    7. Edward I. Altman & Gabriele Sabato, 2013. "MODELING CREDIT RISK FOR SMEs: EVIDENCE FROM THE US MARKET," World Scientific Book Chapters, in: Oliviero Roggi & Edward I Altman (ed.), Managing and Measuring Risk Emerging Global Standards and Regulations After the Financial Crisis, chapter 9, pages 251-279, World Scientific Publishing Co. Pte. Ltd..
    8. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    Full references (including those not matched with items on IDEAS)

    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. Lin, Hsiou-Wei William & Lo, Huai-Chun & Wu, Ruei-Shian, 2016. "Modeling default prediction with earnings management," Pacific-Basin Finance Journal, Elsevier, vol. 40(PB), pages 306-322.
    2. Jairaj Gupta & Nicholas Wilson & Andros Gregoriou & Jerome Healy, 2014. "The value of operating cash flow in modelling credit risk for SMEs," Applied Financial Economics, Taylor & Francis Journals, vol. 24(9), pages 649-660, May.
    3. Zhichao Luo & Pingyu Hsu & Ni Xu, 2020. "SME Default Prediction Framework with the Effective Use of External Public Credit Data," Sustainability, MDPI, vol. 12(18), pages 1-18, September.
    4. Ciampi, Francesco, 2015. "Corporate governance characteristics and default prediction modeling for small enterprises. An empirical analysis of Italian firms," Journal of Business Research, Elsevier, vol. 68(5), pages 1012-1025.
    5. Gupta, Jairaj & Wilson, Nicholas & Gregoriou, Andros & Healy, Jerome, 2014. "The effect of internationalisation on modelling credit risk for SMEs: Evidence from UK market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 31(C), pages 397-413.
    6. Mohammad S. Uddin & Guotai Chi & Mazin A. M. Al Janabi & Tabassum Habib, 2022. "Leveraging random forest in micro‐enterprises credit risk modelling for accuracy and interpretability," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3713-3729, July.
    7. Francesco Ciampi & Valentina Cillo & Fabio Fiano, 2020. "Combining Kohonen maps and prior payment behavior for small enterprise default prediction," Small Business Economics, Springer, vol. 54(4), pages 1007-1039, April.
    8. Nikolaos Arnis & Kostas Karamanis & Georgios Kolias, 2020. "Factors Affecting Business Failure of Small and Very Small Greek Family Enterprises," Accounting and Finance Research, Sciedu Press, vol. 9(2), pages 1-35, May.
    9. Jairaj Gupta & Andros Gregoriou & Jerome Healy, 2015. "Forecasting bankruptcy for SMEs using hazard function: To what extent does size matter?," Review of Quantitative Finance and Accounting, Springer, vol. 45(4), pages 845-869, November.
    10. Rassoul Yazdipour & Richard Constand, 2010. "Predicting Firm Failure: A Behavioral Finance Perspective," Journal of Entrepreneurial Finance, Pepperdine University, Graziadio School of Business and Management, vol. 14(3), pages 90-104, Fall.
    11. fernández, María t. Tascón & gutiérrez, Francisco J. Castaño, 2012. "Variables y Modelos Para La Identificación y Predicción Del Fracaso Empresarial: Revisión de La Investigación Empírica Reciente," Revista de Contabilidad - Spanish Accounting Review, Elsevier, vol. 15(1), pages 7-58.
    12. Kaya, Orcun, 2022. "Determinants and consequences of SME insolvency risk during the pandemic," Economic Modelling, Elsevier, vol. 115(C).
    13. Antonio Blanco-Oliver & Ana Irimia-Dieguez & María Oliver-Alfonso & Nicholas Wilson, 2015. "Systemic Sovereign Risk and Asset Prices: Evidence from the CDS Market, Stressed European Economies and Nonlinear Causality Tests," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 65(2), pages 144-166, April.
    14. Cathcart, Lara & Dufour, Alfonso & Rossi, Ludovico & Varotto, Simone, 2020. "The differential impact of leverage on the default risk of small and large firms," Journal of Corporate Finance, Elsevier, vol. 60(C).
    15. Chiara Pederzoli & Grid Thoma & Costanza Torricelli, 2013. "Modelling Credit Risk for Innovative SMEs: the Role of Innovation Measures," Journal of Financial Services Research, Springer;Western Finance Association, vol. 44(1), pages 111-129, August.
    16. Juraini Zainol Abidin & Nur Adiana Hiau Abdullah & Karren Lee-Hwei Khaw, 2020. "Predicting SMEs Failure: Logistic Regression vs Artificial Neural Network Models," Capital Markets Review, Malaysian Finance Association, vol. 28(2), pages 29-41.
    17. Fejér-Király Gergely, 2015. "Bankruptcy Prediction: A Survey on Evolution, Critiques, and Solutions," Acta Universitatis Sapientiae, Economics and Business, Sciendo, vol. 3(1), pages 93-108, December.
    18. Balios, Dimitris & Thomadakis, Stavros & Tsipouri, Lena, 2016. "Credit rating model development: An ordered analysis based on accounting data," Research in International Business and Finance, Elsevier, vol. 38(C), pages 122-136.
    19. Cao Son Tran & Dan Nicolau & Richi Nayak & Peter Verhoeven, 2021. "Modeling Credit Risk: A Category Theory Perspective," JRFM, MDPI, vol. 14(7), pages 1-21, July.
    20. David Veganzones, 2022. "Corporate failure prediction using threshold‐based models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(5), pages 956-979, August.

    More about this item

    JEL classification:

    • M41 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Accounting
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation
    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies

    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:fan:frfrfr:v:html10.3280/fr2020-002002. 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: Stefania Rosato (email available below). General contact details of provider: http://www.francoangeli.it/riviste/sommario.aspx?IDRivista=163 .

    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.