Desogus, Marco and Venturi, Beatrice (2019): Bank Crashes and Micro Enterprise Loans. Published in: International Journal of Business and Social Science No. 12 (2019): pp. 35-53.
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Abstract
This paper begins with an analysis of trends - over the period 2012-2018 - for total bank loans, non-performing loans and the number of active, working enterprises. A review survey was done on national data from Italy with a comparison developed on a local subset from the Sardinian Region. Empirical evidence appears to support the hypothesis of the paper: can the rating class assigned by banks - using current IRB and A-IRB systems - to micro and very small enterprises, whose ability to replace financial resources using endogenous means is structurally impaired, ipso facto orient the results of performance in the same terms of PD – Probability of Default assigned by the algorithm, thereby upending the principle of cause and effect? The thesis is developed through mathematical modelling that demonstrates the interaction of the measurement tool (the rating algorithm applied by banks) on the collapse of the loan status (default, performing or some intermediate point) of the assessed micro-entity. Emphasis is given, in conclusion, to the phenomenon using evidence of the intrinsically mutualistic link of the two populations of banks and (micro) enterprises provided by a system of differential equations.
Item Type: | MPRA Paper |
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Original Title: | Bank Crashes and Micro Enterprise Loans |
Language: | English |
Keywords: | credit big data; rating models; MSE (Micro Small Enterprises) lending; financial system stability |
Subjects: | C - Mathematical and Quantitative Methods > C0 - General > C02 - Mathematical Methods C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C18 - Methodological Issues: General G - Financial Economics > G2 - Financial Institutions and Services > G24 - Investment Banking ; Venture Capital ; Brokerage ; Ratings and Ratings Agencies |
Item ID: | 114469 |
Depositing User: | Dr. Marco Desogus |
Date Deposited: | 09 Sep 2022 08:12 |
Last Modified: | 09 Sep 2022 08:12 |
References: | BERNANKE, B.S., GERTLER, M. and GILCHRIST, S. (1996), The Financial Accelerator and the Flight to Quality. The Review of Economics and Statistics, 78/1, 1-15. CONTI, G. (2016). Matematica e rischio di credito. http://www.mathisintheair.org/wp. DESOGUS, M. and CASU, E. (2018). Essays in innovative risk management methods based on deterministic, stochastic and quantum approaches. Quanah (TX): Anaphora Literary Press. DESOGUS, M. and CASU, E. (2019). A contribution on relationship banking. Economic, anthropological and mathematical reasoning, empirical evidence from Italy. International Research Journal of Finance and Economics, issue 178-2020, 25-49. FERNANDO, C., CHAKRABORTY, A. and MALLIK, R. (2002). Relationship banking and credit limits. Report presented in „Board of Governors of the Federal Reserve System‟, Washington D.C. FONG, H.G. and VASICEK, O.A. (1984). A Risk Minimizing Strategy for Portfolio Immunization. The Journal of Finance, 39(5), 1541-6. LEVINE, R., LOAYZA, N. and BECK, T. (2000). Financial intermediation and growth: causality and causes. Journal of Monetary Economics, 46(1), 31-77. MEYN, S.P. and TWEEDIE, R.L. (1993). Markov Chains and Stochastic Stability. London: Springer. PANETTA, F. and SIGNORETTI, F.M. (2010). Domanda e offerta di credito in Italia durante la crisi finanziaria. Bank of Italy - OccasionalPaper - Questioni di Economia e Finanza. PERKO L. (2001). Differential Equations and Dynamical Systems. New York: Springer. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/114469 |