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.
This research reexamines the relations between production, money and income and arrives at a need for reform, through a contemporary money theory, with the same foundations that endow the system of the numerical entity that measures the economy. The analysis undertaken began from the "Econophysics" observation that wealth is unequally distributed among agents in an economic system. The literature has consolidated the concept of 'systemic entropy' as the degree of endogenous 'disorder' that occurs with the succession of interactions/transactions among its elements, leading to a stabilization in equilibrium that is no longer modifiable by spontaneous perturbations, even though there is clear evidence of profound inequality in individual wealth. The contribution offered here is an in-depth investigation into the causes that have led and continue to lead to the genesis and exacerbation of these socioeconomic differences, which also convey an exclusion of the less wealthy sectors of the population from the most significant transactions. This ordains the impossibility, at the current state of the art, of achieving a neg-entropic practice, which is fundamental to the evolution of organisms. The point of arrival is in the negation of the monetary structure as currently perceived and organized.
There is an intrinsic and mutualistic dependence between the bio-economic performance of banks and that of enterprises. This supposition is supported by correlations identified in a comprehensive analysis of the Italian banking sector, which reveal particularly strong relations between financial intermediaries and smaller enterprises. Concentrating on developments within the bank-enterprise system (and by extension, in households), we discuss the positive effects, including on macroeconomics, generated when the banking sector supplies funding to productive infrastructure to understand how the industry remains healthy and efficient. The negative effects produced by the disappearance of such a cycle are also considered. This paper thus presents a mathematical argument through dynamic modelling to evaluate the structural trends in bank and company populations that result from more and less expansive credit strategies assumed by banks. Empirical observations of this data also reflect the critical stress factor of the (micro)enterprise population that allows it to generate positive economic variations as financial leverage decreases. The ensuing assessment of stable and unstable points of equilibrium as well as bifurcations and their irreversibility (hysteresis) reveals that banks have stagnating profits and increasing numbers of non-performing loans. Finally, we investigate the possibility of an optimal minimum level of credit leverage and how to improve the stabilizing measures that are conferred to the system itself, especially given the uncertainty caused by the COVID-19 pandemic.
Current assessments of credit and financial risk based on deterministic analyses provide only a limited understanding of current and future solvency rates. This paper offers an alternate model using two-state Markov chains that produces a more comprehensive and accurate system and allows for broader and more complex analyses of present and future situations.Building off findings made in the development of the Altman Z-score, this proposed model applies stochastic processes and probability spaces to multivariate normal populations to account for the uncertainty of market conditions. Where one-step Markov chains demonstrate the relevance of this model for finite and infinite variables, the player's downfall theorem indicates that the nth value is only dependent on the value before it. Using the Chapman-Kolmogorov equation, multi-step transition probabilities then lead to the final two-state Markov chain.
Here, we discuss a three-dimensional continuous-time Lotka–Volterra dynamical system, which describes the role of government in interactions with banks and small enterprises. In Italy, during the COVID-19 emergency, the main objective of government economic intervention was to maintain the proper operation of the bank–enterprise system. We also review the effectiveness of measures introduced in response to the COVID-19 pandemic lockdowns to avoid a further credit crunch. By applying bifurcation theory to the system, we were able to produce evidence of the existence of Hopf and zero-Hopf bifurcating periodic solutions from a saddle focus in a special region of the parameter space, and we performed a numerical analysis.
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