The aim of this research paper is to suggest an operational rating model that can be immediately used to improve the finance scheme of agricultural companies. Currently, banks are employing a rating model provided by Moody’s that uses various weighted indicators and linking the probability of default mainly to general and non-specific factors. The sampling carried out by Moody’s to obtain the probability of default was based on a small sample of agricultural companies. In this study, the authors propose the use of a new model based on the Altman EM score, using the Italian RICA database (Agricultural Accounting Information Network) and other variables derived from reclassified financial statements. This approach facilitates to emphasize how the national distribution of companies by rating classes is unbalanced toward the vulnerability area, central to the classification system used, by drawing a normal Gaussian distribution with a slight negative asymmetry. Therefore, the authors find out that for the evaluation of the creditworthiness of the farms, it is recommended to include in the calculation of the rating “historical” and economic-financial quantitative data (such as financial statements, income tax return), trend data (such as Internal of the credit institutions and Central Risks Database), qualitative, and others. The above proposed rating model has been tested on many companies and applied immediately.

Measurement of Financial and Asset Performance of Agricultural Farms: Operational Proposal for a New Rating Model for Agricultural Companies for a Sustainable Development of the Industry / Capitanio, F.; Adinolfi, F.; Itani, R.; Faccia, A.. - 1:(2020), pp. 109-119. (Intervento presentato al convegno 2nd American University in the Emirates International Research Conference, AUEIRC’18 tenutosi a Dubai nel November 13th–15th, 2018) [10.1007/978-3-030-32922-8_10].

Measurement of Financial and Asset Performance of Agricultural Farms: Operational Proposal for a New Rating Model for Agricultural Companies for a Sustainable Development of the Industry

Capitanio F.
;
2020

Abstract

The aim of this research paper is to suggest an operational rating model that can be immediately used to improve the finance scheme of agricultural companies. Currently, banks are employing a rating model provided by Moody’s that uses various weighted indicators and linking the probability of default mainly to general and non-specific factors. The sampling carried out by Moody’s to obtain the probability of default was based on a small sample of agricultural companies. In this study, the authors propose the use of a new model based on the Altman EM score, using the Italian RICA database (Agricultural Accounting Information Network) and other variables derived from reclassified financial statements. This approach facilitates to emphasize how the national distribution of companies by rating classes is unbalanced toward the vulnerability area, central to the classification system used, by drawing a normal Gaussian distribution with a slight negative asymmetry. Therefore, the authors find out that for the evaluation of the creditworthiness of the farms, it is recommended to include in the calculation of the rating “historical” and economic-financial quantitative data (such as financial statements, income tax return), trend data (such as Internal of the credit institutions and Central Risks Database), qualitative, and others. The above proposed rating model has been tested on many companies and applied immediately.
2020
978-3-030-32921-1
978-3-030-32922-8
Measurement of Financial and Asset Performance of Agricultural Farms: Operational Proposal for a New Rating Model for Agricultural Companies for a Sustainable Development of the Industry / Capitanio, F.; Adinolfi, F.; Itani, R.; Faccia, A.. - 1:(2020), pp. 109-119. (Intervento presentato al convegno 2nd American University in the Emirates International Research Conference, AUEIRC’18 tenutosi a Dubai nel November 13th–15th, 2018) [10.1007/978-3-030-32922-8_10].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/952876
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