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Economic Resilience and Antifragility: Classification of SMEs’ Shock Reactions based on Balance Sheet and Income Statement Data

文献类型： 会议论文

第一作者： Balázs Barta

作者： Balázs Barta 1 ; Gy?rgy Eigner 2 ; Ferenc Tolner 3 ;

作者机构： 1.Pannon Business Network Association, Szombathely, Hungary

2.University Research and Innovation Center, Physiological Controls Research Center, óbuda University|Biomatics and Applied Artificial Intelligence Institution, John von Neumann Faculty of Informatics, óbuda University

3.Pannon Business Network Association, Szombathely, Hungary|Doctoral School of Applied Informatics and Applied Mathematics, óbuda University, Budapest, Hungary

关键词： Economics;Industries;Logistic regression;Electric shock;Companies;Predictive models;Numerical models

会议名称： IEEE International Symposium on Applied Computational Intelligence and Informatics

主办单位：

页码： 129-134

摘要： The attribute of a company of being able to cope with unpredictable negative changes and crises is called resilience. Nevertheless, it is also possible not just to adapt to and survive economic distress periods, then even make benefit out of them. This latter phenomenon is often referred in literature as “antifragility” towards crises. In the present study a classification attempt is provided based on a novel definition of resilience and antifragility using balance sheet and income statement data from almost 26,000 small and medium-sized enterprises of the Hungarian processing industry. Logistic Regression and Random Forest models are used in order to predict a company’s resilient and/or antifragile behaviour to a sudden drop in its sales growth. The outlined work is a response to those numerous calls in literature that highlight the lack of reproducible numerical investigations based on accessible data and a tangible definition of economic resilience.

分类号： tp18-53

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