Abstract
In many real-life situations, deviations are caused by a large number of independent factors. It is known that in such situations, the distribution of the resulting deviations is close to Gaussian, and thus, that the copulas – that describe the multi-D distribution as a function of 1-D ones – are also Gaussian. In the past, these conclusions were also applied to economic phenomena, until the 2008 crisis showed that in economics, Gaussian models can lead to disastrous consequences. At present, all economists agree that the economic distributions are not Gaussian – however, surprisingly, Gaussian copulas still often provide an accurate description of economic phenomena. In this paper, we explain this surprising fact by using fuzzy-related arguments.
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Acknowledgments
This work was supported by:
\(\bullet \) the National Science Foundation grants 1623190 (A Model of Change for Preparing a New Generation for Professional Practice in Computer Science), and HRD-1834620 and HRD-2034030 (CAHSI Includes),
\(\bullet \) the AT &T Fellowship in Information Technology,
\(\bullet \) the program of the development of the Scientific-Educational Mathematical Center of Volga Federal District No. 075-02-2020-1478, and
\(\bullet \) grant from the Hungarian National Research, Development and Innovation Office (NRDI).
The authors are thankful to the anonymous referees for valuable suggestions.
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Van Le, C., Kosheleva, O., Kreinovich, V. (2023). Why Gaussian Copulas Are Ubiquitous in Economics: Fuzzy-Related Explanation. In: Dick, S., Kreinovich, V., Lingras, P. (eds) Applications of Fuzzy Techniques. NAFIPS 2022. Lecture Notes in Networks and Systems, vol 500. Springer, Cham. https://doi.org/10.1007/978-3-031-16038-7_12
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DOI: https://doi.org/10.1007/978-3-031-16038-7_12
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