Mathematical models of copulas for assessing the risks of green projects
As the world embraces green technologies and projects, the need for precise modeling of complex interactions between distinct factors becomes increasingly important. Conventional standard modeling often assumes either independence or simple forms, such as Gaussian distributions, as key assumptions....
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Інститут проблем реєстрації інформації НАН України
2025
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drspiprikievua-article-3356142025-08-09T14:55:54Z Mathematical models of copulas for assessing the risks of green projects Математичні моделі копул для оцінювання ризиків «зелених проєктів» Кузнєцова, Н. В. Квашук, І. О. копули, математичні моделі, оцінювання ризиків, Extreme Value Theory copulas, mathematical models, risk assessment, Extreme Value Theory As the world embraces green technologies and projects, the need for precise modeling of complex interactions between distinct factors becomes increasingly important. Conventional standard modeling often assumes either independence or simple forms, such as Gaussian distributions, as key assumptions. However, these assumptions rarely become true in real-world scenarios. For green risks, these approaches fail due to emergent behaviors that arise at the extremes of distributions, also known as tails. To address these challenges, this study proposes the use of copulas, which are well-regarded for their flexible and robust ability to model dependencies. A key focus of the research is on tail behavior, quantified using an approach similar to Value-at-Risk (VaR) estimation through empirical percentiles. The calculations were performed using three different approaches: a naive approach assuming independent variables, a non-parametric method based on historical data, and a parametric method using copulas. The behavior of the dependencies was analyzed using data covering both economic and financial aspects of projects from various industries. Several copula families, including Gumbel, Clayton, and Frank, were tested, and their modeling performance was evaluated. The results demonstrated the ability of copulas to capture the dependencies accurately. Compared to both naive and non-parametric methods, copulas showed notable advantages. They provided reliable extrapolations for data combinations that were not present in the original dataset, while effectively accounting for dependencies between factors. In conclusion, the importance of copulas in the green sector is expected to grow, leading to their increasing application as a replacement for simplistic models and resulting in more accurate risk assessments and decision-making in green projects. Tabl.: 2. Fig.: 1. Refs: 19 titles. Роботу присвячено аналізу і оцінюванню кредитних ризиків «зелених проєктів» за допомогою математичних моделей копул, що дозволяє покращити врахування залежностей між економічними і екологічними факторами. Аналіз проведено на наборі даних, що включає понад 800 спостережень, які охоплюють фінансові показники і екологічні аспекти компаній з різних секторів економіки. Особливу увагу приділено детальному аналізу екстремальних залежностей на межах розподілу, зокрема у «upper tail» та «lower tail». Дослідження охоплює різні сімейства копул, такі як Гаусова, t-копула та Архімедові копули (Gumbel, Clayton, Frank), з акцентом на тих розподілах, які демонструють кращу здатність відображати асиметричну залежність, що є характерною для екологічних ризиків. На основі отриманих результатів моделювання проведено розрахунок значення Value-at-Risk (VaR) на різних рівнях довіри, що забезпечує всебічний опис характеристик ризику. Оцінка ризику, яку отримано в результаті моделювання на основі копул, представляє собою більш узагальнену та гнучку форму оцінювання ризиків порівняно з традиційними підходами. Інститут проблем реєстрації інформації НАН України 2025-05-20 Article Article application/pdf http://drsp.ipri.kiev.ua/article/view/335614 10.35681/1560-9189.2025.27.1.335614 Data Recording, Storage & Processing; Vol. 27 No. 1 (2025); 15-27 Регистрация, хранение и обработка данных; Том 27 № 1 (2025); 15-27 Реєстрація, зберігання і обробка даних; Том 27 № 1 (2025); 15-27 1560-9189 uk http://drsp.ipri.kiev.ua/article/view/335614/324894 Авторське право (c) 2025 Реєстрація, зберігання і обробка даних |
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Data Recording, Storage & Processing |
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2025-08-09T14:55:54Z |
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OJS |
| language |
Ukrainian |
| topic |
copulas mathematical models risk assessment Extreme Value Theory |
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copulas mathematical models risk assessment Extreme Value Theory Кузнєцова, Н. В. Квашук, І. О. Mathematical models of copulas for assessing the risks of green projects |
| topic_facet |
копули математичні моделі оцінювання ризиків Extreme Value Theory copulas mathematical models risk assessment Extreme Value Theory |
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Article |
| author |
Кузнєцова, Н. В. Квашук, І. О. |
| author_facet |
Кузнєцова, Н. В. Квашук, І. О. |
| author_sort |
Кузнєцова, Н. В. |
| title |
Mathematical models of copulas for assessing the risks of green projects |
| title_short |
Mathematical models of copulas for assessing the risks of green projects |
| title_full |
Mathematical models of copulas for assessing the risks of green projects |
| title_fullStr |
Mathematical models of copulas for assessing the risks of green projects |
| title_full_unstemmed |
Mathematical models of copulas for assessing the risks of green projects |
| title_sort |
mathematical models of copulas for assessing the risks of green projects |
| title_alt |
Математичні моделі копул для оцінювання ризиків «зелених проєктів» |
| description |
As the world embraces green technologies and projects, the need for precise modeling of complex interactions between distinct factors becomes increasingly important. Conventional standard modeling often assumes either independence or simple forms, such as Gaussian distributions, as key assumptions. However, these assumptions rarely become true in real-world scenarios.
For green risks, these approaches fail due to emergent behaviors that arise at the extremes of distributions, also known as tails. To address these challenges, this study proposes the use of copulas, which are well-regarded for their flexible and robust ability to model dependencies. A key focus of the research is on tail behavior, quantified using an approach similar to Value-at-Risk (VaR) estimation through empirical percentiles.
The calculations were performed using three different approaches: a naive approach assuming independent variables, a non-parametric method based on historical data, and a parametric method using copulas. The behavior of the dependencies was analyzed using data covering both economic and financial aspects of projects from various industries. Several copula families, including Gumbel, Clayton, and Frank, were tested, and their modeling performance was evaluated. The results demonstrated the ability of copulas to capture the dependencies accurately.
Compared to both naive and non-parametric methods, copulas showed notable advantages. They provided reliable extrapolations for data combinations that were not present in the original dataset, while effectively accounting for dependencies between factors. In conclusion, the importance of copulas in the green sector is expected to grow, leading to their increasing application as a replacement for simplistic models and resulting in more accurate risk assessments and decision-making in green projects. Tabl.: 2. Fig.: 1. Refs: 19 titles. |
| publisher |
Інститут проблем реєстрації інформації НАН України |
| publishDate |
2025 |
| url |
http://drsp.ipri.kiev.ua/article/view/335614 |
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AT kuznêcovanv mathematicalmodelsofcopulasforassessingtherisksofgreenprojects AT kvašukío mathematicalmodelsofcopulasforassessingtherisksofgreenprojects AT kuznêcovanv matematičnímodelíkopuldlâocínûvannârizikívzelenihproêktív AT kvašukío matematičnímodelíkopuldlâocínûvannârizikívzelenihproêktív |
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2025-09-17T09:26:43Z |
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2025-09-17T09:26:43Z |
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