Design and Valuation of Rainfall Derivativeswithin the Yangtze River Economic Belt in China

In the Yangtze River Economic Belt, extreme rainfall events have a substantial impact on economic activities in agriculture, energy consumption, and associated industries.Consequently, precise rainfall forecasting is of paramount importance for these sectors.This study utilizes rainfall data from 11 provinces (municipalities) within the Yangtze River Economic Belt spanning from 2004 to 2023 to construct both the Seasonal Autoregressive Integrated Moving Average (SARIMA) model and the Ornstein-Uhlenbeck (O-U) model for the rainfall index.Based on the models' fitting performance, a more appropriate rainfall index prediction model is selected.Furthermore, by integrating option pricing theory, this paper designs an option contract contingent on rainfall.Through the analysis of rainfall prediction in the Yangtze River Economic Belt and its derivative pricing, we have identified several key findings.Firstly, after differential processing, the rainfall data from this region exhibits stability, making it suitable for time series model analysis.Secondly, by fitting the rainfall data using both the SARIMA and O-U models, we found that the predicted values closely align with actual observations, indicating that these models provide accurate fits.Thirdly, employing the SARIMA and O-U models simulation to predict rainfall, we observed that the SARIMA model yields superior fit accuracy when comparing their respective errors.Fourthly, option contracts designed based on the SARIMA model reveal that increased climate volatility and higher climate risk correlate with higher pricing.Additionally, this study explores the practical application potential of weather derivatives in the Yangtze River Economic Belt and how they can be utilized to mitigate climate risks associated with rainfall fluctuations.The overarching goal is to effectively reduce climate risks faced by industries within the Yangtze River Economic Belt through scientifically sound rainfall predictions and derivative pricing, thereby promoting regional economic stability.

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Publication Details

Journal
Polish Journal of Environmental Studies
Published
2025-10-02
DOI
https://doi.org/10.15244/pjoes/209840
Citations
1
Primary Topic
Agricultural risk and resilience
Type
article
Field-Weighted Citation Impact
1.19
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article

Design and Valuation of Rainfall Derivativeswithin the Yangtze River Economic Belt in China

Bing Zhou, Yi Li
1 citations
Polish Journal of Environmental Studies
Agricultural risk and resilience
1.19
article

Design and Valuation of Rainfall Derivativeswithin the Yangtze River Economic Belt in China

Bing Zhou, Yi Li
article en
1 citations

Abstract

In the Yangtze River Economic Belt, extreme rainfall events have a substantial impact on economic activities in agriculture, energy consumption, and associated industries.Consequently, precise rainfall forecasting is of paramount importance for these sectors.This study utilizes rainfall data from 11 provinces (municipalities) within the Yangtze River Economic Belt spanning from 2004 to 2023 to construct both the Seasonal Autoregressive Integrated Moving Average (SARIMA) model and the Ornstein-Uhlenbeck (O-U) model for the rainfall index.Based on the models' fitting performance, a more appropriate rainfall index prediction model is selected.Furthermore, by integrating option pricing theory, this paper designs an option contract contingent on rainfall.Through the analysis of rainfall prediction in the Yangtze River Economic Belt and its derivative pricing, we have identified several key findings.Firstly, after differential processing, the rainfall data from this region exhibits stability, making it suitable for time series model analysis.Secondly, by fitting the rainfall data using both the SARIMA and O-U models, we found that the predicted values closely align with actual observations, indicating that these models provide accurate fits.Thirdly, employing the SARIMA and O-U models simulation to predict rainfall, we observed that the SARIMA model yields superior fit accuracy when comparing their respective errors.Fourthly, option contracts designed based on the SARIMA model reveal that increased climate volatility and higher climate risk correlate with higher pricing.Additionally, this study explores the practical application potential of weather derivatives in the Yangtze River Economic Belt and how they can be utilized to mitigate climate risks associated with rainfall fluctuations.The overarching goal is to effectively reduce climate risks faced by industries within the Yangtze River Economic Belt through scientifically sound rainfall predictions and derivative pricing, thereby promoting regional economic stability.

Polish Journal of Environmental Studies
Chongqing Technology and Business University (CN)
Openalex Percentile: Top 17%
Agricultural risk and resilience
1.19
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