In recent years, global climate change has intensified, and extreme weather events have occurred frequently, especially in 2022, the world has suffered a 60-year extreme high temperature weather, water shortages in many places, power constraints, and extreme high temperature weather caused huge direct and indirect economic losses, resulting in a greater impact on agricultural production. The impact of weather risk on China's economy has become increasingly prominent and aroused widespread concern. The 14th Five-Year Plan points out that the innovation level of financial products should be improved to grasp the new opportunities of the growth of the rural industry. Weather derivatives, as a kind of meteorological financial derivatives, are priced on the basis of meteorological indicator data in a certain region, and have been widely used in mature markets and related industries abroad, however, the development history in China is relatively short, and the perfect meteorological financial market has not yet been established. In view of this, we select nine weather stations across the country according to the distribution of climate zones as the research object, and take Nanchang City as an example to model for detailed analysis. Firstly, this study uses the AHP-CRITIC combination method to assign weights to temperature, wind speed and humidity and constructs a weather composite indicator; secondly, the combination model is used to predict the weather composite indicator respectively, and the research results show that the WD-SSA-LSTM model constructed has the best prediction effect; thirdly, the pricing of weather derivatives for each city is realized through Monte Carlo simulation, and a weather financial market with strong flexibility and adaptability is established. option contracts with strong flexibility and adaptability; finally, according to the research conclusions, corresponding recommendations are put forward for traders, related parties and government departments, which provide a strong guarantee for the healthy development of weather-sensitive industries such as agriculture and help China's high-quality development.

Jiang Wenjie. Meteorological Composite Index Prediction Based on WD-SSA-LSTM Modeling and Pricing Study of Weather Derivatives. Academic Journal of Business & Management (2024) Vol. 6, Issue 7: 175-180. https://doi.org/10.25236/AJBM.2024.060724.

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