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Source: People's Republic of China in Russian – People's Republic of China in Russian –
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Source: People's Republic of China – State Council News
BEIJING, Jan. 13 (Xinhua) — China has unveiled its first artificial intelligence (AI) model to analyze the impact of weather conditions on financial markets, marking a new step in climate risk management, the China Meteorological Administration (CMA) said.
The model, called "Shangji" or "Stock," was jointly developed by Fudan University (Shanghai) and the National Meteorological Information Center. It aims to assess the impact of meteorological factors on asset pricing, offering a new tool for investment decisions and financial risk assessment, according to Science and Technology Daily, citing a source within the aforementioned agency.
The model's lead developer, Zhao Yanxia, director of the Open Key Laboratory of Financial Meteorology at CMU, said that using global meteorological data that was re-analyzed and historical stock trading data, the model is able to predict the short-term returns of most stocks in the Chinese A-share market.
Validation tests show that the model can accurately identify weather-sensitive industries such as wind and solar power, traditional petrochemicals, construction, and agriculture, bringing test results in line with international standards.
Zhao Yanxia stated that repeated testing of investment strategies based on the model's predictions showed consistent and stable positive returns over various historical periods, demonstrating practical potential.
Another developer of the model, Professor Li Hao from Fudan University, noted that the model has wide potential for application in the financial sector.
He said listed companies in weather-sensitive industries could use the model to manage climate risks, while banks, insurance firms and other financial institutions could use it to manage business risks such as equity collateral and to explore new areas of activity, including climate investing and financing.
Li Hao added that the model is useful to investors as an aid in quantitative investing, and that scholars can use its results to test and improve asset pricing theories.
The research team plans to expand the model's scope to include bonds and futures, aiming to continually update it to keep pace with market dynamics.
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