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Thus in this paper, a deep neural network-based assistive decision model for financial risk prediction in carbon trading market is proposed for this purpose. Specifically, the dynamic risk spillover effects of domestic and international carbon trading markets are studied, and a frontier time-varying model is utilized to measure the risk spillover effects. Then, the deep neural network is used for quantitative research and to construct an intelligent decision scheme that outputs financial risk prediction results. Four perspectives, energy price, climate environment, carbon market price, and macroeconomics, are selected as the input to analyze the influence factors of carbon emission rights price. Finally, several linear regression models are adopted as the baseline methods for comparison, and experimental results show that the proposed method can achieve better prediction performance compared with baseline methods. <\/jats:p>","DOI":"10.1142\/s0218126624501536","type":"journal-article","created":{"date-parts":[[2023,11,28]],"date-time":"2023-11-28T13:55:55Z","timestamp":1701179755000},"source":"Crossref","is-referenced-by-count":106,"title":["A Deep Neural Network-Based Assistive Decision Method for Financial Risk Prediction in Carbon Trading Market"],"prefix":"10.1142","volume":"33","author":[{"given":"Ji","family":"Luo","sequence":"first","affiliation":[{"name":"School of Economics & Management, Shanghai Polytechnic University, Shanghai, P. R. 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