会议信息

CIFEr 2026: IEEE Computational Intelligence in Financial Engineering and Economics

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截稿日期:
2026-05-15
通知日期:
2026-07-15
会议日期:
2026-09-10
会议地点:
Tokyo, Japan
ICORE: C   浏览: 3494   关注: 0   参加: 0
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用到的输入: 收录等级：ICORE C · 过去 24 个月打开过本页的研究者：5 人

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征稿

CIFEr 2026 (IEEE Computational Intelligence in Financial Engineering and Economics) is a ICORE C conference held in Tokyo, Japan on 2026-09-10. The paper submission deadline is 2026-05-15. Acceptance notifications are sent on 2026-07-15.

In recent years, the popularity of generative AI, including ChatGPT, has had a huge impact on machine learning and the fields that use it. The field most affected is undoubtedly natural language processing, but the ripple effect is spreading to other fields that deal with data. For example, in robot control research, generative AI is used to generate commands for robots. Generative AI is also becoming a presence that cannot be ignored in the fields of finance and economics. In particular, in recent years, there has been an increase in economic analysis research targeting text, and language models such as BERT have begun to be used in these studies. Given this, it is only a matter of time before generative AI is used as the next trend. CIFEr is an international conference that has long focused on the application of information technology to finance and economics. Given this technological trend, we expect a large number of research papers on the application of these new technologies to finance to be presented at CIFEr. In addition, there are an increasing number of cases where alternative data, data that have not been used before, are applied to financial economics, and new technologies are required to process these data. We expect the papers presented at the conference to include research on the use of data that has yet to be used before, as well as research on the application of new computer intelligence technologies, including generative AI, to the fields of finance and economics. In addition, there is a growing body of research that combines generative AI with long-standing technologies, such as multi-agent combinations, and we look forward to this type of challenging research. Topics of Interest Computational Intelligence Areas, Models, and Applications: Machine Learning in Finance Large Language Model Big Data Finance and Economics Neural Networks Deep Learning Models in Finance Data Mining Text Mining Probabilistic Modeling/Inference Fuzzy Sets, Rough Sets, & Granular Computing Intelligent Trading Agents Trading Room Simulation Time Series Analysis Non-linear Dynamics Financial Analytics Financial Data Mining Evolutionary Computation Digital Financial Reporting Semantic Web and Linked Data Multi-objective Optimisation Agent Based Modelling and Simulation Co-evolutionary Techniques Artificial Life Evolutionary Game Theory Particle Swarm Optimisation Cognitive Systems Recommendation Modelling and Problem Representations Operators Application Areas: Finance: Asset allocation strategies Trading systems Algorithmic trading Trade execution systems Risk management Pricing of structured securities Behavioural finance Evolutionary finance Portfolio optimisation Arbitrage Exotic options Cryptocurrencies Blockchain and applications Front and back office operations Financial prediction and forecasting Application Areas: Economics: Agent based computational economics Market modelling Energy and electricity markets Blockchain economics Application Areas: Business: Business analytics Recommender systems E-commerce Advertising and marketing Crowds and market models Demand forecasting Distribution and supply chain
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