International Conference on Computational Economics and Finance (ICCEF - 27)

This track focuses on the application of computational techniques in econometric modeling and analysis. Researchers are invited to present innovative methodologies that enhance the accuracy and efficiency of econometric estimations.

This session explores the intersection of game theory and computational methods in analyzing strategic interactions among economic agents. Contributions that utilize computational simulations to derive insights into competitive and cooperative behaviors are encouraged.

This track emphasizes the development and application of dynamic models in economics, utilizing computational techniques to analyze time-dependent phenomena. Papers that address economic dynamics through simulations and numerical methods are welcome.

This session invites research that employs Bayesian methods for economic modeling and inference. Contributions that demonstrate the application of Bayesian techniques to real-world economic problems are particularly encouraged.

This track focuses on the use of agent-based models to simulate and analyze complex economic systems. Researchers are invited to share their findings on how individual behaviors and interactions can lead to emergent economic phenomena.

This session explores the integration of machine learning techniques in financial modeling and analysis. Papers that demonstrate innovative applications of machine learning to enhance predictive accuracy in finance are welcome.