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These studies suggest that financial market behavior is studied and modeled using a combination of mathematical models, behavioral science, agent-based models, and nonlinear techniques to understand investor interactions, market dynamics, and predict market behavior.
20 papers analyzed
The study and modeling of financial markets are crucial for understanding market dynamics, predicting future trends, and making informed investment decisions. Researchers employ various methodologies, including agent-based models, behavioral science approaches, and mathematical modeling, to analyze and simulate market behavior.
Agent-Based Models (ABMs)
Behavioral Science Approaches
Mathematical and Nonlinear Models
The study and modeling of financial markets involve a combination of agent-based models, behavioral science approaches, and mathematical techniques. Agent-based models simulate individual interactions to understand market phenomena, while behavioral science approaches highlight the psychological factors influencing market behavior. Mathematical and nonlinear models provide robust tools for predicting market dynamics. Integrating these methodologies offers a comprehensive understanding of financial markets, enhancing the ability to predict and respond to market changes effectively.
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