Generating Asset Pricing Model via Symbolic Modeling—a Machine Learning-based Approach

Generating Asset Pricing Model via Symbolic Modeling—a Machine Learning-based Approach - Journal of Cyber Policy

COMPARISON OF FUNCTIONS DISCOVERED BY SYMBOLIC REGRESSION, AND FUNCTIONS DISCOVERED BY SYMBOLIC MODELING. GA, UNITED STATES, March 21, 2025 /EINPresswire.com/ — Researchers develop Symbolic Modeling—an AI-powered technique creating unified mathematical models for financial asset pricing. Compared to neural network, the generated mathematical expression by symbolic modeling is easier to comprehend and analyze. Testing across hundreds of company’s…

Generating Asset Pricing Model via Symbolic Modeling—a Machine Learning-based Approach

Researchers develop Symbolic Modeling--an AI-powered technique creating unified mathematical models for financial asset pricing. Compared to neural network, the generated mathematical expression by symbolic modeling is easier to comprehend and analyze. Testing across hundreds of company's datasets shows lower prediction errors and reduced unexplainable return compared to classic asset pricing models like CAPM or Fama-French 3-Factor model.

Breakthrough In Financial Asset Pricing: Symbolic Modeling Improves Accuracy With Machine Learning

Researchers from Texas A&M University have developed a machine learning-based method called Symbolic Modeling, which employs genetic programming and deep learning to generate nonlinear expressions for asset pricing, outperforming traditional models by capturing hidden market dynamics.