Modeling dynamic elasticity on intraday volatility and volume by finding PDEs using machine learning

The study proposes a methodology to identify a PDE describing the relationship between trading volume and volatility in securities, focusing on the SPDR S& P 500 ETF (SPY) as a case study. By integrating ML exploration with domain expertise, the study uncovers a simple and interpretable PDE, providing insights into market behavior and enhancing market monitoring capabilities for traders and investors. The approach emphasizes the importance of combining ML methods with domain knowledge to derive meaningful insights and practical applications in financial markets.