Order Flow

Order flow, the sequence of buy and sell orders in financial markets, is a crucial data source for understanding market dynamics and informing trading strategies. Current research focuses on developing sophisticated models, including generative AI approaches like autoregressive models and deep state-space networks, to accurately simulate and predict order flow behavior, often leveraging image processing techniques or advanced factor extraction methods. These advancements improve market simulation fidelity, enhance the extraction of meaningful factors from high-frequency data, and enable more effective algorithmic trading and risk management strategies. The resulting insights have significant implications for both academic research in market microstructure and practical applications in quantitative finance.