Order Book Spoofing Identification

Order book spoofing identification involves detecting the practice of placing large, non-bona fide orders to influence the price of an asset, only to cancel them before execution. This deceptive strategy aims to create a false sense of supply or demand to induce other traders to act.

Machine learning models analyze the order book in real-time, looking for rapid cancellations of large orders that coincide with price movements. By correlating order cancellations with subsequent trades, systems can isolate spoofing attempts from legitimate market-making activities.

This protection is vital for maintaining a fair and efficient environment for options and derivative trading. It prevents market participants from being misled by artificial price pressure.