This article simulates the 2010 Flash Crash to analyze how institutional selling algorithms, high-frequency trading, and liquidity constraints triggered a rapid market collapse.
The simulation reproduces a dynamic order book and heterogeneous agents: institutional sellers executing liquidation algorithms, market makers, and high-frequency participants responding in milliseconds. The model recreates rapid price drops, widening bid-ask spreads, and changes in liquidity providers' inventories, and calibrates its results to match the historical findings published by the SEC and CFTC.
The results show how an intensive selling algorithm on liquid contracts can generate an avalanche of orders that erodes liquidity: market makers reduce their exposure, the bid-ask spread widens, and the automatic response mechanisms of high-frequency systems amplify fluctuations. These interactions produce feedback effects that transform a localized drop into a widespread market collapse within minutes.
The simulation also reproduces signals observed in real data: abrupt price movements within seconds, jumps in market depth, and shifts in market makers' inventory positions. These phenomena confirm the importance of real-time risk management, algorithm supervision, and regulations on circuit breakers and market pauses designed to mitigate extreme events.
From the perspective of prevention and system design, the findings imply that it is necessary to combine technological and regulatory solutions: stricter controls on institutional algorithms, better monitoring tools to detect dangerous feedback loops, and contingency systems that allow liquidity to be restored in an orderly manner.
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Keywords custom applications custom software artificial intelligence cybersecurity AWS and Azure cloud services business intelligence services AI for businesses AI agents Power BI
