{'fraction_non_alphanumeric': 0.027210884353741496, 'fraction_numerical': 0.013605442176870748, 'mean_word_length': 4.983739837398374, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
An Agent-Based Model of the Flash Crash of May 6, 2010, with Policy Implications

We describe an agent-based framework that successfully simulates the key aspects of the most famous flash crash in history: the Flash Crash of May 6, 2010. In our model, market making high-frequency traders collectively create a feedback loop system triggered by a large institutional sell, consistent with the widely cited "hot-potato effect." With the help of simulations, we discover functional relationships between the number of HFT market makers, their inventory sizes or speed, and the probability of another similar flash crash. The model can be used for stress-testing algorithms before their production stage and to give sounder policy advice.