Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
173 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
46 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

High-frequency financial market simulation and flash crash scenarios analysis: an agent-based modelling approach (2208.13654v1)

Published 29 Aug 2022 in q-fin.TR and q-fin.CP

Abstract: This paper describes simulations and analysis of flash crash scenarios in an agent-based modelling framework. We design, implement, and assess a novel high-frequency agent-based financial market simulator that generates realistic millisecond-level financial price time series for the E-Mini S&P 500 futures market. Specifically, a microstructure model of a single security traded on a central limit order book is provided, where different types of traders follow different behavioural rules. The model is calibrated using the machine learning surrogate modelling approach. Statistical test and moment coverage ratio results show that the model has excellent capability of reproducing realistic stylised facts in financial markets. By introducing an institutional trader that mimics the real-world Sell Algorithm on May 6th, 2010, the proposed high-frequency agent-based financial market simulator is used to simulate the Flash Crash that took place that day. We scrutinise the market dynamics during the simulated flash crash and show that the simulated dynamics are consistent with what happened in historical flash crash scenarios. With the help of Monte Carlo simulations, we discover functional relationships between the amplitude of the simulated 2010 Flash Crash and three conditions: the percentage of volume of the Sell Algorithm, the market maker inventory limit, and the trading frequency of fundamental traders. Similar analyses are carried out for mini flash crash events. An innovative "Spiking Trader" is introduced to the model, aiming at precipitating mini flash crash events. We analyse the market dynamics during the course of a typical simulated mini flash crash event and study the conditions affecting its characteristics. The proposed model can be used for testing resiliency and robustness of trading algorithms and providing advice for policymakers.

Summary

We haven't generated a summary for this paper yet.