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Investigation of Flash Crash via Topological Data Analysis

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  • Wonse Kim
  • Younng-Jin Kim
  • Gihyun Lee
  • Woong Kook

Abstract

Topological data analysis has been acknowledged as one of the most successful mathematical data analytic methodologies in various fields including medicine, genetics, and image analysis. In this paper, we explore the potential of this methodology in finance by applying persistence landscape and dynamic time series analysis to analyze an extreme event in the stock market, known as Flash Crash. We will provide results of our empirical investigation to confirm the effectiveness of our new method not only for the characterization of this extreme event but also for its prediction purposes.

Suggested Citation

  • Wonse Kim & Younng-Jin Kim & Gihyun Lee & Woong Kook, 2020. "Investigation of Flash Crash via Topological Data Analysis," Papers 2008.11558, arXiv.org.
    • Handle: RePEc:arx:papers:2008.11558
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    References listed on IDEAS

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    1. Andrei Kirilenko & Albert S. Kyle & Mehrdad Samadi & Tugkan Tuzun, 2017. "The Flash Crash: High-Frequency Trading in an Electronic Market," Journal of Finance, American Finance Association, vol. 72(3), pages 967-998, June.
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    Cited by:

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