  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.
