| Abstract: |
| Our study provides empirical, data-driven, and theoretical evidence that stock exchanges self-organize into a critical state with avalanche-like dynamics. We identified time intervals in the hourly stock volume series for 3,000 public company stocks for which the stock market is in a critical state. The time intervals were determined based on the behavior of the 100-hour moving average in the vicinity of the critical time. Next, we propose a model of self-organization of the stock exchange in a critical state, in which the control parameter is the measure of uncertainty of information about a public company`s share, and the order parameter is stock`s volume. |
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