Subject: Quantitative recurrence over time of a financial indicator proposed by the author, the probability of which is low for human influence. Objectives. Proving the heuristic relevance of the "time crystal" concept for studying financial market events by demonstrating the quantitative recurrence over time of a financial indicator, the probability of which is low for human influence, using data on the capitalization dynamics of China Construction Bank and Bank of America, published in the Forbes list of the 2000 largest public companies in the world for 2010–2026. Methods. Comparison, contrast, systemic, descriptive, and cluster analysis methods were used. Results. In calculating and studying the values of the financial indicator "public company share in the sum of market capitalizations of several public companies," which is unlikely to be influenced by humans, using data on the market capitalization dynamics of China Construction Bank and Bank of America, published in the Forbes list of the 2000 largest public companies in the world for 2010–2026, we discovered a distribution of indicator values over time, with quantitative repetition and periodicity. To identify the periodicity of indicator changes, an algorithm was proposed that includes sorting the indicator values and representing them as a fraction with a common denominator. The unit of the indicator value scale was a number with a unique numerical notation structure, which the author called "1/89." Conclusions. The heuristic relevance of the "time crystal" concept for studying financial market events is demonstrated. The quantitative temporal repetition and periodicity of the distribution of values for the "share of a public company in the sum of market capitalizations of several public companies" indicator, which is unlikely to be influenced by humans, are demonstrated using an analysis of data on the market capitalization dynamics of China Construction Bank and Bank of America, published in the Forbes 2000 list of the world's 2000 largest public companies for 2010–2026.
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Viktor Kurlyandskiy (2026) studied this question.
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