Assessment of fractality of financial time series by means of Hurst exponent

The article describes the methodology for estimating the fractal dimensions of financial time series based on a simplified algorithm for calculating the Hurst index. The results of the analysis of the data for compliance with their normal distribution are presented; a conclusion is made about the presence of a leptoexcess indicative of the presence of long-term memory and the inapplicability of the effective market hypothesis. The confidence interval of the Hurst value is calculated. The dependencies of the fractal dimensions of the series on the results of R / S data analysis are formalized. A practical example of determining indicators that can be indicators when working in the stock market is considered.