Feasibility Study of Using Fractal Analysis for Forecasting Stock Market Dynamics

The final qualifying work is devoted to the investigation of the possibility of using fractal analysis for forecasting in financial markets. This work consists of an introduction, three chapters and a conclusion. The first chapter includes an analysis of the field of research, including a review of modern approaches to forecasting in financial markets, theoretical aspects of fractal analysis of financial markets, an overview of current research in this field, and a description of existing methods for analyzing and forecasting financial time series. The second chapter is devoted to the development of a methodology for investigating the possibilities of using the fractal approach to predict future values ​​of price series using the tools selected as a result of the analysis performed. The third chapter describes the conducted empirical study, namely: the use of a simplified approach to the use of fractal methods for forecasting financial time series, prediction of data analysis, predicting the dynamics of indicators, as well as analysis and interpretation of the results. The work contains 99 pages of text, 29 illustrations, 13 tables. Keywords: fractals, fractal dimension, long memory, persistence, Hurst index, fractality index, R / S analysis, detrended fluctuation analysis, time series, ARFIMA, financial instruments, forecasting.