Bibliometric Analysis of Fractal Patterns in Stock Markets: Trends and Perspectives
نویسندگان
1 Department of Financial engineering, Hazrat-e Masoumeh University, Qom, Iran
2 Department of Theoretical Economics, Faculty of economics, Allameh Tabatabaii University, Tehran, Iran
doi
10.22067/ijaaf.2026.47633.1590چکیده
Traditional financial models fail to capture the nonlinear, self-similar patterns in stock markets, whereas the Fractal Market Hypothesis (FMH) provides a more robust framework. This study aimed to carry out a comprehensive bibliometric analysis to map the intellectual structure and evolution of research on stock markets with fractal patterns. Based on 1,280 documents obtained from the Scopus database (1982–2025), bibliometric analyses were conducted including co-authorship and co-word analysis, as well as thematic evolution with the Bibliometrix R package. Despite limitations in study design, results indicated a significant shift from basic to their applied interdisciplinary research. Multifractal approach has emerged as the leading methodology with around 42% studies after 2005. Research output is led by China, India and the USA with increasing interest in financial crises, cryptocurrencies and hybridizing fractals with artificial intelligence. The bibliometric results yield empirical evidence that reinforces the applicability of the FMH in addressing market complexity and aligning with contemporary financial phenomena. Analysis of common themes in literature highlights certain knowledge deficiency, predominantly regarding comparative studies between developed and emerging markets, dynamic performance under systemic shocks of fractal structures and the utility function analysis based on where fractal-based trading strategies are implemented. This is clearly a stepping stone for more extensive research on that topic, but it also highlights how fractal approaches can span across academic fields in finance.