An extensive bibliometric examination of the evolution of intraday trading in the equities market between 2008 to 2024 is conducted in this paper. Using bibliometric methods based on Bradford's Law, Lotka's Law, and Zipf's Law, the research evaluates academic production, determines the prevailing publication patterns, and explores existing research gaps and collaborative associations. The study charts the evolution of literature and identifies the primary information sources, including the top journals, contributors, and articles. A chronology of the conceptual and intellectual frameworks that direct this area of inquiry is also provided by the study. From data collected from the Scopus database, 138 relevant articles were found to be distributed across 111 journals between the given timeframe. Interestingly, “Lecture Notes in Computer Science (with subseries on Artificial Intelligence and Bioinformatics)” is the most published journal, while “Expert Systems with Applications” is the most cited. Manahov Viktor is the most productive author by means of publications (3) and h-index (2), while Cardoso Rodrigo Tomás Nogueira leads the citation count (176). Felipe Dias Paiva, Rodrigo Tomas Nogueira Cardoso, Gustavo Peixoto Hanaoka, and Wendal Moreira Duarte (2019) are the most cited authors, and their article is named as, “Decision-making for financial trading: A fusion approach of machine learning and portfolio selection”, published in “Expert Systems with Applications”. The findings show a steep surge in publications that corresponds to the number of retail traders on the rise and the implementation of regulatory reforms such as T+0 trading, which indicates the increasing intellectual interest in the intraday trading dynamics.