This paper presents a bibliometric analysis of the applications of Operations Research (OR) in portfolio optimization and risk management. The data were retrieved from Elsevier’s Scopus database and comprise 1,304 documents published between 2016 and 2026 in 619 sources, together with a corpus of 48 review papers. Science mapping was carried out with Bibliometrix and its Biblioshiny interface to examine the growth, authorship and sources of the field and to build a thematic map of its keywords. The number of publications rose from 51 in 2016 to 244 in 2026, an average annual growth rate of 16.95%. Machine learning and risk analysis emerge as the motor themes, risk management and project portfolios form the basic themes, reinforcement learning is a niche theme, and classical optimization and uncertainty modelling are emerging or declining. The review identifies gaps in validation, integration across methods, and consistent terminology, and uses them to propose a research agenda.