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This research examines how investment risk is treated within a selection of 667 articles from the Web of Science database, made by applying keywords and filters, within a bibliometric analysis. The keywords by which the selection was made were investment risk, and the specific filters were: the authors’ countries of origin, EU states, and the articles to be published in the period 2019-2023 in order to identify current risks associated with investments. To ensure that the aspects analyzed are from the economic field, we chose the fields of economics, management, and business in the Web of Science categories. In Citation Topics Meso, we chose the subfields of economics and management.

The authors’ territorial distribution and affiliation were analyzed using the Web of Science and VOS viewer software functions. The analysis of the density of words and phrases associated with investment risk was substantiated with the help of Word Cloud software, Word Art, and VOSviewer software, applying the co-occurrence filter. The results generated after filtering reveal 5 clusters with a total of 87 words that are associated with investment risk, appearing at least 10 times. In addition, besides the words risk and investments, other terms with strong links in the selection were performance, impact, determinants, market, growth, and liquidity. The associations resulting from our research can form the basis of other research regarding the decision to invest and the classification of the investments or the risks to which the investment process is subject.