Herding as behavior investing: A bibliometric analysis - Muhammad Iqbal Alamsyah; Miftakul Huda; Rengga Madya Pranata (JAAF (Journal of Applied Accounting and Finance), 2023)
Behavioral investing seeks to understand and exploit psychological biases in financial decision-making. It is based on the idea that investors are often influenced by psychological factors such as emotions, heuristics, and social norms, which can lead to systematic errors in judgment. These biases can cause investors to make irrational or suboptimal decisions, which can have negative consequences for their financial well-being. Behavioral investors aim to identify these biases to make more rational and profitable investment decisions. This research using bibliometric analysis from 246 article was published in a reputable (SCOPUS), peer-reviewed journal that is included in an index of scholarly literature. Bibliometric analysis is a method of analyzing and quantifying the characteristics of a set of publications, to study the trends and patterns in the existing research on herding behavior. Based on the research reviewed, it appears that herding behavior is a complex phenomenon that is influenced by various factors, including psychological biases, environmental conditions, and market conditions. It is often studied in the context of behavioral finance and investor behavior, and is relevant to the study of market efficiency and capital markets.