A Bibliometric Review of Stock Market Prediction: Perspective of Emerging Markets

2020
Arjun Remadevi Somanathan, Suprabha Kudigrama Rama

The objective of the paper is to identify predictive models in stock market prediction focusing on a scenario of the emerging markets. An exploratory analysis and conceptual modelling based on the extant literature during 1933 to 2020 have been used in the study. The databases of Web of Science, Scopus, and JSTOR ensure the reliability of the literature. Bibliometrics and scientometric techniques have been applied to the retrieved articles to create a conceptual framework by mapping interlinks and limitations in past studies. Focus of research is hybrid models that integrate big data, social media, and real-time streaming data. Key finding is that actual phenomena affecting stock market sectors are diverse and, hence, limited in generalization. The future research must focus on models empirically validated within the emerging markets. Such an approach will offer an insight to analysts and researchers, policymakers or regulators.

Atslēgas vārdi
Bibliometrics, emerging markets, stock market prediction, systematic review
DOI
10.2478/acss-2020-0010

Somanathan, A., Rama, S. A Bibliometric Review of Stock Market Prediction: Perspective of Emerging Markets. Applied Computer Systems, 2020, Vol. 25, No. 2, 77.-86. lpp. ISSN 2255-8683. e-ISSN 2255-8691. Pieejams: doi:10.2478/acss-2020-0010

Publikācijas valoda
English (en)