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

Arjun Remadevi Somanathan,Suprabha Kudigrama Rama

doi:10.2478/acss-2020-0010

Arjun Remadevi Somanathan, Suprabha Kudigrama Rama

Open Access

https://doi.org/10.2478/acss-2020-0010

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Abstract

Abstract 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.

Highlights

Research in the field of stock market goes back to the early 1930s
From the perspective of academic disciplines of Statistics and Finance, researchers started looking into how the stock market behaves or prices can be predicted [2]
Three key theories have been developed from the earliest studies: random walk hypothesis (RWH), efficient market hypothesis (EMH), and noisy market hypothesis

Summary

Introduction

Research in the field of stock market goes back to the early 1930s. Apart from concrete theories, most studies have contributed to merging and sub-diverging of academic disciplines and varied findings. The earliest real stock market recorded in human history was Amsterdam stock exchange in 1602. Before the turn of the 21st century, this very definition has paved the way to different notions with the rise of electronic financial markets [1]. From the perspective of academic disciplines of Statistics and Finance, researchers started looking into how the stock market behaves or prices can be predicted [2]. Three key theories have been developed from the earliest studies: random walk hypothesis (RWH), efficient market hypothesis (EMH), and noisy market hypothesis.

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