Scientometric review and analysis of recent approaches to stock market forecasting : two decades survey

Abstract

Stock Market Forecasting (SMF) has become a spotlighted area and is receiving increasing attention due to the potential that investment returns can generate profound wealth. In the past, researchers have made significant efforts to forecast the stock market trends and predict the best time to buy, sell, or hold. The essence of past investigators’ various techniques and methods was to maximise the abundant opportunities that abound in the stock market trading and amass huge wealth from it. Over the years, no scientometric review has been conducted to scientifically map out the trends, progress, and limitations in the subject area. In this regard, this paper presents a pioneering scientometric review in SMF. It investigates a total of 220 reputable articles (2001–2021) to identify trends and patterns in stock market forecasting studies. VOSviewer software was used to conduct science mapping analysis. Actionable insights from the analysis explain significant metrics such as the top research outlets, most-cited articles, most co-occurred keywords, most influential countries, and much more. More so, a key finding in this paper is the introduction of a less computational approach that has the possibility of making a better forecast. Yet, past researchers have not thoroughly explored this option. This paper is beneficial to Early Stage Researchers (ESR), governments, funding bodies, managers, analysts, financial enthusiasts, practitioners, and investors, so as to understand the current progress and focus areas in stock market prediction.