Analyzing the Dividends of Stock Exchange Investors in a Competitive Market Using Varied Trading Frequencies
Abstract
This study presented an analysis of the dividends of stock exchange investors in a competitive market, with a focus on the impact of varied trading frequencies on investors’ returns in the Nigerian Stock Exchange. Existing studies primarily examine bivariate or sectoral relationships and often neglect the combined predictive power of key macroeconomic fundamentals on the overall market index. Moreover, few studies employed computational and simulation-based techniques to forecast all shares index behavior under varying economic conditions. This gap limits investors’ ability to make data-driven decisions and constrains policymakers from understanding the macro-financial transmission pathways affecting market performance. This study therefore addressed these gaps by developing a multiple linear regression model to analyze the impact of USD/NGN exchange rate, inflation rate, and crude oil price on the Nigerian. The research utilized secondary data obtained from the Central Bank of Nigeria’s monthly financial reports, covering the period from January 2015 to May 2023. The study employed advanced statistical and computational techniques, including descriptive statistics, Augmented Dickey-Fuller unit root tests, multiple regression analysis, and residual diagnostics, to examine the relationship between the Nigerian Stock Exchange All Share Index and key macroeconomic indicators such as crude oil prices, inflation rate, and the exchange rate. All calculations were done in Eview to facilitate the understanding of mathematical ideas.
Keywords
References
More Articles from WORLD JOURNAL OF FINANCE AND INVESTMENT RESEARCH
Author: Aliba Ijeoma Vivian, Ikwuagwu Henry Chinedu, PhD, Maduagwuna Veronica Ifeyinwa, PhD
Author: Ejire, Ebiye, D. W. Dagogo, Adamgbo, Suka Lenu Charles, -
Author: Ewa Fiona Oden
Author: Ikwuegbu, Akuchi Doris, Nyeche, Ezebunwo and, Amadi, Sonny Nwonodi
Author: Oluwole Samson Olowo, PhD, Femi Odunayo Ogunsanwo, MSc, Akintunde M. Ajagbe, PhD
