Browsing by Author "Ngue, Elizabeth Minoo"

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    Corporate Governance, Cost of Capital and Profitability on Non-Financial Firms Listed in Nairobi Securities Exchange, Kenya
    (International Journal of Scientific and Research Publications, 2026-03) Ngue, Elizabeth Minoo; Jagongo, Ambrose
    Corporate governance has become a fundamental topic in corporates management due to its pivotal obligation in enhancing accountability, transparency and profitability. Non-financial firms listed in Nairobi securities exchange Kenya have been greatly affected by corporate governance mechanisms and consequent cost of capital which significantly and jointly affect their profitability. Corporate governance has been known to have a great influence on the eventual profitability of listed firm. The declining profitability of nonfinancial firms poses a challenge to the realization of the Sustainable Development Goals and Vision 2030 as a whole. The period before, during and after COVID 19 is critical since its impact needs to be closely monitored.The study therefore looks to examine the effect of corporate governance, cost of capital on performance of non-financial firms listed in Nairobi Securities exchange Kenya. Specifically, to determine the effect of board independence on profitability of non-financial firms listed in NSE, Kenya, to determine the effect of ownership structure on profitability of non-financial firms listed, to determine the effect of audit committees and government codes on profitability of non-financial firms listed and to determine the moderating effect of cost of capital on the relationship between corporate governance and profitability of non-financial firms listed in NSE, Kenya. The study will be anchored on Stakeholder theory, Modern Portfolio Theory, Agency Theory, Pecking order theory and Trade-off theory. Secondary data from published audited annual financial statements will be gathered from the NSE, Kenya website to be utilized in this inquisition for the period 2016-2025.Descriptive analysis and correlation analysis will be utilized. Multiple linear regression and panel regression will be used