https://archive.conscientiabeam.com/index.php/62 Conscientia Beam en-US International Journal of Business, Economics and Management 2312-5772 https://archive.conscientiabeam.com/index.php/62/article/view/4456 <p>Stock market return and foreign exchange rate are two fundamental indicators of a country’s economic performance. Decision-making in most firms is influenced by fluctuations in exchange rates. It is presumed that there is an impact of exchange rates on stock market returns. This paper examines whether there is any nexus between the BDT-USD exchange rate and the return of the DSEX index in the Dhaka Stock Exchange. The study uses monthly data for the period ranging from March 2013 to April 2023. The methodology of the study includes simple linear regression, Granger causality tests, and VAR impulse response and variance decomposition tests. The findings reveal that both the exchange rate and stock market return series are stationary at the level, and there is no evidence of a causal relationship between them. Regression results show an insignificant negative relationship, and the VAR analysis supports the absence of any meaningful impact. The variance decomposition results further confirm that shocks in one variable account for only a marginal portion of the variance in the other. The study concludes that stock market index return and exchange rate are independent of one another, and there is no causality between them, at least during the observation period. The study findings imply that the stock markets in Bangladesh are safer for foreign investors, as there is a weak relationship between exchange rate return and stock market return.</p> Aslam Mahmud Md. Habibur Rahman Copyright (c) 2025 2025-10-08 2025-10-08 12 3 58 68 10.18488/62.v12i3.4456 https://archive.conscientiabeam.com/index.php/62/article/view/4457 <p>This study aims to clarify how Environmental, Social, and Governance (ESG) risk components environmental, social, governance, and controversy scores, influence year-to-date (YTD) returns while considering industry-specific effects. It explores the relationship between ESG risk profiles and financial performance across 377 S&amp;P 500 companies from various sectors. A multi-method analytical framework was employed on a cross-sectional dataset (January–December 2023) obtained from Kaggle, which includes Yahoo Finance financial data and Sustainalytics ESG measures. Regression models based, extended, and complete with industry controls quantified the ESG-return link. Descriptive statistics, ANOVA, and clustering approaches identified sectoral ESG risk patterns. When paired with sector controls, ESG risk ratings accounted for 41.2% of YTD return variation, indicating non-linear effects: moderate-risk companies usually outperformed high- and low-risk counterparts. Sector heterogeneity was notable; Energy and Utilities (high ESG risk) showed different return patterns than Technology and Real Estate (low ESG risk). While controversy ratings had little predictive value, environmental and governance concerns were the main drivers of ESG scores. Industry was underscored as a significant risk predictor; a logistic regression classified sectors by ESG risk with 98.9% accuracy. Since ESG's financial influence is sector-dependent, investors should consider industry context and ESG profiles in their decisions. Some industries, such as technology, may emphasize governance, while companies in high-risk industries, like Energy, may prioritize environmental concerns. These findings assist managers and legislators in customizing ESG plans to fit relevant sector-specific elements.</p> Eka Sudarmaji M Rubiul Yatim Herlan Arya Jati Kusuma Al-Ansori Copyright (c) 2025 2025-10-08 2025-10-08 12 3 59 72 10.18488/62.v12i3.4457