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The purpose of this paper is to examine how chief executive officers’ (CEOs) narcissism impacts firm performance and how this, in turn, affects a CEO’s positive rhetorical tone.

The narcissism score is measured by using an analytical composite score for each CEO based on eight factors. The paper uses textual analysis on a sample of 848 CEO letters of US firms over the period 2010–2019. WarpPLS software, version 7.0 was used to conduct structural equation modeling through the partial least squares because a non-linear algorithm exists between CEO narcissism, firm performance and positive tone, and the values of path coefficients moved from non-significant to significant.

The results suggest that performance partially mediates the relationship between CEO narcissism and positive tone. This indicates that not all the positivity expressed by narcissistic CEOs is opportunism; some of it is indeed driven by better performance. The reported findings indicate that firm performance explains one-quarter of a CEO’s positive words, whereas some three-quarters of the positivity is driven by a narcissistic CEO (i.e. opportunism). A comparison of letters signed by highly narcissistic and less narcissistic leaders reveals that among those letters signed by highly narcissistic leaders, firm performance plays a significant mediating role between narcissistic tendencies and positive tone. However, among those with less narcissistic score, there is no evidence that performance mediates the tone and narcissism. Interestingly, both highly narcissistic and less narcissistic CEOs use positive words and optimistic expressions even when their firms perform poorly or negatively.

The results help shareholders be aware that CEOs may opportunistically use their personal characteristics and language to manipulate them. Data limitations about women CEOs were one of the reasons behind the small proportion of women CEOs in this study, making it low in generalizability.

A comprehensive review showed that none of previous studies examined the more ambiguous relationship between a CEO’s narcissist tendency, the firm’s performance, and CEO rhetorical tone. As one set of studies focused on Narcissism → Performance, and the other one on Performance → Tone, this current study completes the picture with Narcissism → Performance → Tone.

Capital structure decisions are important decisions for any business activity because they have considerable influence on the worth and cost of companies. Most previous studies in Ethiopia were primarily focused on identifying and measuring problems in banking sectors and other sectors and paying little attention to the construction sector. The purpose of this study is mainly to fill the gap by examining the effects of capital structure on the profitability of construction firms in Ethiopia.

To test hypotheses of the study, time series secondary data were gathered from the sample of 30 grade one construction companies in Ethiopia during the 2011–2015 period. To examine the correlation among capital structures and its determinants, random effect multiple regression models were used.

From the regression outcomes, the study indicates that capital structure measured by debt to equity and long-term debt to total assets has a significant positive correlation with return on equity (ROE) and return on assets (ROA) of sampled construction companies. However, the capital structure measured by debt to assets has a significant negative correlation with ROE and ROA of sampled construction companies in Ethiopia.

This paper is the author’s original work and assures that the paper was not undertaken anywhere and is also not published in any journal before.

Introduction: The government has taken many initiatives for the overall growth of India after liberalisation and remarkably performed to make India an emerging economy. Due to changes in macroeconomic conditions, investment in companys’ shares includes the possibility of bearing high risk, which cannot be eliminated but, to some extent, minimised. The persistence of risks motivates investors to invest in different available options of investment. Gearing measures, a company’s financial leverage, represent the risk afforded within the company’s capital structure.

Purpose: The research aims to identify the risk-return analysis of financial geared stocks of Nifty 50 companies in India, which have debt equity ratios of more than 1.

Methodology: Convenience and cluster sampling techniques were used to identify companies with debt equity ratios of more than 1. The considered time period is 2010–2019.

Findings: This research found capital structure ratios, debt equity ratio, and total debt ratio. The total equity ratio does not have any visible effect on any of the dependent variables, i.e., Return on equity (ROE), Return on Assets (ROA), Earnings per share (EPS), Return on capital employed (ROCE). It explains the impact of high-levered firms’ performance on profitability and functioning. The study highlights that highly geared companies do not significantly impact the ROA, proving Modigliani and Miller’s (1958) irrelevant theory.

This paper explores the connection between capital structure and financial performance within European listed firms. The primary objective is to demonstrate an inverse U-shaped relationship between these two variables and pinpoint an optimal debt-equity mix.

In this study, we adopt a dynamic modeling approach to investigate the relationship between a firm’s capital structure and financial performance. Drawing on well-established theories and prior empirical studies, our model examines 3,121 dividend-paying firms from 41 European countries over 14 years, from 2008 to 2021. To enhance the reliability of our findings, we employ two distinct estimation techniques: the fixed effect model (FE) and the system generalized method of moments (System-GMM).

This study reveals an inverse U-shaped relationship between the firm’s financial performance, measured by the return on equity (ROE) and its capital structure (total liability to total assets ratio). Furthermore, an optimal capital structure of about 29% is determined for all firms in the sample, and about 21%, 28% and 41% industry-specific capital structure for manufacturing, real estate and wholesale trade, respectively.

This paper contributes to existing knowledge by empirically determining an optimal capital structure for listed firms across various industries in Europe, which very few studies have attempted to do in the past. An optimal capital structure is an invaluable benchmark for managers and other stakeholders, informing their decision-making.