Impact of personality traits on investment decision-making: Mediating role of investor sentiment in India

The behavior of investors and their investment decision-making process in the financial markets are guided by psychological (sentiments) and personal characteristics (personality traits). Research in recent years has shown the connection between investor sentiment and personality traits and investment decisions. Though academic works in the field of behavioral finance are growing, studies on personality traits and investment decision-making with investor sentiment as a mediator are sparse. To this end, the paper aims to analyze the effects of Indian retail investors’ Big-five personality traits (Neuroticism, Extraversion, Openness to experience, Agreeableness, and Conscientiousness) on their short-term and long-term investment decision-making with the mediating effect of investor sentiment. The study employs the Partial Least Square-Structural Equation Model to test the framed hypotheses. The findings of the study reveal that Neuroticism has a significant positive effect (β=0.352, p<0.05) on investor sentiment. It further shows that Extraversion has a significant positive effect (β=0.186, p<0.05) on long-term decision-making. On the contrary, the consciousness trait has a significant negative effect (β=-0.335, p<0.05) on short-term investment decision-making. Furthermore, the Openness trait demonstrates a significant effect on both short-term and long-term investment decision-making (β=0.357, p<0.05; β=0.007, p<0.05). However, the findings reveal no significant intervening effect of investor sentiment between personality traits and investment decision-making. Thus, the study strongly exerted the impact of investors’ personality traits on their investment decision-making due to the high influence of personal characteristics over sentiment effects

Do bond attributes affect green bond yield? Evidence from Indian green bonds

Over the years, green finance tools have gained considerable attention with the increased concern to achieve sustainability in the economy. Green bonds are one such new innovative green finance tool embodied with bonds and green attributes. However, research on the Indian green bond is relatively modest. Thus, this study aims to analyze the impact of bond attributes on green bond yield. The study retrieves green bond data from the Bloomberg and Climate Bonds Initiative databases from 2015 to 2022. To test the framed hypotheses, the study employs a panel regression technique with a random effect model. The findings of the study show a significant positive effect of bond ratings (β = 2.80926, p < 0.05) on green bond yield based on the argument that good-rated bonds serve as collateral in the security market. On the contrary, the result also reveals a significant negative effect of bond maturity (β = –0.327296, p < 0.05) and bond label (β = –3.16480, p < 0.05) on green bond yield. The results based on the observation suggest that when the certified bond is issued, this signals the greenness of the bond in the market and attracts high demand, whereas the long maturity ensures the green project construction for a longer period, resulting in a lower bond value. Thus, empirical findings reveal that bond attributes are the major factors in influencing bond yield. The obtained results serve as a prerequisite for potential issuers, investors, and policymakers to further popularize the green bond in the country

Is the Nexus Between Capital Structure and Firm Performance Asymmetric? An Emerging Market Perspective

The nature of the relationship between leverage and firm performance has been a subject of investigation in extant literature. We re-examine the nature of the association by using a sample of 78 non-financial firms listed in the Nifty 100 index during the 2013-2023 period by applying the quantile regression technique and comparing the result with the linear regression approach (system GMM technique). Our empirical analysis demonstrates that leverage negatively impacts the performance of firms. Further, results show that the association is non-homogeneous among firms of different quantiles: leverage withers the performance of highly profitable firms (upper quantile) than low profitable firms (lower quantile). The identified concave relationship highlights the prominence of optimal capital structure and the role of finance managers in designing a sound financial policy that matches firm characteristics and borrowing requirements. The findings of our study draw insightful implications for managers and policymakers while contributing to the ongoing leverage and firm performance debate reported in previous studies

Does the Ind AS moderate the relationship between capital structure and firm performance?

In line with the wide implementation of IFRS around the globe, the significant shift in the Indian accounting system appertained to the Ind AS is expected to have a substantial impact on the firm-level information environment. Nevertheless, the question of whether the adoption of such standards moderates the relationship between leverage and firm performance remains unanswered. In this backdrop, we aim to close this research gap employing 3120 firm-year observations from 401 Indian non-financial firms for a period from 2013 to 2022. Notably, we found that the leverage among Indian firms discourages profitability. Further, the adoption of Ind AS negatively moderates the leverage and firm performance association. The findings suggest that the enhanced transparency and the firm's reporting quality dissuade risk-averse investors from investing in highly levered companies. As a result, investors avoid risky investments, and firms must strive to foster their trust and motivation. The conclusion of the present research draws significant implications for management and policymakers while also contributing to the ongoing debate on capital structure and firm performance

Bibliometric portrait of the theory of community-based enterprise: evolution and future directions

AbstractThe focus of this study is to present an overview of the literature related to the Theory of Community-Based Enterprise (TCBE) using bibliometric analysis. We analysed 477 articles published in 201 journals in the Scopus database till 2021. Initially, prominent features based on key bibliometric indicators of 477 articles are presented under performance analysis, like prominent studies, journals, authors, and keywords. Then in network analysis, bibliographic coupling, and co-occurrence analysis were conducted on the articles. The bibliometric analysis enables mapping of the theory’s evolution, provides a comprehensive overview of TCBE literature, and leads to identifying the dynamics of the field and cluster-based themes and their relationships. The study resulted in three significant findings—the first is that limited studies have assessed the assumptions and features of the theory as valid in different cultural scenarios. Second, the theory is used in various concepts but prominently as a sub-topic under social entrepreneurship; there exists an opportunity to study community initiatives as a focus. The third is a spectrum of words used to represent the idea of community-based enterprises that hampers building uniformity of the concept

Overview of Corporate Governance Research in India: A Bibliometric Analysis

AbstractThough the Corporate Governance concept has gained paramount interest due to the spate of corporate scandals, there is a void in the literature in terms of a summary overview of corporate governance in the Indian context. The present study aims to provide a state-of-the-art summary of corporate governance in India. To do so, the study employs a bibliometric analysis with a systematic literature review approach with extensive use of Bibliometric R Packages and VOSViewer software. To this end, the study reviews a total of 344 articles published in the Scopus database between 2004 and 2022. Akin to this, the review performs performance analysis, science mapping, and network analysis. The findings show an increasing trend in publications since 2004 till date with an annual growth rate of 23.99%. The network analysis results delineate earnings management, gender diversity, ownership structure, board structure, board size, corporate governance, ownership, and firm performance as major research themes in this field. This study is the primary attempt to show the growth and evolution of CG research in India. Thus, the review contributes to the existing literature on CG at the country level and provides scope for further research. Also, the study findings help policymakers, academicians, and regulators to strengthen corporate governance practices in the country

Land Use/Land Cover Segmentation of Satellite Imagery to Estimate the Utilization of Earth’s Surface

Land Use/Land Cover (LULC) mapping plays a major role in land management applications such as to generate community map, proper urban planning, and disaster risk management. Proposed algorithm efficiently segments different land use/land cover classes such as buildings, trees, bare land, and water body. RMS value based multi-thresholding technique is used to segment various land use/land cover classes and consequently using the binning technique to accurately estimate the utilization of earth’s surface. The proposed algorithm is tested on two different data sets of Bengaluru city, India. The percentage utilization of surface objects for grid 7 image of dataset I is found to be 96.68% building, 1.05% vegetation, and 0.22% barren land, the area covered in grid 7 of dataset I is identified as overutilized land. Percentage utilization of surface objects for grid 8 of dataset II is found to be 68.95% building

A Texture based Image Retrieval for Different Stages of Alzheimer’s Disease

In the last few years, using digital images have become significant across most of the sectors including healthcare and medical labs. To analyze and interpret the large collection of images having a complex disease pattern requires the knowledge of medical experts. So, the image retrieval technique plays an important role to assist the doctors to carefully examine an image of a new patient by comparing with most similar images existing in the database and also to take a correct decision during diagnosis. So, we carried out our studies by collecting the images of Magnetic Resonance Imaging (MRI) from the Open Access Series of Imaging Studies (OASIS) database. Later, we have categorized the collected MRI images into three different groups based on the size of a ventricular region of the brain and then employed second and higher order statistical methods to extract the textural features from each image. Thus

Green Bond as an Innovative Financial Instrument in the Indian Financial Market: Insights From Systematic Literature Review Approach

As India has set its ambitious target of reaching renewable energy by 2050, it has shown overwhelming interest in Environmental, Social, and Governance (ESG) focused financial products. However, studies on the Indian green bond market are sparse, besides its divergent role in terms of green bond issuance from an emerging market’s perspective. This study aims to fill this gap by employing a systematic review of the literature, emphasizing green bond market growth, the limiting factors, and its future development. This review examined papers published between 2010 and 2022. The review demonstrates that the lack of proper framework, high transaction costs, non-labeling of bonds, higher greenwashing, issuers’ poor creditworthiness, less government involvement, unattractive sovereign rate, unavailability of financial benefits, and lack of awareness have suppressed the rapid expansion of this market. The study based on its findings suggests effective policy measures with the expectation of the active involvement of multiple stakeholders

Is the nexus between capital structure and firm performance asymmetric? An emerging market perspective

The nature of the relationship between leverage and firm performance has been a subject of investigation in extant literature. We re-examine the nature of the association by using a sample of 78 non-financial firms listed in the Nifty 100 index during the 2013-2023 period by applying the quantile regression technique and comparing the result with the linear regression approach (system GMM technique). Our empirical analysis demonstrates that leverage negatively impacts the performance of firms. Further, results show that the association is non-homogeneous among firms of different quantiles: leverage withers the performance of highly profitable firms (upper quantile) than low profitable firms (lower quantile). The identified concave relationship highlights the prominence of optimal capital structure and the role of finance managers in designing a sound financial policy that matches firm characteristics and borrowing requirements. The findings of our study draw insightful implications for managers and policymakers while contributing to the ongoing leverage and firm performance debate reported in previous studies. Since the pioneering work of Modigliani and Miller, the debate on the relationship between Capital Structure (CS) and Firm Performance (FP) has been a subject of discussion. Consequently, the CS and FP linkage has garnered the attention of several academic scholars. However, the majority of the empirical studies have demonstrated a linear link between CS and FP, whereas the studies on the nonlinear relationship are scant in the existing scholarly studies. Thus, to provide more insights, we used quantile regression techniques, and our results corroborate that the CS and FP relationship is non-homogeneous among Indian firms. To succinctly put, the magnitude of the negative impact of leverage is found to be more around highly profitable firms. Our regression result highlights the importance of maintaining the right capital mix and suggests that large firms should refrain from excessive borrowing. Further, we contend that policymakers must strengthen corporate governance mechanisms and restrict the earnings management activities of the management. Overall, our robust findings enhance the existing body of knowledge while drawing significant implications for management, policymakers, and other stakeholders.</p