Sandeep S. Shenoy

Determinants of dividend policy have been a topic of debate in the academic literature for several decades, but the studies have not been able to give a concluding result on the topic. Existing literature reveals that one of the most challenging decisions, dividend payout, is affected by multiple determinants thereby impacting the value of stock, among which proficatibility, capital structure and level of cash flows are identified to be significant factors. The aim of this study is to evaluate empirically the determinants of dividend payout among the companies in the Indian auto components sector which are listed in major Indian bourses. This paper constitutes a modest attempt to explore the relationship between dividend policy (dividend pay-out ratio) of the companies and the variables representing profitability, capital structure, investments, liquidity and cash flows. The other salient feature of the study is that it examines casual relationship of financial performance, operational efficiencies and investment strategies on decision of paying the dividend. ANOVA, correlation analysis and regression analysis have been used to explore the relationship between the identified variables. The study finds that the dividend policy of the companies in the Indian auto components sector is largely influenced by the operating profit, cash from operations, proportion of cash from operations used for financing the investment activities and the proportion of equity in the capital structure of the companies. The study addresses the Indian auto components sector, which is not researched much, and suggests rejuvenation in dividend policy after accounting a derived variable of cash flow to capital expenditure, as identified relevant to the group of auto manufacturers selected for the study.

The unprecedented outbreak of COVID-19 has affected every aspect of the human life, be it health, social, or economic dimensions. The anxiety and uncertainty wobbled the economies of affected countries worldwide. This study attempts to quantify the impact of COVID-19 on the performance of major stock markets of G-7 nations vis-à-vis BRICS nations. An event study methodology is employed to capture the effect of the systematic event in the form of Buy and Hold Abnormal Returns (BHAR) and Average Buy and Hold Abnormal Returns (ABHAR). The study considers a 90-day observation window, consisting of six sub-event windows after the COVID-19 news up-doves the world, and 120 days prior to the selected event date to estimate average expected returns. BHAR values in the four event windows are statistically significant, covering stock markets from panic and nosedive to their correction and recovery. ABHAR values reported are significantly negative in the event window ranging from –0.15% to –38.43% for G-7 and –0.06% to –37.12% for BRICS nations. Despite similar ABHAR trends, the BHAR values and correlation matrix exhibit a diverse reaction in BRICS nations compared to the highly synchronized reaction in the G-7 group of nations in the COVID period.

Investor sentiment is the result of trading behavior and irrational beliefs of investors leading to high volatility and market mispricing. This review aims to study the entire spectrum of articles in the domain of investor sentiment using a bibliometric analysis approach. To this end, the study analyzes a total of 1,919 articles published in the Scopus database between 1979 and 2022. The review uncovers major themes, leading authors, influencing articles, trend topics, top contributing countries, and affiliations. The review shows that the research in the domain of investor sentiment is growing exponentially with an annual growth rate of 15.88%, and the year 2020 witnessed the highest number of scientific productions accounting for 252 (13.68%) total publications. The results display that the USA and China are leading countries in terms of the total contribution and volume of studies from respective authors. The review also reveals that existing research in the field has mainly focused on themes such as market efficiency, asset pricing, stock returns, sentiment analysis, IPO underpricing, overreaction, and volatility, whereas Covid-19 and Bitcoin depicted as emerging themes from recent scholarly works.

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.

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.