The mediating effect of investment decisions and financing decisions on the effect of corporate risk and dividend policy against corporate value

The biggest challenge facing countries, including India, is creating and managing an LCR (low carbon resilient) economy, which balances the need for high growth rates and is environmentally sustainable. The green bond market provides investors the means to help change the economy into an LCR economy. The study was undertaken to understand the key drivers and the factors influencing the individual retail investor’s decision to invest in green bonds. A survey instrument was designed and administered through the snowball sampling technique to 125 Indian respondents of various age groups who were eligible to invest in the Indian bond market. SPSS software was used to conduct a descriptive analysis followed by regression and conjoint analyses. The study results suggest that the Environmental, Social, and Governance (ESG) rating and credit rating of the green bond issuers are the key factors that influence an individual’s investment decision. The findings also highlight that incentives such as tax exemptions and awareness of green bonds also affect an investor’s decision. This research stands out as one of the first attempts to understand the Indian retail investors’ perception of a green bond.

Dividend policy, as part of corporate governance, is largely dependent on the institutional environment in which companies operate. The study aims to determine factors affecting dividend policy in the conditions of the Ukrainian underdeveloped stock market, legal insecurity of minority shareholders, high cost and concentration of capital. For this purpose, hypotheses about the impact of a company’s financial state, size, business risk, and ownership structure on dividend payments were tested using a sample of 58 Ukrainian non-financial public joint-stock companies and applying Interactive tree classification techniques (C&RT). The resulting classification model for predicting dividend decisions correctly classifies 92.86% of companies that paid dividends and 93.3% of companies that did not. The findings, based on the classification tree and importance scale, prove the hypothesis that companies in which individuals and institutional investors have a controlling interest are more likely to pay dividends than other non-state companies. The financial indicators accurately classify only those firms that do not pay dividends, and business risk does not affect classification accuracy at all. The paper substantiates the ways of using the study findings for economic regulation, protection of minority shareholders’ rights, and proliferation of modern corporate governance practices.

Estimation of systematic risk is one of the important aspects of the best investment decisions. Through systematic risk prediction will be known risks to be faced by investors, because systematic risk is a measure of investment risk. In addition to returns, investors always consider the risk of investment, because investors are rational individuals, ie individuals who always consider the trade-off between return and risk. At a certain level of return, investors will tend to choose investments with the lowest risk level. Conversely, at a certain level of risk, investors tend to choose investments with the highest return rate. The purpose of this paper is to analyze the influence of the financial information on the systematic risk of stock manufacturing companies listed on the Indonesia Stock Exchange over a period of five years from January 2011 to December 2015. The financial information is measured in four accounting variables, i.e. financial leverage, liquidity, profitability, and firm size. The results of data analysis using multiple linear regression method to prove that at the 0.05 level only variable sized companies that significantly influence systematic risk. Meanwhile, the variable financial leverage, liquidity, and profitability does not affect the systematic risk. The results showed inconsistencies with the results of several previous studies. This inconsistency may be due to measurement problems variable accounting, the implementation period of the study, and the use of different research samples.