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Environmental, social, and governance (ESG) issues have recently received much attention. This research investigates the daily performance of socially responsible investment (SRI). To do that, the authors construct portfolios consisting of the SRI, non-SRI, and matched non-SRI. The portfolios can be compared with the market benchmark based on α adjusted asset pricing models. Due to using high-frequency data, the authors use ARCH/GARCH to deal with time-varying volatility. Moreover, the authors also utilized Fama–MacBeth pooled regression to confront the SRI stocks and the non-SRI counterpart. In sum, the findings of this study confirm the superior performance of the value-weighted (VW) SRI portfolio against the market. On a head-to-head basis, the SRI yields a higher return than the non-SRI. The results are robust in the quarterly analysis. It is essential for investors that put their money in socially responsible (SR) portfolios to either promote sustainable development or chase a return on it.

The first alternative is to enrich shareholding by management. The basic theory of this research is the agency theory. This study aims to examine the institutional ownership, dividend policy, debt policy, and risk that are interconnected directly or indirectly. The research sample was a non-financial company from 2010 to 2014. Four variables will be tested using Two-stage Least Square (2SLS) in the SPSS application. The result of this study represents the overall interdependency relationship among institutional ownership, dividend policy, debt policy, and risk. The research outcome signifies an interdependency relation for endogenous variables, even if some exogenous variables have no significant relation. In addition, the effects of substitution between institutional ownership and dividend policy, debt policy and dividend policy, and institutional ownership and risk. Meanwhile, institutional ownership and dividend policy, risk and dividend policy, and risk and debt policy have no substitution effect.

Environmental degradation is a global concern that results from massive economic activities. Carbon dioxide (CO₂) emissions are one of the environmental degradation indicators. This study investigates the impact of population, oil consumption, international tourist arrival, and corruption on CO₂ emissions in ASEAN’s five developing countries of Malaysia, Indonesia, Thailand, Philippines, and Vietnam from 1998 to 2017. This study employed panel Fixed-effect (FE) regression to estimate the panel data generated by British Petroleum and World Bank. The result revealed that the population has a significant positive effect on CO₂ emissions. Furthermore, oil consumption has a significant positive effect on CO₂ emissions. Meanwhile, the effect of tourism and the corruption perception index (CPI) as a proxy of corruption on CO₂ emissions was positive but not significant. Authorities should construct such policies to reduce CO₂ emissions by applying low-carbon technologies, green mass transport, and creating less corrupt behavior.

In this study, the authors propose a VaR method for evaluating the market risk of investing in the stock portfolio of Pension Institutions. The data used for this research is hypothetical data, including the exposure or the amount of value invested by Pension Institutions in their stock portfolio. With the VaR – Monte Carlo simulation, the authors know the loss level will occur when the Indonesian economy or market conditions deteriorate. The lost value amount is determined in the Rupiah value, according to the confidence level or the desired percentile level. The results revealed that at the 5% (99.95%) percentile level of confidence, a pension fund with an investment value of IDR 4,070,000,000 would suffer a loss of IDR 1,110,000,000. While at the 1% (99.995%), the loss rate will be of IDR 1,480,000,000. The conclusion is that the results of this study are useful for Pension Institutions in managing their asset portfolios with the VaR model.

The aviation business has had a difficult time due to the COVID-19 pandemic in the past year. As a result, people worldwide are limited to travel which causes a decrease in turnover from a business in the transportation sector, particularly aviation. This condition, indeed, also affects the company’s stock price. This study examines the volatility of stock prices as an initial indication of what has happened and looks at future projections. The method used in this study is the autoregressive integrated moving average (ARIMA) in achieving research objectives. The findings found that the autoregressive combined moving average on AR1 and MA1 can show conditions based on past data and predict the projection of its volatility. The aviation business is still considered to survive with daily stock prices that are relatively positive and stable for the next upcoming period.

This chapter focuses on testing optimal capital structure theory: The role of intervening variable debt to equity ratio (DER) on the influence of the financial performance, Ownership Structure of Independent Board of Commissioners (IBCO), Audit Committee (ACO), and Institutional Ownership on Firm Value. The research design was explanatory research using path analysis. Using purposive sampling, 61 manufacturing companies, observation period from 2014 to 2018 with 286 N samples. The research novelty empirically can prove the role of intervening variable DER on the effect of return on assets (ROA) on firm value and shows the market response to the ROA is fully reflected by DER, indicating the existence of an optimal capital structure. The role of DER on the effect of ROE and IBCO on firm value is a partial mediation with the inverse direction. This phenomenon shows that the mechanism of forming a balance between the responses of investors and creditors relates to debt financing.

This chapter investigates the effect of financial performance and corporate governance on market performance, using evidence from the companies listed on the IDX30 Index of the Indonesia Stock Exchange (IDX) from 2015 to 2018. The authors use six main independent variables and one dependent variable, controlled by using control variables in the regression analysis. Ordinary least square (OLS) regression methods are used to model the relationship between the dependent variable and the independent variables. The results show that the current ratio (CR) and Board Size (BS) have a significant negative effect on stock return (SR). In contrast, the quick ratio (QR) and debt to equity ratio (DER) have a significant positive impact on SR. Both the debt to asset ratio (DAR) and Independent Board of Commissioners (BOC) have an insignificant effect on SR. This evidence suggests that the CR, QR, DER, and BS are essential factors affecting SR.

This study aimed to know the effect of cross-sectional risk, which comprises business-specific risk and stock market volatility, as a variable for estimating macroeconomic risk in Indonesia. This study observes public companies in Indonesia and Indonesian macroeconomic data from 2004 to 2020. In this study, the author uses term spread as the dependent variable that reflects macroeconomic risk. The cross-sectional risk comprises financial friction (FF), cash flow (CF), debt–service ratio, and stock market volatility as independent variables. By using the Autoregressive Distributed Lag (ARDL) Model method, this study shows that business-specific and stock market risk can estimate macroeconomic risk, so that it becomes an early signal of economic shock, such as recession or high inflation, in the future. The model in this study also examines the cross-sectional risk relationship with other macroeconomic indicators, such as the Consumer Confidence Index (CCI), money supply (M0), and Indonesia’s trade balance (TB).