The nexus between financial literacy, risk perception and investment decisions: Evidence from Indonesian investors

The stock market represents complex systems where multiple agents interact. The complexity of the environment in the financial markets in general has encouraged the use of modeling by multi-agent platforms and particularly in the case of the stock market.
In this paper, an agent-based simulation model is proposed to study the behavior of the volume of market transactions. The model is based on the case of a single asset and three types of investor agents. Each investor can be a zero intelligent trader, fundamentalist trader or traders using historical information in the decision making process. The goal of the study is to simulate the behavior of a stock market according to the different considered endogenous and exogenous variables.

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.

This study applied Altman Z-score model to assess the bankruptcy risk of a set of multidisciplinary enterprises of various types, mainly small and medium enterprises, with data taken from official financial reports of 180 enterprises in Soc Trang province. The binary logistic regression was employed to assess the impact of non-financial and financial factors on the bankruptcy risk of enterprises. The research findings showed that both the non-financial factors such as business area, types and size of the business, the educational level of managers and executors and other characteristics, and the financial factors (indicators) such as earnings before tax, net profit/equity ratio, earnings before interest and tax/total assets ratio, equity/total debt ratio, affect the bankruptcy risk of enterprises. Predicting the bankruptcy risk and measuring its determinants play an important role not only as an effective managing tool of the business, but also as evidence for policymakers to support the sustainable development of business.