Making Investment Decisions Research Articles

How Investment Behaviour of Young Investors? A Case Study on The Indonesia Stock Exchange

This research aims to dig deeper into the investment behavior of young investors on the Indonesian Stock Exchange. This research was conducted in Bali Province, especially the Denpasar City area. The sample was determined using convenience sampling with a total sample of 180 young investors, namely the millennial generation and generation z in Denpasar City. Data was obtained directly from distributing questionnaires via Google Form. The data analysis technique used is SEM-PLS analysis. The research results show that, 1) herding behavior effect investment decision making, 2) heuristic bias has no effect on investment decision making, 3) anchoring bias effect investment decision making, 4) the level of overconfidence an investor has will improve the investment decision making process , 5) herding behavior does not have a significant effect on the level of overconfidence, 6) heuristic bias can increase the level of overconfidence, 7) anchoring bias can increase the level of overconfidence, 8) overconfidence cannot increase the effect of herding behavior to improve investment decisions, 9) overconfidence can increasing the effect of heuristic bias to improve investment decisions, and 10) overconfidence can increase the effect of anchoring bias to improve investment decisions. Future researchers can further examine overconfidence in mediating the effect of herding behaviours on investment decision making, and the effect of heuristic bias on investment decision making. Young investors in Denpasar City are advised to increase their knowledge and investment skills in the capital market to reduce the risk of bias in making investment decisions.

Pengaruh Herding Bias, Overconfidence Bias, dan Cognitive Dissonance Bias terhadap Keputusan Investasi

The purpose of this study is to analyze investor behavior influenced by herding bias, overconfidence bias, and cognitive dissonance bias on investment decision making. Investors were given a questionnaire as part of the quantitative data collection for this study. This study used data from a sample of 102 investors who had all been active in the capital market for at least one year, had traded, and had invested at least twice. Several statistical analyses, including convergent and discriminant validity tests, composite reliability, and significance tests, were performed on the data collected for this study. Information from this study was statistically analyzed using the SmartPLS 3.0 program. The results of this study indicate that Herding bias does not significantly affect investment decision making, overconfidence bias has a positive and significant effect on investment decision making. Cognitive dissonance bias does not significantly affect investment decision making. In this study, investors are expected to pay more attention to the latest information, suggestions, and input from other parties as considerations in the future in making investment decisions. Investors are expected to be able to control themselves in the decision-making process by considering the risks more

Behavioral Insights Into Investment Decision-Making: Evidence From the Nepal Stock Exchange

This paper provides a reliable foundation for investigating how people's behaviors influence investment decisions. The study surveyed 286 individual investors who participated in the Nepal Stock Exchange, employing a purposive sampling procedure and self-administered structured Likert scale questionnaire. The results indicate that behavioral factors, including stock affordability, information availability, third-party opinions, and herding effect, significantly influence individual investors’ rationality in making investment decisions. The study concludes that in a developing and expanding environment, factors such as disposable income, market trends, and external opinions notably shape investment decisions when individuals choose to invest in the stock market. The alignment of our findings with existing literature reinforces the robustness of our results. The implications of these findings extend to investors, financial advisors, and policymakers alike. Recognizing the influence of behavioral factors can aid in developing strategies to promote informed decision-making and mitigate the adverse effects of herding behavior.

PERAN PROFITABILITAS DALAM MEMODERASI KEBIJAKAN DIVIDEN DAN CORPORATE SOCIAL RESPONSIBILITY (CSR) TERHADAP NILAI PERUSAHAAN PADA SEKTOR INDUSTRI BARANG KONSUMSI YANG TERDAFTAR DI BEI PERIODE 2020-2022

Every individual needs to have management in their activities to achieve their goals. Likewise, with organizations, management is needed to run the company well. This helps investors make investment decisions by assessing the value and state of the company as a whole. The consumer goods industry is exciting because all its products are always needed daily. This sector produces products that can support the entire community, such as food, drinks, medicines, and others. This study aimed to analyze and test the role of profitability in moderating dividend policy and corporate Social Responsibility (CSR) on firm value. The population in this study was the Consumer Goods Industry Sector, with 124 companies and a sample of 11 companies. The sampling technique was determined by purposive sampling. Data analysis and hypothesis testing were conducted using Structural Equation Analysis—partial Least Square (PLS-SEM). The results of research hypothesis testing using the Smart PLS 3.0 application show that dividend policy has a significant positive effect on firm value, Corporate Social Responsibility (CSR) has a negative but insignificant effect on firm value, profitability significantly moderates the impact of dividend policy on firm value, profitability does not considerably moderate Corporate Social Responsibility (CSR) on firm value

Funding Innovation and Risk: A Grey-Based Startup Investment Decision.

As found in behavioral decision theory, venture capitalists (VCs) rely on heuristics and bias, owing to their bounded rationality, either by limited alternatives or information and resources. India's booming startup scene challenges VCs in decision-making owing to information overload from numerous evolving ventures, which hinders informed judgment. VC investment behavior, due diligence, and cognitive factors related to decision-making have always drawn the attention of researchers. We provide an alternative approach for an optimal decision by VCs by identifying the attributes that influence investment or funding decisions at an early stage of a venture in tech-based industries. Through a literature review, we identify eight attributes, both on internal and external criteria, that venture investors consider when making investment decisions. Based on interviews with 20 experts, we further identify eight key tech-based sectors. Using grey system theory, we then determine the rankings of eight tech startups for investors' early-stage investment decisions. This study presents a linguistic variable-based approach of grey numbers to decide weights and ratings, the grey possibility degree to compare and rank different tech startups, and based on the results, suggests the ideal tech startup. We find that agritech ranks first; thus, investors should prefer venturing into such startups for early-stage investment. E-commerce and edutech ranked second and third, respectively, followed by electric vehicle infrastructure, insurtech, fintech, space tech, and software as a service.

Technical and fundamental analysis of insurance stock prices on the Indonesian Stock Exchange (2018–2022)

Purpose: This study was conducted to determine the influence of fundamental (ROA, TATO, DER, NPM, and EPS) and technical (past share price, share volume, and past share volume) variables on share prices. in insurance companies listed on the IDX. Method: This study uses secondary data in the form of panel data, namely a combination of time series data for quarterly periods for five years, namely 2018-2022 and cross-sectional data from 11 insurance companies on the Indonesia Stock Exchange. The relationship between the research variables was tested using a panel data regression analysis. Results: The t-test results from the fixed effects model show that TATO and DER have a positive and significant influence on stock prices. ROA, NPM, and EPS do not significantly influence share prices. Past share prices and share volume have a significant positive influence on stock prices, whereas past share volume has a significant negative influence on share prices. The F-test results from the fixed effects model show that there is a significant influence of the independent variables, namely fundamental and technical variables, on stock prices. Limitations: This study only analyzes insurance companies (other than reinsurance) listed on the IDX from to 2018-2022, issue quarterly financial reports continuously from to 2018-2022, and have never been delisted during that period. Contribution: The contribution of this research is that it considers investors in making investment decisions, especially in selecting insurance company shares.

The Influence Of Free Cash Flow, Profitability and Growth Opportunity On Dividend Policy

Dividends are one of the returns expected by shareholders apart from capital gains. Dividend distribution to investors gives a positive signal to investors for making investment decisions. The aim of this research is to analyze and explain the influence of free cash flow, profitability and growth opportunity on dividend policy. The number of samples in this research was 33 mining sector companies in 2018-2022. Data collection uses non-participant observation methods. The data analysis technique used is multiple linear regression analysis. The results of the analysis show that free cash flow has a significant positive effect on dividend policy, profitability has a significant positive effect on dividend policy and growth opportunity has a significant negative effect on dividend policy. The theoretical implication of this research is to provide knowledge and strengthen dividend policy theories related to free cash flow, profitability and growth opportunity. The practical implication of this research is that information on profitability and free cash flow produced by the company is used by the company to determine future investment directions or distribute dividends to investors as a form of good perception in the eyes of investors.

Modeling and optimization of costs associated with the development of clustered organizational management structures in construction companies

The article aims to examine models and methods of cost optimization associated with the development of clustered organizational structures in construction companies. The research methodology involved an analysis of existing approaches, simulation modeling, and econometric equation analysis. As a result, different approaches to cost estimation and optimization applied in the construction sphere are presented. Particular attention is paid to the development of complex models and their optimization under the conditions of uncertainty through simulation modeling of various scenarios of cluster organizational structures in construction companies. The analysis also includes an assessment of the advantages and disadvantages of econometric semi-linear dynamic equations and the feasibility of their application. The discussion section emphasizes the importance of integrating different optimization methods to achieve the most optimal outcome in the management of construction companies. Further research directions are outlined. The results can be relevant when formulating development strategies and making investment decisions in the construction sphere. The research conclusions confirm the significance of applying modern cost optimization methods to improve the management efficiency of construction companies and their competitiveness in the market of construction services.

Dividend Policy as a Moderating of the Effect of Dividend Announcement on Stock Price in Indonesian Firms

This goal of this study is to investigate how dividend announcements affect the stock price of the company on the cum and ex-dividend dates. This study also explores the possibility of dividend policy reduce the effect of dividend announcements on stock prices on the cum and ex-dividend dates. The researcher used the unit analysis of manufacturing companies listed on the Indonesia Stock Exchange (IDX) for the period of 2013 - 2018. The 2019 - 2021 period is not observed due to the present of Covid Pandemic. The findings are that the dividend announcements at cum and ex-dividend dates have positive impact on stock prices. Dividend policy weakens the impact of dividend announcements on stock prices at cum and ex-dividend dates. The dividend announcement at cum and ex-dividend dates varies across companies. This study does not use the event study method. This study has a significant implication, not only for business officials and policy makers but also for investors who directly decide how to plan their portfolio in the future as consideration in making investment decisions. There is no research in Indonesia that moderates dividend policy for the effect of dividend announcements on the cum and ex-dividend dates on stock prices, so a descriptive study is required to fill this gap.

Capital Asset Pricing Model (CAPM) Analysis: Technology Sector Stock Conditions Before and During the Pandemic

The COVID-19 pandemic made people more active in saving, such as investing in the capital market. Stocks in the technology sector were excellent stocks because the trading volume increased by up to 7.3 times during the pandemic. The Capital Asset Pricing Model (CAPM) was a model to see the expected rate of return and aimed to assist investors in making investment decisions. CAPM used beta (β) to measure the sensitivity a stock or portfolio is to market movements. Beta indicates the tendency of an asset's return to react to fluctuations in the overall market. This study aimed to look at differences in technology sector stocks in the period before and during the pandemic using the CAPM method and paired t-test. The research using a purposive sampling method. A quantitative descriptive method was used in this study and used secondary data in the form of financial statements of technology sector companies listed on the Indonesia Stock Exchange. Based on the results of the study, seven stocks had an average negative return before the pandemic and positive returns during the pandemic. There was one efficient stock in the pre-pandemic period and six inefficient shares, and seven shares were classified as efficient shares during the pandemic. The results of the paired t-test showed that there was a significant difference between individual returns before and during the pandemic.

THE IMPACTS OF INNOVATION EFFICIENCY AND GOVERNMENT SUBSIDY ON EXTERNAL FINANCING: EVIDENCE FROM CHINA

Subsidies from the government and financial resources from external investors play critical roles in supporting firm innovations. We develop a model to empirically investigate the role of firm innovation efficiency in government subsidy allocations and the joint effect of innovation efficiency and government subsidies on external investor decision-making in China. We collect panel data from 337 firms in China over ten years (2011–2021). The results show an inverted U-shaped relationship between innovation efficiency and government subsidies. Both government subsidies and innovation efficiency are positively associated with external financing. Government subsidies positively moderate the impact of innovation efficiency on external financing. The findings provide empirical evidence of the complex relationships among firm innovation efficiency, government subsidies and external financing. In this study, insights are provided into how Chinese government officials and external investors interpret signals of firm innovation. The findings of this study can also be used by managers to attract financial resources and by investors to make investment decisions.

The Effect of Over-Confidence on Jiwasraya's 2017-2020 Payment Defaults

Overconfidence is a term that refers to the human tendency to estimate their abilities, knowledge, or results with more confidence than they should. PT. Jiwasraya Insurance (Persero), the oldest insurance company in Indonesia which is owned by BUMN, was declared to have failed to pay its customers' policies in 2020. This failure to pay was caused by errors in managing customer funds, namely by collecting funds for JS Products. Saving Plan and investing with customer funds in high risk stocks. The purpose of this research is to find out why Jiwasraya experienced payment failure. Therefore, the variable prices of high-risk shares purchased by companies from 2017 to 2020 is used as a secondary variable. Secondary data was obtained from the Indonesian Stock Exchange and the Financial Services Authority. This study uses. Vector Auto regressive (VAR) analysis technique with Stata/IC 15.0 software. The research results show that it is the Jiwasraya company's share price that influences Jiwasraya's shares in the short term. In the long term, it shows that the share price of Semen Baturaja does not have a significant effect on Jiwasraya's share price. Meanwhile, the share price of the West Java Development Bank has a significant negative effect on Jiwasraya's share price. Then, PP Properti's share price has a significant positive effect on Jiwasraya's share price. The results of this research can be used as consideration for companies and investors in making investment decisions so as not to take high-risk actions because of too high self-confidence.

Impact of foreign ownership on stock return volatility of financial firms in Vietnam

The paper investigates the impact of foreign ownership on the stock return volatility of financial firms in Vietnam. Applying panel regression models on a year-end research sample of 23 banks and financial firms listed on stock exchanges in Vietnam from 2017 to 2022, the study assures the negative relationship between foreign ownership and the stock return volatility, implying that increasing foreign ownership reduces the volatility of stock returns of financial firms. Our study’s novelty is reflected in following aspects. First, our study, examining about the foreign ownership's impact on stock returns’ volatility in emerging stock market conditions, will enrich this research field by contributing additional empirical evidence to the field through a concrete and well-designed research. Additonally, our research findings not only provide useful information about the volatility of those influential shares in mentioned industries coupled with its determinants but also support investors and policymakers in making investment decisions informedly as well as reviewing suitable regulations for investors and capitals from foreign countries, which is a critical aspect in helping Vietnam's stock market to expand more steadily and sustainably.

Determinants of Socially Responsible Investment (SRI) Intention

There has been a recent surge of interest in socially responsible investment, attracting attention from all industries, including investors. Nevertheless, the factors that impact one's attitude and attention towards SRI remain relatively unexplored. Hence, this study aims to identify important factors that shape the attitude and attention of consumers when making investment decisions in the stock market. The data is obtained from investors who are making investments in the Pakistani stock exchange. The data analysis employs the technique of partial least squares structural equation modelling (PLS-SEM). The study findings indicate a substantial relationship between collectivism, knowledge, and SRI bias, and the attitude towards SRI. However, there is no significant association between perceived danger and attitude towards SRI. Attitude exhibits a robust and meaningful correlation with SRI.

Information-analytical support to business processes for making investment decisions

The object of this study is the business processes of making an investment decision based on determining the state of the investment attractiveness of the enterprise. To support the adoption of investment decisions under the conditions of a fast-moving and dynamic environment, information-analytical support to the algorithm using intelligent information systems has been developed. The relevance of the study is justified by the continuous development of digitization processes, in particular in the financial realm. The traditional approach to the reproduction of management decision-making technology is complemented by the tools and methods of intelligent information systems. In particular, the modeling of the target subject area using UML made it possible to determine the main requirements for the projected information-analytical support (user roles, available options, types of connections and the logic of interaction between them). SQL queries to the information database speed up the process of processing and obtaining the necessary data samples. Business intelligence (BI) tools are used to create interactive reports that provide access to operational financial data. At the stage of making investment decisions, these tools make it possible to study a wide range of analytical data based on the results of the assessment of the investment attractiveness of the enterprise obtained at the previous stage of the developed algorithm. Monitoring of the main indicators of the enterprise's investment attractiveness is carried out on the basis of a dashboard, an information panel (display) with graphs, tables, and figures that clearly reflect the dynamics and rates of change of the investigated indicators. The results of the use of algorithmic information-analytical support make it possible to quickly prepare and make investment decisions. A visual description of the projected information-analytical support, visual content of the results of investment analysis, the validity of decisions due to the use of reliable retrospective information from an aggregated database

Contradiction "risk-income" and ways to solve it in the process of making investment decisions

Contradiction "risk-income" and ways to solve it in the process of making investment decisions

Research on Factors Affecting Digital Marketing Investment Activities in Small and Medium Enterprises in Hanoi City

In the ever-evolving technology landscape, digital marketing has been thriving globally. Investing in digital marketing activities is crucial for businesses in general and SMEs in particular. The study selects the scope of small and medium enterprises (SMEs) in Hanoi city to evaluate factors affecting digital marketing investment activities in small and medium enterprises. The study uses both qualitative and quantitative methods. The research results identify five factors affecting digital marketing investment in small and medium enterprises (including leadership capacity, quality of human resources, financial ability, corporate culture and scientific and technological capacity). The research results can serve as a basis for solutions to improve digital marketing investment activities in small and medium enterprises, as well as valuable information for reference for small and medium enterprises in Hanoi in making investment decisions.

One-way ticket to the moon? An NLP-based insight on the phenomenon of small-scale neo-broker trading

We present an Natural Language Processing based analysis on the phenomenon of “Meme Stocks”, which has emerged as a result of the proliferation of neo-brokers like Robinhood and the massive increase in the number of small-scale stock investors. Such investors often use specific Social Media channels to share short-term investment decisions and strategies, resulting in partial collusion and planning of investment decisions. The impact of online communities on the stock prices of affected companies has been considerable in the short term. This paper has two objectives. Firstly, we chronologically model the discourse on the most prominent platforms. Secondly, we examine the potential for using collaboratively made investment decisions as a means to assist in the selection of potential investments.. To understand the investment decision-making processes of small-scale investors, we analyze data from Social Media platforms like Reddit, Stocktwits and Seeking Alpha. Our methodology combines Sentiment Analysis and Topic Modelling. Sentiment Analysis is conducted using VADER and a fine-tuned BERT model. For Topic Modelling, we utilize LDA, NMF and the state-of-the-art BERTopic. We identify the topics and shapes of discussions over time and evaluate the potential for leveraging information of the decision-making process of investors for trading choices. We utilize Random Forest and Neural Network Models to show that latent information in discussions can be exploited for trend prediction of stocks affected by Social Network driven herd behavior. Our findings provide valuable insights into content and sentiment of discussions and are a vehicle to improve efficient trading decisions for stocks affected from short-term herd behavior.

Improving the prediction of firm performance using nonfinancial disclosures: a machine learning approach

PurposeThe purpose of this study is to test whether the prediction of firm performance can be enhanced by incorporating nonfinancial disclosures, such as narrative disclosure tone and corporate governance indicators, into financial predictive models.Design/methodology/approachThree predictive models are developed, each with a different set of predictors. This study utilises two machine learning techniques, random forest and stochastic gradient boosting, for prediction via the three models. The data are collected from a sample of 1,250 annual reports of 125 nonfinancial firms in Pakistan for the period 2011–2020.FindingsOur results indicate that both narrative disclosure tone and corporate governance indicators significantly add to the accuracy of financial predictive models of firm performance.Practical implicationsOur results offer implications for the restoration of investor confidence in the highly uncertain Pakistani market by establishing nonfinancial disclosures as reliable predictors of future firm performance. Accordingly, they encourage investors to pay more attention to these disclosures while making investment decisions. In addition, they urge regulators to promote and strengthen the reporting of such nonfinancial information.Originality/valueThis study addresses the neglect of nonfinancial disclosures in the prediction of firm performance and the scarcity of corporate governance literature relevant to the use of machine learning techniques.

Peer Effects in Investment: Evidence from Early-tenure CEOs

This study examines whether Chief Executive Officers’ (CEOs) incentives to rely on peers’ investments vary over their tenure at a firm. Newly appointed CEOs (hereinafter ‘early-tenure CEOs’) often encounter a lack of firm-specific information and are subject to rigorous evaluation. Therefore, when making investment decisions, they tend to seek more efficient and readily accessible external information, such as investment decisions made by peer firms. We find that the positive association between a focal firm’s investments and those of its peers (termed ‘peer effects’) is stronger when early-tenure CEOs manage the focal firm. Furthermore, this peer effect is stronger when managers possess greater incentives to rely on peers (i.e., lower ability and stronger monitoring) or when firms’ investment information quality is poorer (i.e., early stage of their life cycle, greater investment volatility and uncertainty). We also find that geographic proximity and the sharing of common board members or auditors may serve as mechanisms facilitating peer effects. Finally, we document improved future performance for early-tenure CEOs who align their investment decisions with those of peers. This study contributes to the existing literature by illustrating that manager-level characteristics can influence heterogeneity of peer effects and underscores the benefits of peer effects.