Individual Investment Decisions Research Articles

The relevance and influence of social media posts on investment decisions of young and social media-savvy individuals: An experimental approach based on Tweets

We conducted an experiment to examine the role of positive and negative tweets (generated by AI) on investment behavior of young and social media-savvy individuals, comparing them with provided historical and fundamental financials. Through mediator analysis, we discovered that positive tweets have a significantly positive mediating effect on investment amounts, while negative tweets have a negative impact. Importantly, we found that this effect is not primarily driven by the perception of the tweets; rather, positive tweets influence individuals’ perception of a company’s financials which is the most influencing factor in individuals’ investment decision. In this manner our study contributes to the existing literature by (1) proving evidence for a causal effect of social media investor sentiment on investment behavior on capital markets and especially (2) focussing how the influence channels are built.

Factors Affecting Stock Investment by Individual Investors on the Indonesia Stock Exchange

This study aims to examine the factors that influence individual investors in investing in stocks on the Indonesia Stock Exchange. The factors studied and suspected of influencing individual investor decisions are financial literacy, risk perception and herding behavior. The study also examines the effect of financial literacy on risk perception. The population in this study were college students in Yogyakarta who had invested in the Indonesia Stock Exchange. Respondents were focused on students of the Islamic University of Indonesia with a total of 115 students taken using convenience sampling and snowball sampling techniques. To test the hypothesis, the researcher used a structural equation model analysis tool with the Smart PLS program. The results of the study indicate that financial literacy, risk perception have a positive effect on investment decisions. However, herding behavior does not affect investment decisions, while financial literacy also affects risk perception.

Keputusan Investasi Keuangan dan Fear of Missing Out Sebagai Variabel Mediasi pada Mahasiswa UPN Veteran Jawa Timur

Over the past five years, the percentage growth of investors in Surabaya has experienced extreme fluctuations due to rapid advancements in information development. Easy access to information through social media and the surrounding environment has a significant potential to influence an individual's investment decisions. According to behavioral finance theory, psychological factors influence investment decisions, where information from the environment can lead to herding behavior, while information from social media can drive impulsive investment decisions. This research was conducted on students of UPN Veteran Jawa Timur with a total of 100 respondents. Data analysis used the SEM PLS method. The analysis results show that herding factors and social media contribute to impact on investment decisions. Additionally, the fear of missing out (FoMO) proves to be an influential mediator between social media and investment decisions. These findings underscore the importance of understanding psychological factors in investment decision-making in the digital era.

Factors Affecting Investment Decisions of Individuals: A Comparative Study Between Developed and Emerging Markets (The Case of Jordan)

This study aimed to analyze the factors influencing individuals' investment decisions in Jordan, comparing emerging markets (such as Jordan) and developed markets (such as Dubai). The sample included 100 individual investors (50 from Jordan and 50 from Dubai), and a 30-item questionnaire covering economic, psychological, social, and technical factors was used. The results showed that economic factors such as inflation and growth significantly influence investment decisions in both markets, but without significant statistical differences, as the T-statistic value for economic factors was 0.8665 and the P-value was 0.3883. On the other hand, psychological factors were more influential in developed markets, as the T-Statistic showed a value of -4.3778 and the P-value was 0.00003, indicating that Dubai investors bear more risks than Jordan. Technical factors significantly impacted developed markets, as the F-statistic value was 9.623 and the P-value was 0.0025. In contrast, the study showed that investors in emerging markets face more significant challenges compared to developed markets, with a T-Statistic of 6.6154 and a P-Value of 0.0000000019. The study recommends increasing government support to enhance political and economic stability in emerging markets to mitigate investor challenges. It also recommends enhancing the use of technology in investing in emerging markets, and improving financial education to encourage informed risk-taking. In addition, it is suggested that regulators in developed markets adopt strategies that support greater transparency and clarity of investment opportunities to facilitate decision-making.

LOSS AVERSION: THE UNSEEN FORCE SHAPING INVESTMENT DECISIONS

This research paper aims to investigate the profound impact of loss aversion on individual investment decision-making, with a specific focus on its influence on risk preferences. Loss aversion, a key concept in behavioral economics, posits that individuals experience a greater psychological impact from losses than equivalent gains, thereby shaping their decision-making processes. The study employs an empirical approach, utilizing a diverse sample of individual investors to analyze how loss aversion interacts with risk preferences and influences investment choices. The research methodology involves a combination of surveys and data analysis to explore the intricate relationship between loss aversion and risk preferences. By examining real-world investment decisions in various market conditions, the study seeks to identify patterns and behavioral tendencies that emerge when individuals confront potential losses in their investment portfolios. The research design also considers demographic factors, financial literacy, and other relevant variables to provide a comprehensive understanding of the factors influencing investment choices. Ultimately, this study aims to enhance our comprehension of the psychological factors driving individual investment decisions and to inform the development of strategies that mitigate the negative impacts of loss aversion on financial outcomes.

Effect of Behavioural Biases on Investment Decisions of Individual Investors in India

The current study "effect of behavioural biases on investment decisions of individual investors in India" aims to uncover and quantify the influence of behavioural biases on individual investors' investment decisions. The study's goal is to examine the influence of behavioural biases on individual investors' investing decisions. It is discovered that five components are formed from the thirteen items as a consequence of heuristics factor analysis, namely Availability, Representativeness, Overconfidence, Anchoring, and Gambler's Fallacy. The prospective factor analysis also reveals that three components are retrieved and loaded from the eleven items, namely Loss Aversion, Regret Aversion, and Mental Accounting. According to the findings of this study, behavioural biases affect individual investors while making investment decisions in the Indian securities market. Investor behaviour in making investment decisions is influenced to a larger extent by availability, representativeness, overconfidence, anchoring, and loss aversion. To be successful, an investor must first understand his or her own investment behaviour, which begins with recognising and avoiding behavioural biases from their own experiences, followed by setting realistic and achievable goals through a diversifiable portfolio, and taking into account all financial market mechanisms.

Analysis of Behavioral Biases Affecting Investment Decisions of Individual Investors using Analytical Hierarchy Process

Individual investors exhibiting irrational behaviors may encounter a difficult situation in financial markets. Investor trends, also known as behavioral trends, have been introduced under different headlines in different studies. Overconfidence, representation, anchoring, regret aversion, and herding were included in the research study. In this study, it was aimed to determine the order of importance of investor biases of individual investors trading in Borsa Istanbul. For this purpose, a survey questionnaire was applied to individual investors trading in BIST. Analytical Hierarchy Process was utilized in testing the research model. A total of 411 participants contributed to the study. As a result of the study, regret aversion bias and overconfidence bias were the leading biases to which individual investors attached importance. However, the criterion (C41) “I feel sorrow for the long-losing stocks I hold.” was found to rank highest among all sub-criteria. This sub-criterion is part of regret aversion bias. Regret aversion bias was also the main criterion ranking highest among all criteria. Upon considering the other sub-criteria of regret aversion bias; C42, C43, and C44 sub-criteria were found to rank second, fourth, and eleventh, respectively. C12 criterion, which ranked third, was seen to belong to overconfidence bias, and this bias ranked second among the main criteria. This research would contribute to a better comprehension of the behavioral biases that affect the decision-making of individual investors trading in BIST. The obtained results of the study are thought to contribute to the behavioral finance literature.

FACTORS INFLUENCING INDIVIDUAL INVESTORS’ INVESTMENT DECISIONS AT THE DHAKA STOCK EXCHANGE

The goal of the study is to identify the factors affecting individual investors’ investment decisions on the Dhaka Stock Exchange (DSE). To do this, the research also looks at how accounting issues, information obtained from independent sources, financial needs, advocate recommendations, and personal reputation/company reputation compliance may all affect an investor's behavior. Data were collected from Dhaka, Bangladesh. The researcher individually delivered a standardized questionnaire to each respondent in order to collect data. There were 27 items in the survey. SPSS 26 and AMOS 24 are used to analyze the functional data from 300 surveys. The Friedman rank test is used to test the research hypotheses. The study revealed that there does appear to be some association between the factors affecting the DSE investors' decisions to invest. The researcher found that expected dividends, the stock's past performance, collecting information about firms, stock index fluctuations, interest in non-stock investment, investment diversification, obtaining borrowed funds easily, broker recommendations, family members’ opinions, friend or coworker recommendations, the company's public reputation, well-organized financial markets, and the ethics of a firm are the most crucial factors that affect individual investors' investment decisions. The results of this study will help investors comprehend the various choices they will have to make based on their current circumstances and the likely results of each choice. The research will also help the companies identify the factors that will have the biggest impact on investors' behavior in the future, which will affect future strategies and policies.

THE IMPACT OF ARTIFICIAL INTELLIGENCE RECOMMENDATIONS ON INDIVIDUAL INVESTOR DECISIONS

Purpose- Although artificial intelligence technology is a new technology, it affects every aspect of our lives by finding a very fast field of activity. Artificial intelligence technology, which also shows its effect in the field of finance, is seen to have many applications. There are many alternatives in the investment markets, it will take a long time to make a profit in the markets and a certain amount of knowledge is required. People cannot master the data in all markets when they will invest, but technological developments provide the opportunity to invest by storing each data or observing their changes. This study aims to investigate the effects of artificial intelligence technology on individual investor decisions. Methodology- The study consists of individual investors who live in Diyarbakır province and generally make investments. The questionnaire prepared in accordance with the scope of the study was applied to 1800 participants using face-to-face survey method. The 22 statements prepared in accordance with the scope of the study were applied to the participants. The questionnaires that 1616 participants answered correctly and accurately were included in the scope of the study. In order to ensure the reliability of the study statements, Cronbach's Alpha was calculated and this rate was determined as 91%. The answers given to the study statements were transferred to the tables as a result of the analyses. The transferred information was tried to be interpreted. In addition, frequency tables, t-test and anaova analysis were used in the analysis of the study data. Findings- Thanks to artificial intelligence algorithms, which is one of this technology, it analyses the data in the market and enables the investor who wants to invest to trade in the market by giving buy and sell orders. Thus, artificial intelligence technology allows the investor to make more profitable investments by guiding the investor. Conclusion- As a result, it is possible to say that the individual investors participating in the research do not have sufficient knowledge about artificial intelligence technologies, but they have an interest in investing using artificial intelligence technologies. In addition, it has been determined that the older the age, the lower the education level, the higher the income level and the married investors are insecure about investing using artificial intelligence technology.

Fostering The Changing Economic Market Demand from The View of Various Behavioral Social Personal and Economic Transformation: Empirical Evidence from A Developed Country

The key objective of the study is to foster the changing market demand from the view of various social, behavioral, personal, and economic transformations on individual investment decisions at Shanghai and Shenzhen stock markets in China. The study used a questionnaire to survey a total of 345 investors holding stocks of listed companies at both Shanghai and Shenzhen stock exchanges. The results of the study indicate that behavioral factors, personal factors, and market factors have a significant positive impact on individual investor investment decisions in both shanghai and Shenzhen stock markets while social factors have an insignificant negative impact on individual investor investment decisions in both shanghai and Shenzhen stock markets. Chinese stakeholders will understand better the role of various social, behavioral, personal, and markets factors and their impacts on stock market performance at both Shanghai and Shenzhen stock markets. The findings have important insights for various stakeholders i.e. government, regulatory bodies, practitioners, academia, industry, and researchers.

NEPAL’S REAL ESTATE LANDSCAPE: UNVEILING BEHAVIORAL DYNAMICS FOR STRATEGIC INVESTMENTS

This study delves into the intricate dynamics of behavioral biases and their consequential effects on individual investment decisions within the real estate sector in Nepal. Through a comprehensive examination of existing literature, this research identifies prevalent behavioral biases among investors, including the illusion of control, cognitive dissonance, herd instinct, hindsight, and representativeness biases. Employing a descriptive research design, content analysis of scholarly articles elucidates the significant influence of these biases on investment decisions. The findings underscore a strong correlation between behavioral biases and investment choices, with notable biases such as loss aversion, self-attribution, regret aversion, and over-optimism prominently shaping investors’ attitudes towards real estate investments. Moreover, the study highlights the pervasive impact of optimistic outlooks on future returns and the herd mentality, wherein investors are driven by peer actions, contributing to the burgeoning real estate market in Nepal. This research provides valuable insights into the underlying behavioral mechanisms driving investment decisions, offering implications for investors, policymakers, and practitioners in mitigating biases and fostering informed decision-making in the real estate domain.

Financial literacy in predicting investment decisions: do attitude and overconfidence influence?

PurposeThe significance of financial literacy (FL) in deciding how to allocate one’s investment capital has recently attracted much attention from various market participants and stakeholders. The study examines how FL affects individual investors' investment decisions (ID) in emerging markets. Additionally, the study investigates the potential mediating effects of attitude (ATT) and overconfidence bias (OCB) on the association between FL and ID.Design/methodology/approachThe study employed a structured questionnaire to collect data from 311 individual investors in India, using both convenience and snowball sampling methods. The collected data were analysed using Partial Least Square Structural Equation Modelling (PLS-SEM) and processed through SMART PLS 4.0 software to test the study’s hypotheses.FindingsFL alone may not greatly affect ID, but the study enhances understanding of investor behaviour by examining how ATT and OCB mediate the link between FL and ID. The findings imply that FL, combined with positive ATT and overconfidence, empowers individual investors with the knowledge and skills for appropriate decision-making.Practical implicationsThis research would benefit financial institutions, financial experts, and individual investors in India since it enables them to evaluate the causes and biases affecting their IDs and manage their portfolios accordingly. Policymakers should develop appropriate FL programs for investors to make informed decisions to achieve financial well-being.Originality/valueThe paper is exceptional in its approach as it delves into the mediating function of ATT and OCB in the intricate association between FL and ID. This innovative approach sets it apart from other studies in the field, making it a unique contribution to literature.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-05-2023-0370

Investment Decisions of the Individual Investors in the Capital Market of Bangladesh

Investment decisions of the individual investors in the capital market are influenced by various factors. Main objective of this study is to find out the influences of the factors on investment decisions of individual investors in the capital market in Bangladesh. A highly structured questionnaire has been used to collect primary data from 384 individual investors who are traded in the Dhaka Stock Exchange (DSE). The study respondents have been selected at a simple random method. Analysis of variance (ANOVA), multiple regression model, graphs, charts and tabular analysis have been used to analyze collected data and to test hypotheses of the study. The results showed that EPS has positive influence (β=0.0682, t=1.2439 and p=0.2143, test of hypothesis 2) on investment decisions and rank of EPS is 4 with mean score of 3.8099 and S.D=0.5087 (table 3). It has also found that dividend has positive relationship (β=0.0590, t=1.1054 and p=0.2697, test of hypothesis 3) with investment decisions and dividend is ranked 6 with mean score of 3.5755 and S.D=0.5593 (table 3). Accordingly, P/E ratio has a negative influence (β =-0.0069, t=-0.1341 and p=0.8934) on investment decisions of the individual investors. Therefore, this study will be very helpful to the individual investors to make correct investment decisions by analysing EPS, dividend trends and P/E ratio of the company.

Determinants of individual investment decision: A moderated mediation model

This study aims to examine the effect of financial self-efficacy, risk tolerance, risk perception, and gender on individual investment decisions using a moderation and mediation approach. In addition, this study also examines the role of risk tolerance in mediating the effect of financial self-efficacy on investment decisions as well as the role of gender in moderating the effect of financial self-efficacy on risk tolerance and investment decisions. The sample used in this study is individuals living in Madura Island who invest in financial and real assets. A total of 416 respondents filled out the questionnaire distributed online. This study uses Partial Least Square-Structural Equation Modeling (PLS-SEM) to test the hypotheses. The results of this study prove that financial self-efficacy, risk tolerance, and gender have a positive effect on individual investment decisions. Meanwhile, risk perception has a negative effect on individual investment decisions. Risk tolerance partially mediates the effect of financial self-efficacy on investment decisions. Furthermore, gender strengthens the effect of financial self-efficacy on risk tolerance and investment decisions. This study provides an understanding of the role of risk in investment decisions. Investors are expected to increase their financial knowledge and control their behavioral biases so as not to get trapped in high-risk investments.

Broadband Internet and the Stock Market Investments of Individual Investors

ABSTRACTWe study the effects of broadband internet use on the investment decisions of individual investors. A public program in Norway provides plausibly exogenous variation in internet use. Our instrumental variables estimates show that internet use causes a substantial increase in stock market participation, driven primarily by increased fund ownership. Existing investors tilt their portfolios toward funds, thereby obtaining more diversified portfolios and higher Sharpe ratios, and do not increase their trading activity in stocks. Overall, access to high‐speed internet spurs a “democratization of finance,” with individuals making investment decisions that are more in line with the advice from portfolio theory.

Jövőbiztos készségek – Várhatóan mire lesz szükség a jövő munkahelyein?

Advances in Artificial Intelligence and robotics have made it possible to automate many high-level cognitive skills, but different jobs and occupations may be affected differently by technological developments. High-skilled occupations are less at risk of automation, as they also require skills and competences that remain important bottlenecks to automation. However, according to OECD 2022 results, the jobs most at risk from automation will not disappear completely, as only 18-27% of the skills and competences required in these occupations are highly automatable. Rather, it is likely that the organisation of work will need to be radically changed and that workers in these jobs will need to retrain as technology replaces workers in many tasks. In my study, I aim to summarise, based on the literature of recent years, the key skills that will potentially equip workers for the diverse workplace demands of the near future, arising from technological developments. I conducted a keyword search of the Scopus database for future jobs, workplaces, occupations, skills, abilities and competences. I narrowed down the search results to the period 2021-2023, English language journal articles, economic and business fields and relevant keywords associated with the articles by the authors. In addition to these articles, I also reviewed the reporting materials of other relevant professional organisations (OECD, World Economic Forum) for the period. The geographical, regional and territorial differentiation of the studies was taken into account. In my findings, I have also discussed the role of universities and other educational institutions in meeting the employability expectations of the Fourth Industrial Revolution in order to ensure that they can provide skills that are as relevant as possible to market expectations. I will highlight the top 69 skills identified in the hospitality industry and their groupings, and the elements of the 4 important skill groups identified for accountancy professionals. I also cover the future-proof skills that entrepreneurs are expected to have. In general, I will describe the appreciation of soft skills based on the academic findings of recent years. The results collected can also serve as useful information for individual human capital investment decisions, organisational training and even the design of training frameworks for educational institutions.

Factors Affecting Bitcoin Investment of Individual Investors

Purpose: This article clarifies the factors influencing individual investors' Bitcoin investments in the Vietnamese stock market. Design/methodology/approach: We employed the Theory of Planned Behavior (TPB) and Technology Acceptance Model (TAM), a comprehensive survey with 300 responses, and quantitative analysis using SmartPLS from December 2022 to March 2023. Findings: The findings reveal that the perceived usefulness of the Bitcoin market, subjective norms, self-efficacy, and herd behavior positively impact the Bitcoin investment decisions of individual investors in Vietnam. Research, Practical & Social Implications: This study provides regulators and relevant agencies with more practical evidence regarding the Bitcoin market, facilitating the formulation of appropriate management policies in an emerging economy. Originality/value: There is a shortage of research on the Bitcoin cryptocurrency investment market from the perspective of individual investors in emerging countries like Vietnam. Therefore, this study tries to shed light on individual investors with a comprehensive and objective overview to consider before making investment decisions. Additionally, the results can offer managers and relevant agencies empirical evidence to promulgate future regulations on the Bitcoin market.

Effect of herding behavior and overconfidence bias on investor’s financial decisions: A case of investment in crypto currency in Pakistan

There are various behavioral aspects that influence the financial decisions of individual investors, such as overconfidence, herding behavior, loss aversion, and regret aversion. Other psychological elements may play a substantial influence in deciding the success or failure of any financial action. The primary aims of the present research article are to examine the effects of overconfidence bias and herding behavior on individual financial decisions regarding crypto currency investment. The markets for crypto currencies are extremely sensitive to any minute or significant changes in the economy, as well as to any changes in the individual behaviors of investors. To achieve these aims, 650 questionnaires were distributed to individual investors employed by various financial institutions, multinational corporations, including oil and gas exploration and production companies, operating in Pakistan, individual investors dealing in stocks, and students regardless of investment size. Purposive sampling was used to choose 311 valid responses from a total of 593. Those investors that engage in crypto currency investments were deemed valid responses. Classifications of investments were outlined, and demographic information was requested from respondents. SPSS-based empirical analysis provided the basis for the conclusions. The primary findings indicate that both overconfidence bias and herding tendency have a favorable and statistically significant impact on investors' financial decisions when investing in cryptocurrencies. In this study's sample, however, the majority of investors were overconfident in their crypto currency investing decisions.

Perceived Behavioral Factors and Individual Investor Stock Market Investment Decision: Multigroup Analysis and Major Stock Markets Perspectives

The study aims to examine the impact of various behavioral biases such are overconfidence, representativeness, availability, anchoring and herding, and their effects on individual investment decisions in the case-developed country context of China. To achieve this, data was meticulously gathered from 362 participants active in the Shanghai stock market. Employing advanced analytical tools, particularly the Smart PLS 3.3.2 software and structural equation modelling (SEM), this study rigorously scrutinized the intricate relationships between behavioral biases and investment decisions. The findings of this study notably reveal that all examined behavioral biases exert a significant positive impact on investment decisions within the Anxin, Haitong, Shanxi, and China Galaxy stock markets. Remarkably, no substantial disparities in the effects of these biases on stock market trading were observed among these markets. Importantly, these findings bear exceptional significance within the context of a developed country like China. The implications extend to a wide spectrum of stakeholders, including government entities, regulatory bodies, practitioners, the academic community, industry professionals, and researchers. Regulatory authorities can leverage these insights to refine their strategies, practitioners can fine-tune their investment advisory approaches, and academia and researchers can build upon these findings to deepen the understanding of behavioral finance in the realm of stock market investments.

Các nhân tố ảnh hưởng đến quyết định đầu tư của nhà đầu tư cá nhân trên thị trường chứng khoán Việt Nam: Nghiên cứu trường hợp sinh viên trường Đại học Kinh tế- Đại học Quốc gia Hà Nội

Financial investment, typically investment in stock markets, has been of great interest to business students. The aim of this study is to identify and measure the impact of different factors that can affect the investment decisions of individual investors in the Vietnamese stock market. The data was collected in June 2023 using a convenience sampling technique on 201 students of the University of Economics and Business, Vietnam National University, Hanoi (UEB) regarding their investment decisions. The results from multivariate regression show that Neutral information exerts the strongest impact on the surveyed students’ investment decisions, followed by Market psychology, Stock information, Company image, and Financial knowledge. However, Individual financial demand is not statistically significant in the regression model. The results of this study suggest that young people should have sufficient financial knowledge and other preparations to maximize return and minimize risk when participating in the Vietnamese stock market.