Stock Investment Research Articles

Does religiosity affect stock investors’ herding behaviour? Global evidence

We investigate if religiosity promotes herding among stock market investors. In a global sample of 21 markets over the period 2006–2018, increasing religiosity fosters herding only when the absolute religiosity level is relatively high. At low levels, an increase in religiosity has the opposite effect, promoting anti-herding. Our finding that changes in religiosity, depending on its level (high versus low), exert opposing effects on herding helps to understand contradictory findings in prior literature. Religiosity further induces more herding when economic freedom is low and the state is either impotent or corrupt, and promotes anti-herding when institutional quality is high.

THE EFFECT OF PROFITABILITY AND LEVERAGE ON THE TIMELINESS OF FINANCIAL REPORTING

Punctuality is an important trait that shows the ability of the organization to compile and present financial statements according to the grace period, because information in financial reporting that is in accordance with the deadline is more useful for stock investors when making investment decisions. The purpose of this study is to evaluate how profitability and leverage affect the timeliness of financial statements. In this study, profitability is assessed through return on assets (ROA) and leverage is analyzed using debt to equity ratio (DER). This type of study is a quantitative set that utilizes secondary information in the form of financial statements per year from the company obtained through the www.idx.co.id site. Participants in this study are property and real estate sub-sector business entities listed on the Indonesia Stock Exchange for the period 2020-2022. The respondents of this study were 69 organizations that met 4 respondent requirements using purposive sampling techniques. The test was carried out through the use of logistic regression analysis with SPSS software version 18. The partial presumptive test output shows that profitability and leverage have a significant positive impact on the timeliness of financial statements. The findings of the coefficient of determination test explain that the percentage of the influence of profitability and leverage for the timeliness of financial statements is 10.2% and the remaining 89.8% is impacted by other independent elements that have not been studied in this study

Impact of Psychosocial Factors on Sustainability of Stock Investors’ Inclination: A Case of the South Pacific Stock Market

Previous research has documented that psycho-cognitive resources and socioeconomic status have significant influences on investment behavior in financial assets. Drawing from the positive psychosocial perspective, I hypothesized that positive enterprising personality mediates the influence of individual characteristics on investment behavior. I tested this hypothesis in the Structural Equation Modeling (SEM) framework using a purposive sample of potential stock investors in Fiji. The theoretical framework and analytical procedures, I introduce here, can also be used to discover additional factors influencing investment inclination and then estimate the predictors of stock market investments in other developing countries with similar socioeconomic contexts, for example, Sri Lanka. The results revealed that four latent factors (Intuition, Education and knowledge, Sociocultural norms, and Enterprising personality) are distinct dimensions of investment inclination together with the maturity factor (Age) towards stock investments. The findings could broaden our understanding about the direct and indirect impact of psychosocial characteristics on stock market participation through positive, personal resources such as an enterprising personality. The findings will be useful for financial service providers and regulators in designing educational programs for different levels of maturity, knowledge, and education, to enhance enterprising personality qualities amongst people generally, and inculcate positive attitudes towards stock investments in the young through high school curricula and mass-awareness programs.

Investment in Malaysian Stock Market and the Inflation Rate

The increasing concern on the rising inflation rate in Malaysia had motivated the need for the study on the investment return for the Malaysian stock market to compare against the inflation rate in Malaysia. The study had reflected towards the literature review to identify the potential pattern for the study creating the expectations to observe the positive correlation between the inflation rate and the portfolio return of the stock investment as well as the higher KLSE market index growth rate over the inflation rate in the country. With this, the resign design through the quantitative method had been introduced with reference to the application of the correlation analysis and regression analysis to test for the hypothesis for the study. In addition, the comparative analysis will be used as part of the quantitative analysis to understand the potential difference in the inflation rate against the KLSE market index growth rate. The outcome for the quantitative findings had concluded that there is very weak negative correlation being observed between the two variables, but the regression analysis failed to show any significant in the relationship between the two variables disagreeing with the previous studies. On the other hand, the KLSE market index growth had been significantly higher than the inflation rate in Malaysia suggesting that the stock investment in Malaysia could be beneficial for the investors to beat the inflation rate in Malaysia. With this, the objective of the study is being achieved with the suggestion towards the potential future research study being proposed for the future researchers.

Herding behavior, information type, and overconfidence bias: an experimental study on novice investors’ investment decisions

Research aims: By the end of 2023, Indonesian Central Securities Depository data revealed a significant increase in the number of investors dominated by millennial investors (56.41%). They are categorized as novice investors who have distinctive characteristics from professional investors. This study, thus, aims to examine whether herding behavior dominates the characteristics of novice investors and whether information type and overconfidence bias affect the herding behavior of novice investors.Design/Methodology/Approach: This study used a quasi-experimental 2x2 mixed design on 42 student participants who were members of the Capital Market Study Group. The data obtained were then tested using non-parametric statistics.Research findings: The test results uncovered that herding dominated the investment behavior of novice investors. This behavior was supported by the information type that participants paid attention to in making decisions. However, testing for overconfidence demonstrated that this variable was not the cause of novice investors' herding behavior.Theoretical contribution/Originality: The results of this study contribute theoretically to the investment behavior of novice investors by strengthening the argument that they tend to behave herding when making stock investment decisions. Testing with an experimental design allows researchers to confirm that such herding behavior is reinforced by the preference for the information type they use in decision-making. The results also provide insight into the fact that the overconfidence level of novice investors may be different from that of professional investors.Practitioner/Policy implication: The tendency of herding behavior of novice investors needs attention from the Financial Services Authority as a regulator to consider protection for novice investors who dominate the number of investors in the capital market.Research limitation/Implication: The tests in this study employed non-parametric statistics, which are not as good as parametric tests, so the study results should be understood wisely. Future research needs to consider the adequacy of the sample and use capital market groups in several universities to improve sample quality.

The impact of Chinese public expenditures on household investment in risky financial assets: Evidence from a national survey

AbstractUsing data from the 2012, 2013, 2015, 2017, 2018, and 2021 Chinese General Social Survey (CGSS), this paper investigates the effect of public expenditures on household investment in risky financial assets. Our findings show that a higher level of public expenditures significantly increases household investment in stocks and other risky financial assets and that the respondent's overconfidence in their financial well‐being partially mediates such an effect. We further provide evidence that the influence of public expenditures on household investment behavior in risky financial assets is robust after considering various sample heterogeneities by disaggregating public expenditures and risky financial assets into different subcategories and dividing households into different age and socioeconomic groups.

Unleashing the behavioral factors affecting the decision making of Chinese investors in stock markets.

This research paper delves into the behavioral factors that have impact on decision making of Chinese investors in stock markets. As one of the world's most dynamic and rapidly evolving financial landscapes, stock markets of China have witnessed significant growth and transformation in recent years. However, the role of behavioral biases in shaping investment decisions remains a relatively understudied aspect. Drawing upon a detailed review of studies, psychological theories, and empirical studies, this research explores various behavioral factors affecting the decision of investors at Beijing, Shanghai and Shenzhen stock markets. Through a structured questionnaire and by collecting a sample of 521 respondents, this paper investigates that herding, overconfidence, prospect, market, gamble's fallacy, and anchoring-ability bias often lead investors to deviate from rational decision-making and contribute to market inefficiencies. While herding, prospect, and heuristic affect the investment performance in stock markets of China. Moreover, the research underscores the need for investor education programs and regulatory interventions that acknowledge the presence of behavioral biases and encourage more informed decision-making. By shedding light on these dynamics, it provides valuable insights for policymakers, financial institutions, and investors seeking to navigate the intricacies of this rapidly growing financial landscape.

Analisis Arus Kas Operasi Dan Laba Terhadap Return Saham pada Perusahaan Manufaktur Cigarette

The purpose of this study is to analyze the effect of operating cash flow and profit on the investment results of cigarette manufacturing companies' shares on the Indonesia Stock Exchange 2019–2022. Secondary data were collected as part of quantitative research methodology. Cigarette manufacturing companies listed on the Indonesia Stock Exchange at the time constituted the study population. Purposive sampling is used to select research samples. The Structural Equation Model (SEM) - Partial Least Square (PLS) analysis approach was used in this study, and SmartPLS 3.0 software was used to handle the data. The findings show that operating cash flow has no noticeable impact on stock performance. This result shows that the value of stock investment returns is not significantly affected by the increase in revenue in cigarette manufacturing companies.Cash Flow

Sharia stock investment decisions: Sharia stock literacy and risk factors and their relations with behavioral bias

Research aims: This study aims to analyze the influence of Sharia stock literacy and risk factors on Sharia stock investment decisions with behavioral bias as an intervening variable.Design/Methodology/Approach: The population was investors in East Java Province who invested in Sharia stock. The sample for this research was 500 respondents. The analysis employed was the Structural Equation Model.Research findings: The impact of Sharia stock literacy on both Sharia stock literacy and investor behavioral bias was positive. Sharia stock investment decisions were adversely impacted by risk factors. Additionally, risk factors had a detrimental impact on investor behavioral bias. Behavioral bias yielded a favorable impact on the decision-making process for investing in Sharia-compliant stocks. Through behavioral bias, Sharia stock literacy positively affected Sharia stock investment decisions. Meanwhile, risk factors obtained a negative effect on Sharia stock investment decisions through behavioral bias.Theoretical contribution/Originality: This research contributes to Sharia stock investment decisions and provides empirical evidence of Sharia stock investment decisions concerning Sharia stock literacy, risk factors, and behavioral biases.Practitioner/Policy implication: This research contributes to investors' ability to determine investment decisions in Sharia stock.Research limitation/Implication: The limitation of this research is that independent variables only used two components of Sharia stock investment decision, i.e., Sharia stock literacy and risk factors. Hence, the level of influence of the independent variables on the dependent was small.

Pengaruh Sekolah Pasar Modal terhadap Pengetahuan Investasi Saham Mahasiswa Manajemen Keuangan Syariah UIN Sayyid Ali Rahmatullah Tulungagung

This study aims to see the difference before and after the implementation of the Capital Market School (SPM) on stock investment knowledge in Sharia Financial Management (MKS) study program students, Faculty of Economics and Islamic Business (FEBI) UIN Sayyid Ali Rahmatullah Tulungagung. The type of approach used in this research is a quantitative approach, while the type of research is quasi experimental (pseudo experimental research). The research design used is one group pre test-post test design, so that research data is obtained from SPM participants as respondents who are measured using a pre-test before the SPM is implemented, and a post-test after the SPM. The population used is MKS students who are SPM participants, with a total population of 129. While the sample used was 30 MKS students as SPM participants who met the criteria in sampling. The sampling technique is purposive sampling using predetermined sampling criteria. While the type of data source used is primary data, which is obtained from the pre-test and post-test of SPM participants. The variables used are SPM as the dependent variable, and stock investment knowledge as the independent variable. While the data collection technique used is the test method, all of which data is obtained from the results of measuring the investment knowledge of MKS students using measuring instruments in the form of pre-test and post-test. The results of hypothesis testing using paired sample t-test show that there is a significant difference in students' stock investment knowledge before and after the implementation of SPM.

The Influence Of Financial Socialization, Overconfidence And Mental Accounting On Investment Decisions

This study examines the effect of financial socialisation, herding, overconfidence and mental accounting on investment decisions among stock investors in Jakarta. The sample in the study is stock investors who reside in Jakarta. The purposive sampling method collected 205 respondents through Google Forms distributed online on social media. The research data were analysed with a structural equation system using SmartPLS.3.2.9 software. The results showed that financial socialisation positively and significantly influences Generation Z's investment decisions in Jakarta. Overconfidence positively and significantly influences Generation Z's investment decisions in Jakarta. Mental accounting has a positive and significant influence on the investment decisions of Generation Z in Jakarta.

Optimizing the LQ45 Stock portfolio using Piecewise Linear Function: A Case Study from an Investor's Point of View

In optimization problem solving, both linear and nonlinear approaches can be used, with nonlinear programming considering constraints or not. One effective method of nonlinear programming is the Piecewise Linear approach, which breaks down complex nonlinear functions into straight-line segments to make their solution easier. This method can be applied in the financial sphere, such as in stock investment. This study discusses the application of piecewise linear function in optimizing investment portfolios in Bank Jago Tbk. (ARTO), Barito Pacific Tbk. (BRPT), and Go To Gojek Tokopedia Tbk. (GOTO) stocks. The purpose of this study is to provide insight that Piecewise Linear can provide optimal solutions in managing investment portfolios by calculating the risks and returns of selected stocks. The results showed a risk with a level as big as 0.01, the expected profit from the investment of the three stocks in the calculation period reached Rp 1,803,109. On the other hand, for investors who are more cautious and have a Level as big as 1, the anticipated profit in the same investment is around Rp 1,275,052.

The Implementation of Roy's Safety-First Criterion in Stock Portfolio Selection

Statistical data shows that the Indonesian capital market has experienced significant growth. This growth is attributed to public awareness of the benefits of stock investments. However, with an increasing number of new investors entering the stock market, attention to investment risks deepens. Many investors prefer stocks that are easily predictable and have low risk, as higher volatility increases the level of uncertainty in obtaining returns. The relatively high risk level in investing requires investors to minimize risks, one of which is by diversifying funds into various investment assets, commonly known as optimal portfolio selection. An optimal portfolio can be formed using various methods and approaches. One method for portfolio selection is the application of the Safety First Criterion, a method dependent on downside risk, referring to risks that result in losses. This article conducts a simulation of the implementation of Roy's Safety First Criterion using stock data from the largest companies in eleven sectors over the past year. These sectors include basic materials, communication services, consumer cyclical, consumer defensive, energy, financial services, healthcare, real estate, technology, and utilities. Based on this analysis, out of the eleven stocks, six stocks meet Roy's criteria: LIN, GOOG, AMZN, BRK-B, LLY, and AAPL, with respective weights of LIN=10.84%, GOOG=12.61%, AMZN=24.67%, BRK-B=1.37%, LLY=34.17%, and AAPL=16.35%. Using Roy's Safety First Criterion for selected stocks from various sectors indicates that the resulting portfolio has a very low risk level, specifically 1%. This means that by using the portfolio obtained from the eleven stocks, investors can achieve minimal risk, making this portfolio secure for new investors.

Applying Warren Buffet’s Investment Strategy to Indonesia Stock Market

In the past five years, there has been a significant surge in local Indonesian investors, predominantly comprising millennials and Gen Z, contributing to the positive growth of the stock market. However, a concerning phenomenon known as “herding bias” has been observed, highlighting the tendency of young investors to follow prevailing trends without fully understanding the intricacies and risks associated with their investments. This paper aims to address this issue by enhancing public awareness of stocks and minimizing associated risks, focusing specifically on value investing as an effective strategy. The research utilizes a ten-year period, selecting samples from companies listed in IDX30 through Warren Buffett’s screening test. This test incorporates key factors such as Conservative Debt, Price-to-Earnings Ratio (P/E Ratio), Price-to-Book Ratio (P/BV Ratio), Debt to Equity Ratio (D/E Ratio), and Return on Equity (ROE). Following the sample selection, the paper calculates the intrinsic value of chosen stocks, determines the margin of safety, estimates expected returns, and evaluate the risk-adjusted performance. Additionally, qualitative factors like understanding the business, market conditions, and internal company factors are considered. The findings indicate that Warren Buffett’s investment strategy can be successfully applied to Indonesian stocks. Investors are advised to select stocks based on careful consideration of financial ratios, analyzing annual reports, calculating intrinsic values, determining margins of safety, and assessing expected returns alongside associated risks. This research provides valuable insights that can serve as a practical reference for stock investment decisions, particularly for stocks with high market capitalization. By promoting a comprehensive understanding of value investing, this paper aims to empower young Indonesian investors to make informed and strategic choices, thereby mitigating the impact of herding bias in the local investment landscape.

Return and Risk of Stock Investment in Finance Sector

The goal of this study is to offer investors with information to aid in deciding how to allocate their investment dollars. Investment risk results from the discrepancy between the projected return and the actual return; unfavorable risk is brought on by uncertain situations. If macroeconomic conditions are favorable, inflation is under control, exchange rates improve, and interest rates are low, investors will feel secure. Investors look for a return on their investments, either in the form of dividends or capital gains. Investors' behavior toward risk have an impact on investment decisions that are based on risk and return. The five economic circumstances studied in this study are as follows: (1) recession; (2) moderate recession; (3) normal; (4) good; and (5) excellent. The result of this study is investment at BNGA (PT CIMB NIAGA, Tbk) and BBCA (PT BANK CENTRAL ASIA, Tbk) as a high return and low risk. These stocks are recommended in any economic situation. If an investor fits the suggested risk-taker profile, they should consider investing in BNGA; otherwise, they should consider BBCA.

Legal Analysis of Online Foreign Exchange Buying and Selling and Stock Investment Using the Al-Qur'an Interpretation Method

This study aims to find out how the law of buying and selling foreign exchange online and stock investment through the Al-Qur'an detention method. The meaning of foreign exchange or trading is a type of trade or transaction that trades one country's currency against another country's currency (currency pair/pair) which involves the main money markets in the world for 24 hours on an ongoing basis. Stock Investment is the purchase and storage of capital shares in a capital market by investors, both individuals and companies in anticipation of income from dividends and capital gains determining the increased value of these shares. Lately, there have been many fraudulent investment cases under the pretext of buying and selling foreign exchange. This of course attracts the attention of the public to participate in buying and selling foreign exchange which in the end is detrimental to themselves. This study uses a field research method that examines problems or events that occur in society regarding the law of buying and selling foreign exchange or buying and selling shares. This type of research is a case study with a qualitative approach method. From this research, we can find out that if the law of buying and selling foreign exchange online and investing in shares is not in accordance with the Al-Qur'an and Sunnah, it is haram.

The prediction of Apple stock price based on linear regression model and random forest model

In the financial market, due to various factors, the stock price fluctuation is universal. Therefore, the directional prediction of stock market price based on technical analysis is very important in stock investment. This paper conducted a regression analysis and forecasted the future trends in the close price of Apple stock through recent five years between 2018 and 2023. For the purpose of this specific study, this paper did descriptive statistical analysis of the dataset, and made graphs and analyses of regression and predictions relied on the techniques of the Linear Regression Model and Random Forest Model. Based on the three indices: MSE, RMSE, and MAE, the paper compared the advantages and disadvantages of the two machine learning methods. The result of the experiments indicated that the regression generated through employment of the Linear Regression Model outperforms the result of the Random Forest Model, leading to the conclusion that Linear Regression Model is a more effective method to forecast in this dataset.

Investors' Stock Investments in the Chip Industry: Motivations, Strategies, and Impacts

This paper talks about what motivates investors to invest in chip-related stocks, and how their investment strategies and models do impact the chip market. This paper analyzes investors' stock investments in the chip industry from the perspectives of their motivations, strategies, and the subsequent impact on the market. The research identifies that investors are driven by diversification, passion, innovation support, and long-term growth, employing strategies such as in-depth research, active involvement, and early-stage investments. Their choices influence market sentiment, accelerate research and innovation, and impact M&A activities in the chip sector. This paper is significant for investors seeking insights into investors' investment motivations and strategies in the chip industry. Gives the investors a clearer view for the current Chip Technology Corporation’s stock market. And also, benefits researchers studying the dynamics of the semiconductor market and the pivotal role of investors in shaping it.

Machine Learning in Tesla’s Stock Price Prediction

With the development of new energy battery technology and people's attention to environmental issues, new energy vehicles have gradually become one of the important choices for people to travel, and stock investors have also begun to keep an eye on the field of new energy vehicles. However, since the new energy industry is an emerging industry, the current stock market analysis in this regard is not complete. Machine learning is one of the important means of stock forecasting at present. This article will use 6 machine learning models such as linear regression, polynomial regression, XGBoost, ARIMA, Prophet and LSTM to analyze and predict the stock of Tesla, a leading company in the field of new energy vehicles, so as to judge the investment prospects of new energy vehicles. The outcomes demonstrate that LSTM has the lowest error in predicting the price of Tesla’s stock.

Research on Risk Measurement in Chinese Stock Market - Based on GARCH-VaR Modeling

Chinese stock investors, whether he is an individual investor or working for a investment company, are always worried about the risk of their asset, it is difficult to measure the risk without a functional model, thus, using a model to solve it is of the pivot. The initial aim of this paper is to measure and predict the risk of Chinese stock market using GARCH-VAR model. By analyzing historical stock index return data, this paper develops a dynamic model to capture the volatility and risk correlation of the stock market. The comprehensiveness and accuracy of the results are ensured by using recent data, including stock indices that broadly cover different industries and market capitalization. The findings suggest that significant volatility and risk correlations exist in the Chinese stock market. This paper provides an effective methodology to measure and predict the level of risk in the stock market, which provides investors and risk management organizations with valuable references and decision-making bases and is important for understanding and managing the risk in the Chinese stock market, which helps stock investors to make informed optimal decisions on risk management and asset allocation.