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Commonly used research models analysing technological adoption, such as the Technology Adoption Model, Theory of Planned Behaviour, and Unified Theory of Acceptance and Use of Technology, mostly emphasise technology-related variables. In the context of mobile stock investment application adoption, this study extends the existing technological adoption models by adding digital financial service-related variables. The purpose of this study is to investigate the main determinants of mobile stock investment application adoption in emerging countries, specifically in Indonesia. The study deployed a quantitative type of research with an online survey questionnaire by recruiting 256 respondents of stock investors who have used mobile applications for a minimum of one year. Data was analysed using partial least squares structural equation modelling (PLS-SEM) with advanced analysis tests. The results confirm the significant influence of performance expectancy, finfluencers, perceived financial risks, perceived financial benefits, perceived technology security, financial literacy, and e-reputation on adoption behaviour. The results also find a significant influence of adoption behaviour on the intention to recommend. Meanwhile, effort expectancy and facilitating conditions were insignificant toward adoption behaviour. These findings signify that the comprehensive research model could contribute to enriching studies on adoption of the mobile technology by extending TPB and UTAUT with specific variables related to stock investment and its impact on the intention to recommend the applications. Finally, the implications of the proposed new model for future research and FinTech practice are discussed.

Commonly used research models analysing technological adoption, such as the Technology Adoption Model, Theory of Planned Behaviour, and Unified Theory of Acceptance and Use of Technology, mostly emphasise technology-related variables. In the context of mobile stock investment application adoption, this study extends the existing technological adoption models by adding digital financial service-related variables. The purpose of this study is to investigate the main determinants of mobile stock investment application adoption in emerging countries, specifically in Indonesia. The study deployed a quantitative type of research with an online survey questionnaire by recruiting 256 respondents of stock investors who have used mobile applications for a minimum of one year. Data was analysed using partial least squares structural equation modelling (PLS-SEM) with advanced analysis tests. The results confirm the significant influence of performance expectancy, finfluencers, perceived financial risks, perceived financial benefits, perceived technology security, financial literacy, and e-reputation on adoption behaviour. The results also find a significant influence of adoption behaviour on the intention to recommend. Meanwhile, effort expectancy and facilitating conditions were insignificant toward adoption behaviour. These findings signify that the comprehensive research model could contribute to enriching studies on adoption of the mobile technology by extending TPB and UTAUT with specific variables related to stock investment and its impact on the intention to recommend the applications. Finally, the implications of the proposed new model for future research and FinTech practice are discussed. [ABSTRACT FROM AUTHOR]

To study the factors affecting the stock investment intention of Vietnamese youth, the research team used quantitative research methods based on sample data collected from a survey of 482 young people, of which 262 were young people who have made stock investments and intend to invest in stocks. The research team used SMARTPLS software to process collected survey data. Research results show that, in 6 factors with 95% confidence, 4 factors have an impact on the stock investment decisions of young people living in Vietnam. Among them, "Subjective Norms" (CCQ) has the strongest influence on stock investment intention with an influence of 0.349; Next is the factor "Perceived behavioral control" (NTKS) with an influence level of 0.181; The factor "Attitude towards money" (TDTB) has an influence level of 0.175; The factor "Attitude towards stock investment" (TDCK) has an influence level of 0.166. Two factors "Risk Perception" and "Profitability and stability" are not statistically significant enough to show a relationship with the stock investment intentions of young people living in Vietnam. Based on the analysis results, the research team proposed several discussions to promote young people's readiness and improve awareness and ability to carry out investment activities and stock investments. [ABSTRACT FROM AUTHOR]

The one-stop platform of stock investment has a positive effect on technological developments in the world of stock investment. That triggers changes in investor behavior in buying stock. This research investigates the influence of the "stream" feature as User Generated Content (UGC) media as well as the relationship between the Fear of Missing Out (FoMO) phenomenon and investor's financial literacy in buying stocks. This research implements partial least squares-structural equation modeling (PLS-SEM) to conduct quantitative research. Sample data collection was collected using non-probability sampling. This research is limited to Indonesian stock investors, using the Stockbit platform for stock investment, and the research was conducted cross-sectionally. This research found that FoMO effects that investors felt can significantly influence purchasing attitudes, subjective norms, and perceived behavioral control. Meanwhile, the quality of information contained in UGC has a significant positive effect on purchase attitudes and financial literacy can reduce the influence of investor FoMO on purchasing intentions. This research contributes to the extended theory of planned behavior in explaining stock investment behavior and enriches understanding of the influence of UGC, FoMO, and financial literacy on investment decisions. This research also contributes to Stockbit management, psychology practitioners, content creators, and financial consultants in the realm of stocks.

Investing in stock market is considered a high-risk monetary motion where investor may not take into version the factor of stock charge fluctuations or destroy their profits without gaining professional knowledge and investment experience. In addition, when working with stock information, people increase the importance of available and self-correcting information, a habit that runs counter to objective and reasonable investment decisions. In recent years, various methods of stock market forecasting have been proposed to enhance the quality and profitability of investor decision making. Recent machine learning models have been able to reduce the risk of stock market forecasting. However, diversity remains a major challenge in developing better learning models and in identifying intellectually valuable traits to further improve diagnosis. In this paper, we propose an optimal characteristic selection with hybrid machine learning classifier for stock market price forecasting (OFML-SMF) using social media and secondary data sources. First, we introduce a multi-objective earthworm optimization (MOEO) algorithm for optimal feature selection among multiple features i.e. called feature optimization which reduces the data dimensionality problem. Second, we develop a hybrid Quantile regression learning based deep belief neural network (HQR-DBNN) to classify the stock market price movement prediction which enhances the statistical metrics. Finally, to appraise the presentation of planned OFML-SMF model through the influential international stock market indices and the performance can be compare with the existing state-of-art models in conditions of accuracy, precision, recall and F-measure. [ABSTRACT FROM AUTHOR]

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The development of information technology has had a significant impact on the world of investment, with the emergence of online-based stock investment applications. Along with its popularity, legal protection of investors has become very important. This study aims to analyze and evaluate the legal protection mechanism provided to investors on online-based stock investment applications. The method applied in this legal research is the study of normative juridical research methods, which refers to research on substance analysis of laws and regulations, books, journals and papers as well as other jurisprudence. Normative research because research specifications are more made on secondary instructions in the library. The results showed that legal protection for investors in online stock investment applications involves various aspects, ranging from laws and regulations to internal policies of application organizers. Existing regulations, both national and international, provide a legal basis that protects the rights of investors, but there are still some weaknesses in their implementation. Legal uncertainty, information transparency, and the responsibility of application operators are crucial aspects that need to be improved to improve investor protection. Regulatory alignment, the active role of supervisory authorities, and education to investors are also key steps in improving legal protection for investors on online-based stock investment applications. [ABSTRACT FROM AUTHOR]

This study introduces the novel concept of a stock investment strategy tailored to crises. It adopts a quantitative approach that tests various factors influencing stock price dynamics. In the first stage of the study, a multiple regression analysis is conducted, encompassing macroeconomic indicators such as Southeast Asian, Chinese, and American stock indexes, gold prices, and the impact of COVID-19 on stock prices. Subsequently, an additional examination assesses the influence of LQ-45 company performance on stock price formulation. Finally, a qualitative analysis is employed to scrutinize government policies implemented during the pandemic and their impact on Jakarta Composite Index (JCI) movements. As a result, it is found that all macroeconomic factors exert a significant negative influence on stock prices. Additionally, as COVID-19 cases surge, stock indexes in Southeast Asia, China, and America exhibit a substantial positive effect on stock prices. In contrast, firm performance and gold prices do not significantly affect stock price movements. Moreover, the market also reveals a more favorable response to government initiatives aimed at relaxing activity restrictions and positive developments in vaccination efforts. Lastly, based on the extensive analyses conducted in this study, we have identified four distinct investment strategies tailored explicitly for effectively navigating crises. These strategies encompass diversification, a prudent wait-and-see approach, the Richman party, and the Guerrilla strategy.

We employ a Boxplot method for detecting and analyzing outlying daily returns of 14 international stock market indices sampled from around the world. The main objective of the paper is to provide an extensive analysis of the main characteristics, features and effects of the detected outlier returns. The results show that from about 4–10% of observations constitute outlying returns with an average of 6%. Conservatively, about 1.4% of return series are extreme outliers. Negative outliers are found more frequent, influential, severe and transmissible. The bulk of detected outliers are found to be in the magnitude of three standard deviations. Also, outliers tend to cluster together, both within individual return series over time and across stock markets. We find a sequential pattern in outlier occurrence within individual return series, and a concurrent pattern across stock markets. Moreover, adjusting for outlying returns leads to a decrease in standard deviation, negative skewness and kurtosis by about 18%, 74% and 69% on average, respectively. We do not find consistent evidence that advanced and well-developed stock markets have less frequent and/or sever outliers. Overall, the results and analysis of the paper provide important considerations about international stock market returns which are relevant to stock investment, portfolio and risk management. The results show that the best (worst) outlying returns which represent about only 1% of the return observations have an enormous effect on the stock return performance and realization.

While informal debt is often used as a funding source for retail investors, very little is known about the characteristics of its sources and use. This is particularly true in emerging markets where the use of informal debt is widespread. We examine the determinants of the use of informal debt of individual investors in the Vietnam stock market and find that perceived risk has a positive impact on informal debt decisions, that borrowing sources are primarily from parents and friends and that experience, wealth and borrowing sources have a positive impact. We also find that women perceive higher risks in stock investments than men do.The policy implication is that informal debt sources play a significant part in stock market development, and therefore, a greater level of attention needs to be paid to them. Policies need to be developed that increase and manage informal sources of investment finance.

Copyright of Modern Economic Science is the property of Modern Economic Science Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study investigated whether overconfidence with respect to one's financial literacy affects stock market participation and retirement preparation and if so, how. Using an effective sample of 12,653 Japanese individuals, the empirical results confirm that financial literacy plays a positive role, while confidence in financial literacy also matters. For people with relatively low financial literacy, overconfidence can encourage taking financial action, while for people with high financial literacy, underconfidence can deter action. Confidence could have an effect equal to or greater than financial literacy. Moreover, it was also found that the positive effect of overconfidence is weaker for women than for men. [ABSTRACT FROM AUTHOR]

Abstract With the maturity of neural network theory, it provides new ideas and methods for the prediction and analysis of stock market investment. The purpose of this paper is to improve the accuracy of stock market investment prediction, we build neural network model and genetic algorithm model, study the law of stock market operation, and improve the effectiveness of neural network and genetic algorithm. Through the empirical research, it is found that the neural network model can make up for the shortcomings of the traditional algorithm through the optimization of genetic algorithm.

Research aims: This study aims to examine factors that influence stock investment intention among students. Design/Methodology/Approach: The population in this study are all individual student investors registered at the Indonesia Stock Exchange Investment Gallery in the North Sulawesi and Gorontalo Regions. Sample selection is based on the purposive sampling method. Data analysis was performed with SmartPLS 3.0 M3. Research findings: The results found that student attitudes are determined by employment opportunities in the capital market. In addition, attitudes and behavioral control also have significant effect on student intention. This is different with subjective norms which does not affect student investment intention. Theoretical contribution/ Originality: This research confirm that job opportunity influences students attitude in stock investment. The attitude and perceived behavioral control support students intention to invest stock in capital market. Subjective norms does not effect to students intention, in the context of students in the North Sulawesi and Gorontalo Regions. Practitioner/Policy implication: The implication is the universities need to make policies which is friendly with stock investment, such us Seminars, Workshops, Capital Market Schools, and Securities Traders Representative Courses (WPPE). The Indonesian Stock Exchange (Representative Office) and Exchange Members also need to increase an internship quota in order to support student investment intentions. Research limitation/Implication: This study only examines the stage of student intentions because the sample is student whose main activity is studying and the additional activity is investing.

While informal debt is often used as a funding source for retail investors, very little is known about the characteristics of its sources and use. This is particularly true in emerging markets where the use of informal debt is widespread. We examine the determinants of the use of informal debt of individual investors in the Vietnam stock market and find that perceived risk has a positive impact on informal debt decisions, that borrowing sources are primarily from parents and friends and that experience, wealth and borrowing sources have a positive impact. We also find that women perceive higher risks in stock investments than men do.The policy implication is that informal debt sources play a significant part in stock market development, and therefore, a greater level of attention needs to be paid to them. Policies need to be developed that increase and manage informal sources of investment finance. [ABSTRACT FROM AUTHOR]

We employ a Boxplot method for detecting and analyzing outlying daily returns of 14 international stock market indices sampled from around the world. The main objective of the paper is to provide an extensive analysis of the main characteristics, features and effects of the detected outlier returns. The results show that from about 4–10% of observations constitute outlying returns with an average of 6%. Conservatively, about 1.4% of return series are extreme outliers. Negative outliers are found more frequent, influential, severe and transmissible. The bulk of detected outliers are found to be in the magnitude of three standard deviations. Also, outliers tend to cluster together, both within individual return series over time and across stock markets. We find a sequential pattern in outlier occurrence within individual return series, and a concurrent pattern across stock markets. Moreover, adjusting for outlying returns leads to a decrease in standard deviation, negative skewness and kurtosis by about 18%, 74% and 69% on average, respectively. We do not find consistent evidence that advanced and well-developed stock markets have less frequent and/or sever outliers. Overall, the results and analysis of the paper provide important considerations about international stock market returns which are relevant to stock investment, portfolio and risk management. The results show that the best (worst) outlying returns which represent about only 1% of the return observations have an enormous effect on the stock return performance and realization. [ABSTRACT FROM AUTHOR]

Investment is a sacrifice made by investor in the present days to obtain good return in the future after taking into account the risk that they possibly confront with. Return and Risk have unidirectional relationship. For example, high return is only achievable with high risk. Low return comes with low risk. In such condition, investors must choose the best investment among many options available to them, such as buying, selling or keeping stocks. Any investment can deliver the expected return, but the return in the form of capital gain or dividend yield is only achieved through stock investment. Based on the opinion given, return on investment is an indicator used by investors to increase their welfare. Investors expect that they would get capital gain and dividend yield as high as possible at certain risk rate. This expectation motivates investors to take into consideration any information and also psychological factor in order to produce optimum investment decision. [ABSTRACT FROM AUTHOR]

This paper documents a computational form of the Intelligent Portfolio Theory for investing and trading in stock markets with two multi-factor models and two trend following trading strategies. The Intelligent Portfolio Theory for stock investment goes beyond the classical portfolio theory by using multi-factor models for stock selection and quantitative trading strategies instead of buy-and-hold. In China A-share market, a special multi-factor Model 1 is developed targeting at the food and beverage sector, which is made up of 7 effective and non-redundant factors selected from 20 candidate factors representing 6 categories: valuation, technology, size, profitability, growth ability, and solvency. A more general multi-factor Model 2 targeting at all the stocks in the whole stock market is also developed, which is constructed as a rule-based system integrating fundamental and technical analysis inspired by the empirical approach of CANSLIM. The multi-factor models are used to forecast or rate the future return of each stock in the sector, and then a small number of stocks are selected to form a portfolio. Each selected stock in the portfolio is then traded using a trend following trading strategy. Two strategies are developed, Strategy 1 with the high-low price channel breakout, and Strategy 2 with the parabolic stop and reverse indicator. The first intelligent portfolio trading system integrates Model 1 with Strategy 1, and is tested on an in-sample data of 7 years and also on an out-of-sample data of 2 years. The second system couples Model 2 with Strategy 2 and is tested on a data of 2 years. Both intelligent portfolio trading systems generated significantly useful performance in terms of annual returns and maximum drawdown. The test results confirmed the effectiveness of the Intelligent Portfolio Theory with proposed multi-factor models and trading strategies. [ABSTRACT FROM AUTHOR]

This study contributes to the literature on the stock-holding puzzle by examining the effects of student debt on the decision of U.S. households to own stocks in non-retirement accounts. The study uses longitudinal data from the 2011 to 2017 U.S. Panel Study of Income Dynamics for the analyses. The results show that households with student debt have a lower probability of owning stocks in a non-retirement account compared to households without student debt. The results also show that the amount of student debt is associated negatively to the decision to own stocks in a non-retirement account. The findings suggest that the financial constraints associated with student debt may influence stock ownership in a non-retirement account. [ABSTRACT FROM AUTHOR]

Since the launch of the InvestSmart™ initiative in 2014, the government agencies in Malaysia have been actively engaging community and university students via their outreach programs to promote investment literacy. Given this background, the state of the investment literacy of Malaysian undergraduates and their readiness to invest is intriguing. Therefore, this article offers a dataset of Malaysian undergraduates’ readiness to invest and the role that investment literacy and social influence play in their readiness to invest. Using a non-probability sampling technique, 500 undergraduate students in Malaysia were engaged to participate voluntarily in this survey. Descriptive statistics are presented in this paper. The dataset provides insights into the current state of investment literacy among Malaysian undergraduates, the sources of information on stock investment, and the readiness of these undergraduates to participate in the stock market.

Tri dharma higher education requires lecturers to carry out, research, warming and devotion to society. Therefore as a form of moral responsibility to the community to improve knowledge through formal education or non-formal. The purpose of this coaching is to introduce capital market products and how knowledge and costs for investments and costs. So far, people are still patterned with a project with a high cost and difficult for those who are afraid to invest, even if there is an investment community with a road to find a safe at home and maybe even raising. Investing in shares is something that is very important that the internet. These targets are students and teachers with the hope that these students will transmit their knowledge to the community. Existing benefits by using existing resources for other things offered for sale in terms of investment.Tri dharma higher education requires lecturers to carry out, research, warming and devotion to society. Therefore as a form of moral responsibility to the community to improve knowledge through formal education or non-formal. The purpose of this coaching is to introduce capital market products and how knowledge and costs for investments and costs. So far, people are still patterned with a project with a high cost and difficult for those who are afraid to invest, even if there is an investment community with a road to find a safe at home and maybe even raising. Investing in shares is something that is very important that the internet. These targets are students and teachers with the hope that these students will transmit their knowledge to the community. Existing benefits by using existing resources for other things offered for sale in terms of investment.

This study (a) investigates dispositional attributes regarding the risk-related personality, attitude, and behavior of college students majoring in financial engineering (FE-major group) and business (business-major group); and (b) examines whether risky behavior is differentially explained by explicit versus implicit attitude toward stock investment. The FE-major group scored consistently higher than the business-major group on measures of sensation-seeking, financial risk-taking, and computerized risk-taking behavior. This pattern was also observed in the two explicit attitudinal measures of risk, whereas no group differences were noted on the two corresponding implicit measures of risk. A newly developed implicit measure of stock investment showed incremental validity in predicting risky behavior beyond the corresponding explicit measure. [ABSTRACT FROM AUTHOR]

With the maturity of neural network theory, it provides new ideas and methods for the prediction and analysis of stock market investment. The purpose of this paper is to improve the accuracy of stock market investment prediction, we build neural network model and genetic algorithm model, study the law of stock market operation, and improve the effectiveness of neural network and genetic algorithm. Through the empirical research, it is found that the neural network model can make up for the shortcomings of the traditional algorithm through the optimization of genetic algorithm. [ABSTRACT FROM AUTHOR]

This paper evaluates an editorial and seven invaluable and interesting review papers for the Journal of Risk and Financial Management (JRFM). The topics covered include the rising complexity of bank regulatory capital requirements from global guidelines to their United States (US) implementation, connections among big data, computational science, economics, finance, marketing, management and psychology, factors, outcome, and the solutions of supply chain finance, with a review and future directions, time-varying price-volume relationship, adaptive market efficiency, and a survey of the empirical literature, improved covariance matrix estimation for portfolio risk measurement, stock investment and excess returns, with a critical review in the light of the efficient market hypothesis, and a cross section analysis of country equity returns, and a review of the empirical literature. [ABSTRACT FROM AUTHOR]

This study uses data from the 2013 Survey of Consumer Finances to investigate factors related to stock investment in individual retirement accounts and focuses on the role of gender and marital status in particular. This study finds that single women are less likely to own stocks and invest in fewer stocks in their IRAs. Personal characteristics, such as stock ownership in other financial assets, education level, and risk tolerance may play a key role in shaping individuals' decisions regarding stock investment in IRAs. However, these determinants are different for single women than for other demographic groups. [ABSTRACT FROM AUTHOR]

Copyright of Share: Journal of Islamic Economics & Finance / Jurnal Ekonomi dan Keuangan Islam is the property of Share Jurnal Ekonomi dan Keuangan Islam and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the field of financial investment, investing in stocks is relatively easy compared to other investment commodities, since making a profit through buying a stock at a low price and selling it at a higher price is intuitive. However, it is really challenging work for an investor to choose stocks which might be profitable, to determine the capital allocations for these selected stocks or even to time the transactions for stocks. In this study, the analytic hierarchy process (AHP), support vector regression (SVR), and genetic algorithm (GA) are employed to design a three-stage portfolio optimization approach for sequentially solving the portfolio selection, portfolio optimization, and transaction timing. Stocks in the semiconductor and iron and steel subsectors in Taiwan are used to illustrate the procedures for applying the present approach. Based on the investment results from 26 May 2017 to 25 Aug. 2017, the annualized returns on investment are 15.36% and 6.15% for the stock markets of the semiconductor and iron and steel sub-sections, respectively. Both returns are superior to the one-year certificate of deposit of about 1% in Taiwan. Hence, we are confident that the proposed approach can fit the real-world stock market, and thus serve as a valuable, functional tool for an investor.