Stock Investment Research Articles

Return on assets, return on equity, earnings per share, dividend yield, and book-to-market ratio’s effects on stock return

This research intends to investigate the ability of Return on assets (ROA), return on equity (ROE), earnings per share (EPS), dividend yield (DY), and book-to-market ratio (BMR) on stock returns. Stock investment is one strategy for investors to channel their finances while boosting wealth due to the high return on equities earned. In this study, company information is represented by financial ratios, which play a significant role in guiding investors in identifying which companies have the potential to give the highest number of returns. With 164 total observations, this research used 56 companies that were part of the LQ45 index on the Indonesian Stock Exchange (IDX) in the 2019–2022 timeframe as a sample study with the aim to examine the effects of ROA, ROE, EPS, dividend yield, and book-to-market ratio on stock return. Using STATA 14.0 software, double linear regression analysis is used in the hypothesis test. The results of this research, as proven by the regression analysis, are as follows: (1) the book-to-market ratio negatively affects stock return; and (2) ROA, ROE, EPS, and dividend yield have no bearing on stock return. This study emphasizes the value of diversifying investment strategies and avoiding a narrow range of financial ratios when choosing which stocks to buy. Investors should evaluate general business conditions and take a wider range of issues into account.

The Influence of Financial Literacy, Social Interaction, and Use of Technology on Students' Interest in Stock Investment

This research aims to analyze the influence of financial literacy, social interaction, and use of technology on students' stock investment interest. The population in this study was 35 active former members of the KSPM Mercu Buana University Class of 2022-2023. The data collection method is a survey method, with a research instrument, namely a uuestionnaire. The sampling method used is a saturated sample where all members of the population are used as samples. The data analysis method uses Structural Euuation Model-Partial Least Suuare. This research proves that the financial literacy variable has a positive and significant effect on students' interest in investing in shares, while the variables of social interaction and use of technology have no effect on students' interest in investing in shares.

Modeling of Machine Learning-Based Extreme Value Theory in Stock Investment Risk Prediction: A Systematic Literature Review.

The stock market is heavily influenced by global sentiment, which is full of uncertainty and is characterized by extreme values and linear and nonlinear variables. High-frequency data generally refer to data that are collected at a very fast rate based on days, hours, minutes, and even seconds. Stock prices fluctuate rapidly and even at extremes along with changes in the variables that affect stock fluctuations. Research on investment risk estimation in the stock market that can identify extreme values is nonlinear, reliable in multivariate cases, and uses high-frequency data that are very important. The extreme value theory (EVT) approach can detect extreme values. This method is reliable in univariate cases and very complicated in multivariate cases. The purpose of this research was to collect, characterize, and analyze the investment risk estimation literature to identify research gaps. The literature used was selected by applying the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and sourced from Sciencedirect.com and Scopus databases. A total of 1107 articles were produced from the search at the identification stage, reduced to 236 in the eligibility stage, and 90 articles in the included studies set. The bibliometric networks were visualized using the VOSviewer software, and the main keyword used as the search criteria is "VaR." The visualization showed that EVT, the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models, and historical simulation are models often used to estimate the investment risk; the application of the machine learning (ML)-based investment risk estimation model is low. There has been no research using a combination of EVT and ML to estimate the investment risk. The results showed that the hybrid model produced better Value-at-Risk (VaR) accuracy under uncertainty and nonlinear conditions. Generally, models only use daily return data as model input. Based on research gaps, a hybrid model framework for estimating risk measures is proposed using a combination of EVT and ML, using multivariable and high-frequency data to identify extreme values in the distribution of data. The goal is to produce an accurate and flexible estimated risk value against extreme changes and shocks in the stock market. Mathematics Subject Classification: 60G25; 62M20; 6245; 62P05; 91G70.

Human Resource Investment and Early-Stage Career Choice: Evaluating Work–Life Income Paths in 21st-Century Canada

Of necessity, people make many investment decisions regarding their human resource stock early in their life cycle, long before outcomes predicated upon those choices are realized. Different choices involve very different initial effort and financing outlays and issues arise as to how these alternative paths can be compared and evaluated. Here, techniques for the cardinal comparison of human resource contingent work–life-cycle income value profiles under alternative income valuation function assumptions are outlined and instruments for examining potential ambiguities in comparison developed. All are applied in an analysis of the impact of different levels of investment of human resources in 21st-century Canada. The results, with one notable exception (the choice for boys between a trade or a bachelor-level degree), indicate unambiguous life-cycle benefits to higher levels of human resource stock investment for both girls and boys. Within gender, best–worst relative magnitudes are increasing over time for both genders but more so for girls. Boys are enjoying a universal but diminishing premium over time, reflective of male–female income convergence.

Finite-time stabilization of mean-field systems with uncertain parameters, multiple disturbances and delays

The main focus of this paper is to explore the finite-time stabilization of mean-field time-varying stochastic systems that are affected by uncertain parameters, multiple disturbances, and delays. In contrast to prior studies, we present a set of sufficient conditions for achieving finite-time stability in the closed-loop model. Notably, these conditions are established based on the analysis of the state transition matrix (STM). Additionally, we address a sufficient condition based on the Lyapunov function, where the STM significantly simplifies the selection process of the Lyapunov function. Finally, we introduce a linear matrix inequality (LMI)-based approach that facilitates the computation of non-fragile controllers. The effectiveness of the developed theoretical results is verified through a stock investment model.

Love Me Do: Twitter Likes and Earnings Surprise

We introduce a new method to gauge firm-level mood using Twitter engagements on non-financial tweets. By counting likes on such tweets, we assess positive sentiment, impacting market reactions to earnings surprises. This sentiment measure doesn’t foresee earnings surprises and its market impact is short-lived, indicating it reflects mood more than informational content. However, it underscores mood’s significance in stock investment and the utility of big data for novel financial market analysis tools.

Pemetaan Portofolio Optimal dalam Manajemen Kekayaan pada Investasi Saham : Studi Bibliometrik VOSviewer dan Literature Review

This study aims to determine the mapping of research around optimal portfolios in wealth management on stock investment with a mix-method approach, namely VOSviewer bibliometric studies and literature reviews. “Data analysis techniques include: (1) mapping the number of journal publications spread around the Optimal Portfolio using Microsoft Excel and Mendeley Desktop by year of publication; (2) mapping the results of bibliometric network visualization and journal publication trends around the Optimal Portfolio using VOSviewer (Visualization of Similarities) algorithm software based on the number of clusters and their items; and (3) map research topics around the Optimal Portfolio using literature studies. The results showed that: (1) based on mapping the number of journal publications, there were 500 journal publications around the optimal portfolio; (2) based on the mapping of VOSviewer bibliometric studies The results of network visualization around the optimal portfolio are divided into 6 clusters and 163 topic items; (3) Based on the mapping of literature review studies, there are 2 topics around optimal portfolios that often appear first optimal and second stocks. The implication and contribution of this study is to map research topics around optimal portfolios in stock investments that are often or rarely researched by researchers, so that they can be a reference for researchers afterwards”.

Pengaruh Analisis Fundamental Dan Analisis Teknikal Terhadap Keputusan Pembelian Saham PT. Industri Jamu Dan Farmasi Sido Muncul Tbk (SIDO)

This study aims to analyze the influence of fundamental analysis and technical analysis on stock purchase decisions of PT Industri Jamu dan Farmasi Sido Muncul Tbk (SIDO). Fundamental analysis and technical analysis are two approaches that are often used by investors in making stock investment decisions. This study uses a quantitative method with multiple linear regression analysis techniques. Data were obtained through questionnaires distributed to 100 SIDO stock investors. The results showed that fundamental analysis and technical analysis partially have a significant effect on SIDO stock purchase decisions. Simultaneously, both types of analysis also have a significant effect. Fundamental analysis has the most dominant influence on SIDO stock purchase decisions compared to technical analysis. Investors are advised to consider both types of analysis in making stock investment decisions in order to make the right decisions.

Investor Regret and Stock Returns

We introduce a measure of regret for stock market investors and investigate its cross-sectional asset pricing implications. According to our regret-based framework, investors experience regret due to not achieving the highest possible return from a similar set of stock investments, and equity portfolios with high regret generate 6.84% more annualized alpha than portfolios with low regret. Using investor-trading activity of 78,000 households at a large U.S.-based brokerage firm, we develop an investor-based regret index and show that this household-level regret measure predicts stock returns in a similar way to our proposed regret measure. We also show that regret is not spanned by established risk or behavioral factors that have been documented to be robust predictors of equity returns. This paper was accepted by David Sraer, finance. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.03389 .

Technical Analysis of Stock Investment Decisions in Telecommunication Companies Listed on the Indonesian Stock Exchange

This research aims to examine stock investment decisions in telecommunications companies listed on the Indonesia Stock Exchange using a technical analysis approach. This research does not use hypotheses, so quantitative descriptive research is used. The purposive sampling method was used to obtain a representative sample in accordance with the sampling criteria, namely telecommunications companies listed on the Indonesia Stock Exchange. The object of the research is data in the form of graphs and trends in monthly stock price movements of three issuers in the fourth quartile of 2023 starting from October-December 2023. The research results show that the analysis of the three stocks above shows that MACD crossovers often give false signals if they are not confirmed by indicator movements momentum like RSI. In the case of TLKM and ISAT, even though the MACD has crossed over, the RSI actually moves in the opposite direction or at least does not provide a strong response, so there is potential for a reversal. Likewise with EXCL where even though a MACD crossover occurred, the RSI did not penetrate a significant level to validate the signal. Overall, MACD crossovers without the support of evidence of changes in momentum from the RSI tend to be weak and inaccurate. It takes confirmation from other indicators for a MACD crossover to truly indicate a long-term trend change instead of just a high-risk temporary move. Thus, it is important to carry out multi-factor validation so that the MACD crossover signal is stronger before being used as a reference for entry or exit positions.

Analisis Teknikal Dan Analisis Fundamental Terhadap Kelayakan Pembelian Saham PT Bank Negara Indonesiaia Tbk (BBNI)

The decision on the feasibility of purchasing a share is an indicator or criterion that is considered before finally deciding to invest or invest in the issuer. Researchers conducted technical analysis and fundamental analysis of PT Bank Negara Indonesia, Tbk. (BBNI) shares to find out whether the issuer's shares are suitable as issuers for investing or just for trading. Technical analysis and fundamental analysis are performed to see opportunity whether the shares are worthy of stock investment or not. Technical analysis is carried out using the simple moving average (SMA) and RSI methods. In addition, fundamental analysis is also carried out with several indicators such as price book value (PBV), price earning ratio (PER), debt equity ratio (DER), net probability margin (NPM), and earnings per share (EPS). In this study, the approach taken is a qualitative descriptive approach where data is presented in the form of narratives or detailed elaboration from experts. PT Bank Negara Indonesia (BBNI) shares are the oldest bank stocks that have a large market capitalization. This stock can also be said to have a relatively stable level of price fluctuation with a high level of profit and price. In terms of technical analysis and fundamental analysis, PT Bank Negara Indonesia (BBNI) shares are stocks that deserve to be an investment choice.

Stock Investors' Reaction to Layoff Announcements: A Meta-analysis

Stock Investors' Reaction to Layoff Announcements: A Meta-analysis

МІЖНАРОДНІ ФІНАНСОВІ ПОТОКИ В КРАЇНИ ЦЕНТРАЛЬНОЇ ТА СХІДНОЇ ЄВРОПИ ПІСЛЯ ГЛОБАЛЬНОЇ ФІНАНСОВОЇ КРИЗИ 2008 РОКУ: СТРУКТУРНІ ОСОБЛИВОСТІ

In our study, we will focus on determining the dynamics and structural changes in the flows of foreign capital to the countries of Central and Eastern Europe after the global financial crisis of 2008. For the analysis, we selected a group of Central and Eastern European countries that joined the European Union: Bulgaria, Romania, Poland, Hungary, the Czech Republic, Slovakia, Slovenia, Estonia, Lithuania, Latvia, as well as the post-Soviet European countries - Ukraine, Belarus, Russia and Moldova. We chose three periods for the study: the first period from the beginning of liberal reforms to the present (1991-2021); the second period from macroeconomic stabilization to the global financial crisis (1994-2008); the third period covers the post-crisis period before the start of the Russian-Ukrainian war (2009-2021). The article examines the structure of the inflow of foreign capital to the countries of Central and Eastern Europe before the global financial crisis of 2008 and in the period after it. It was determined that the share of direct and portfolio foreign investments in the structure of foreign capital increased significantly in the post-crisis period. In the post-crisis period of 2009-2021, there was a significant increase in the average value of the stock of foreign direct investment to 41.2% of GDP and a more than two-fold decrease in the volatility of FDI inflows, which amounted to 5.2, as well as a 1.5-fold increase in portfolio foreign investments and a drastic reduction in the volatility of this type of foreign capital to 2.69. As for other investments, they remained at the pre-crisis level, but volatility decreased by a quarter. An econometric study of the influence of the stock of foreign direct investment and foreign debt per worker on the level of economic well-being in the CEE countries was conducted, which proved the strengthening of the role of foreign direct investment after the global financial crisis and the lack of influence of foreign debt. In our opinion, the governments of the CEE countries have focused on the economic policy of slowing down foreign capital flows and avoiding financial risks associated with foreign debt flows. Today's geopolitical tensions, the Russian-Ukrainian war will contribute to the deepening of these processes, increasing the influence of states on limiting international financial flows.

RankFIRST: Visual Analysis for Factor Investment By Ranking Stock Timeseries.

In the era of quantitative investment, factor-based investing models are widely adopted in the construction of stock portfolios. These models explain the performance of individual stocks by a set of financial factors, e.g., market beta and company size. In industry, open investment platforms allow the online building of factor-based models, yet set a high bar on the engineering expertise of end-users. State-of-the-art visualization systems integrate the whole factor investing pipeline, but do not directly address domain users' core requests on ranking factors and stocks for portfolio construction. The current model lacks explainability, which downgrades its credibility with stock investors. To fill the gap in modeling, ranking, and visualizing stock time series for factor investment, we designed and implemented a visual analytics system, namely RankFIRST. The system offers built-in support for an established factor collection and a cross-sectional regression model viable for human interpretation. A hierarchical slope graph design is introduced according to the desired characteristics of good factors for stock investment. A novel firework chart is also invented extending the well-known candlestick chart for stock time series. We evaluated the system on the full-scale Chinese stock market data in the recent 30 years. Case studies and controlled user evaluation demonstrate the superiority of our system on factor investing, in comparison to both passive investing on stock indices and existing stock market visual analytics tools.

Stock Price Prediction Using Deep-Learning Models: CNN, RNN, and LSTM

With the rapid development of the economy, stock markets or equity markets have an important role nowadays. More and more people participate in stock investment, the rise or the fall in prices is vital and closely related to investors’ earnings. The basic way uses linear or non-linear algorithms, but the stock market has many factors, so it is highly non-linear prediction, so it is helpless to use one simple model, so this paper proposes to figure out a good deep-learning model to capture and analyze the data of six companies from Yahoo Finance by comparing the fitness of three famous neural network: CNN, RNN, and LSTM. The Sliding-Window model was applied to make future predictions in time series. The results of the models were calculated by using MSE, MAE, and MAPE.

Gender Perspectives on ESG Stocks: Awareness and Engagement in Sustainable Investment Analysis

ESG (Environmental, Social, and Governance) criteria are increasingly significant in evaluating a company's performance and impact. Investors and stakeholders consider these factors when making investment decisions, and gender influences preferences in ESG stocks. This study assesses public awareness and understanding of ESG stocks in sustainable investments, with a focus on gender differences among 380 investors from Kolhapur City, selected using purposive sampling to ensure diversity in age, education, occupation, and socio-economic status. Data analysis through SPSS software and Chi-square tests revealed several insights. Male investors were more actively engaged in stock investments than female investors. Male investors demonstrated higher awareness and consciousness of ESG aspects before investing compared to female investors. Environmental and social dimensions were given more importance than governance when selecting stocks based on ESG criteria. Investors were particularly aware of environmental issues such as a company's carbon footprint, energy efficiency, waste management, and adherence to environmental regulations. Social aspects like labor practices, diversity and inclusion, human rights, and community engagement were also prioritized. However, the governance dimension, which includes understanding of a company's leadership, executive compensation, shareholder rights, and corporate governance practices, was less understood and considered by investors. This is crucial for both genders to make informed investment decisions that align with sustainability goals. As ESG considerations become integral to investment strategies, understanding how different genders perceive and engage with ESG stocks can provide valuable insights for effective sustainability communication and overcoming barriers to adoption.

Analisis Capital Asset Pricing Model (CAPM): Dasar Pengambilan Keputusan Investasi Saham pada Perusahaan Sektor Perbankan

Investing is one way to increase income. However, the reality is that not all investors can generate additional income and not all investors can manage their investments optimally. This problem arises because investors make several mistakes when investing. The purpose of this study is to classifiy between efficient stocks and inefficient stocks using the CAPM method, so that it can help investors in considering the right stock investment. The data collection techniques used are documentation and literature study. The data analysis technique used is descriptive quantitative. The results of this study indicate that PT. Allo Bank Indonesia Tbk (BBHI) shares have the highest average individual rate of return (stock return) of 0.2523 or 25.23%. PT. Allo Bank Indonesia Tbk (BBHI) has the highest beta index of 6.6166 and is an aggressive stock because beta is more than one (?>1). PT. Allo Bank Indonesia Tbk (BBHI) has the highest expected return of 0.0824 or 8.24%. The conclusion of this study states that there are 18 efficient stock issuers, namely stocks that have individual stock returns higher than the expected rate of return [Ri>E(Ri)] and 16 inefficient stocks, namely stocks that have individual returns lower than the expected rate of return [Ri<E(Ri)]

The impact of environmental, social, and governance information on individual stock investment decisions

The global business landscape has seen a growing necessity for companies to implement and disclose environmental, social, and governance (ESG) information (AlHares et al., 2023). Driven by the expectations of investors and society, companies find themselves obligated to publish ESG reports. Therefore, this study focuses on exploring the impact of ESG information on the investment decisions made by individual investors in Vietnamese stock markets. By employing the theory of planned behavior (TPB) and conducting a comprehensive survey, coupled with logistic regression analysis on a sample of 232 individual investors, our research uncovers a significant influence of ESG information on the stock decision-making process of these investors. Notably, our findings reveal that investors place greater emphasis on governance (G) information compared to social (S) and environmental (E) information when making investment decisions. This trend aligns with the conclusions drawn by Sultana et al. (2018) and Mehwish et al. (2022) but diverges from the findings of Rounok et al. (2023). These findings are poised to catalyze the disclosure of ESG reports among listed companies. They also impel policymakers to craft and implement policies actively promoting ESG reporting. Such initiatives will likely foster increased interest and bolster investments in companies adhering to ESG criteria, particularly among individual investors in emerging stock markets.

Assessment of Efficiency of Investment in Companies Belonging to the Rare Earth Metals Sector

Purpose – This paper aimed at assessing the efficiency of investment in companies belonging to the rare earth elements sector and examining the stability of the results. Research method – The following performance measures were used in the study: modified Sharpe and Omega, Sortino, Calmar, Sterling and Burke ratios. The investigation is based on daily quotations of selected companies whose business activities were related to extraction, processing and recycling of rare earth metals in the period: from July 2018 to June 2023 and MVIS® Global Rare Earth/Strategic Metals Index representing the global market. Results – The analysis for the entire period revealed a worse performance of investments in rare earth stocks than investment in risk-free assets. Only AREC outperformed other securities offering the best results for 3 of 6 ratios. To examine the stability of the results, the total investigation period was divided into 5 subperiods and all performance ratios were determined for each of them. A strong variation of results did not allow to recognise stable patterns. When the results for the entire investigation period were used as a benchmark, only MVREMX offered stable and attractive results of modified Sharpe ratio outperforming the five-year value in 4 out of 5 subperiods. Originality / value / implications / recommendations – This study provides a new insight into the rare earths sector regarding its growing international importance and the efficiency of investments into listed rare earth firms. The examination uses two-dimensional measures offering the advantage of simultaneously combining return and risk into a single performance number. The findings imply the necessity of improving the stock price performance to attract investors’ interest.

The Relationship Between Electronic Word-of-Mouth Information, Information Adoption, and Investment Decisions of Vietnamese Stock Investors

The Relationship Between Electronic Word-of-Mouth Information, Information Adoption, and Investment Decisions of Vietnamese Stock Investors