Stock Investment Research Articles

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

Choosing a securities brokerage on the stock market: the risk governance perspective

Introduction: The role of a securities company is demonstrated through operations such as brokerage, investment consulting and portfolio management for investors. Therefore, investors' decisions in choosing a securities company affect the profitability and risks of their investment activities. Aim: The research objective is to clarify the factors that determine investors' choice of stock brokers as securities companies in Vietnam's stock market.Methods: The data sample was collected by the author in an online survey from 250 individual and institutional stock investors from January 2023 to December 2023. Conducted through multivariate quantitative regression research method on SPSS 20 software.Results: The article has identified 6 factors that influence the decision to choose a stock broker as a securities company, including: (1) Modern technical facilities, modern core software ( VCCKT); (2) Company size (QMCT); (3) Quality of consulting staff (NVTV); (4) Type of specialized/multi-function securities company (CDDN); (5) Relationship (MQH); (6) Brand marketing (MTMK). Conclusions: Based on the research results, the authors have recommended solutions for securities companies in expanding market share of securities investors such

Quantitative Stock Selection Strategy Analysis Based on Multi-factor Model Under the Epidemic Situation

Contemporarily, COVID-19 undoubtedly had a profound impact on the current Chinese economy, as well as presented various challenges and opportunities for different industries in China. As a matter of fact, these changes may profoundly affect the future development trends and competitive landscape of industries. In recent years, the number of stock investors had continued to increase, surpassing 200 million in 2022. In a highly competitive market, the ability to select high-quality stocks often determines the final returns. This study selected the constituent stocks of the “CSI 500” as the “stock pool” for stock selection between 2020 and 2023. By analysing the degree of factor exposure, the correlation between factors, and IC values of factors, suitable and effective factor combinations were selected, and an evaluation model was established using multiple regression analysis to obtain a trading strategy. To ensure its feasibility and rationality, the strategy was simulated using backtesting before actual trading, ultimately aiming to achieve excess alpha returns.

AI-Enhanced Fuzzy Precision in Stock Investment Decisions with Integrated Weighted Aggregation and Multivariate

AI-Enhanced Fuzzy Precision in Stock Investment Decisions with Integrated Weighted Aggregation and Multivariate

Development of Financial Literacy Through a Self-advising Stock Investment Model: an Integration of Machine Learning and Business Intelligence Tools to Guide Novice Investors

Development of Financial Literacy Through a Self-advising Stock Investment Model: an Integration of Machine Learning and Business Intelligence Tools to Guide Novice Investors

CB-SEM vs PLS-SEM comparison in estimating the predictors of investment intention

This paper compares different structural equation modeling approaches in estimating the predictors of investment intention. Covariance-based structural equation modeling (CB-SEM) and partial least squares structural equation modeling (PLS-SEM) techniques were compared in the estimation of the model according to the theory of planned behavior (TPB). Additionally, the consistent PLS algorithm (PLSc) was taken into consideration in the methods comparison. To determine which factors affect stock investment intention, a TPB model with attitude towards behavior, perceived behavioral control, and subjective norm as independent variables was estimated using three different approaches. The factors in the model were measured using survey indicators and the final sample included 200 Croatian residents. The results mostly show matching conclusions about the investment intention predictors, with a small difference observed in the PLS-SEM method. It can also be concluded that the factor loadings are higher according to PLS-SEM, as well as the indicators of convergent validity and reliability. On the other hand, CB-SEM shows stronger structural paths than PLS-SEM, and PLSc results are closer to those of CB-SEM. While CB-SEM shows better model fit, PLS-SEM shows high predictive power. This research further provides explanations of the differences and guidelines on when to use which approach.

Research on Investment Value of Bank Stocks Based on Factor Analysis Model

Banks are directly affected by macroeconomic factors in China, with changes in these factors significantly impacting bank stock prices and the banks' operations and management. Due to differences in capital attributes, state-owned banks and non-stateowned banks exhibit various micro-level differences, leading to different reactions in their stock prices to macroeconomic changes. Consequently, the investment value analysis for banks with different attributes also differs. This paper conducts an empirical analysis of the investment value of bank stocks, primarily following these steps: first, conducting factor analysis on cross-sectional data to calculate the total variance explained by the factor analysis and the factor scores; second, calculating the common factors and composite scores for each quarter; and finally, using panel data and the improved TOPSIS-based factor analysis model to evaluate the stock investment value of 16 banks for the first, second, and third quarters of 2022. The results indicate a disparity in investment value between state-owned and non-state-owned banks, with an overall imbalance in investment value among these banks.

Privacy Policy Matters: An Empirical Investigation on the Users’ Willingness to Disclose Personal Information and Trust in a Stock Investment Mobile Application

Stock investment mobile application often requires significant personal information disclosure. However, users might be reluctant to provide such information due to privacy. In this study, we conducted a 2 × 2 full factorial experimental design involving 185 participants to investigate this issue. Our results yield interesting findings. Firstly, the presence of a privacy policy positively impacts users' willingness to disclose. Secondly, an easily understandable privacy policy impacts users' willingness to disclose, especially in low privacy policy conditions. Thirdly, the effect of readability on users' willingness to disclose is more pronounced among women than men. Fourthly, trust influences users' willingness to disclose.

Fama’s model of efficient market: Analysis of the performance of insurance companies and the insurance stock price movement in Nigeria

The study analyzed the performance of insurance companies and the insurance stock price movement in Nigeria using Fama’s model of efficient market approach. Lack of information about insurance stock prices movement can influence investor’s decision making on insurance stock investments. An ex post facto research design was employed in the study. The research covers the activities of 19 insurance companies that are listed on the Nigerian Stock Exchange as at December 31, 2022. The data sample of the study comprises of daily stock prices data of 19 listed insurance companies for the period January 4, 2022 December 30, 2022. Fama-French three factor coefficient estimates obtained from quantile regression was used to test the hypothesis. The results revealed that there is a significant relationship between the insurance stock price movement and the performance of insurance companies in Nigeria, and that such relationship is negative. Recommendations were that there should be perfect information about stock market forces of demand and supply because if there is information asymmetry through which borrowers (securities issuers) know more about the risks than the lenders to (securities purchasers), the market participants may be reluctant to trade with insurance stocks, whose characteristics and behaviour under varying economic conditions are not well known. Also, it is important for the regulator in formulating policies that encourage diversification of investments among others.

Determinants influencing investment decisions of individual investors: The case of the developing economy

In recent years, the Vietnam stock market has recorded a large number of new investors, of which individual investors account for the majority. Although it has increased both in the number of listed shares and in trading value, price fluctuations are very unpredictable over different periods, and awareness of factors influencing investment decisions is still limited, leading to a high risk of loss in investment activities (Mayfield et al., 2008). The research was carried out in order to point out the factors influencing investment decision-making among potential individual investors, thereby proposing solutions to improve investment efficiency. The study used data from 261 questionnaires with four hypotheses, using qualitative and quantitative research methods, Cronbach’s alpha, exploratory factor analysis (EFA), and regression analysis by SPSS software. As a result, four elements influencing: 1) personality traits, 2) behavioral factors, 3) company-related factors, and 4) exogenous factors have a positive impact on the stock investment decisions of individual investors. Thereby the article shows solutions from the government, the stock market, businesses, and individuals to improve investment efficiency.

Impact of Public Health Events on Aviation Stock Returns and Volatility: Evidence from COVID-19

The aviation industry was greatly impacted during COVID-19 since 2020. At the end of 2022, the epidemic was basically under control. In the post-epidemic era, the prevention and control policies were relaxed. The aviation industry gradually recovered. These events led to great influence to aviation stocks. To examine the influence of the pandemic on aviation stocks, the event study method and the GARCH model are adopted analysing the return and its volatility. The result indicates that the outbreak of the coronavirus brought about a detrimental impact on aviation stocks. During the epidemic, negative news had a greater impact than positive news, while in the period before the COVID-19 positive news exerted greater impact. Moreover, both persistence and long-term memory of the fluctuation decreased during the pandemic. The come of the post-epidemic era had a favourable influence on aviation stocks. Nevertheless, the effects of both events were relatively transient. These results help to guide aviation stock investment during public health events.

Stock Portfolio Optimization with Support of Python

: Securities business activities are understood as the activities of organizations, individuals, securities companies, stock brokers and other intermediary financial institutions in the stock market to perform operations. Securities trading aims to make a profit. A common task in portfolio management is to find the optimal investment portfolio according to the return and risk approach, that is, for the same level of risk, portfolio whose highest return gives is the optimal investment portfolio. Similarly, corresponding to the same predetermined rate of return, the portfolio with the lowest level of risk is the optimal investment portfolio. There are several popular data analysis tools today, including Python. This article will demonstrate the application of Python tools in data analysis to determine optimal stock investment portfolios.

Foreign direct investment from Japan, South Korea and China in the Czech Republic: A comparative analysis

Multinational companies from Japan, South Korea and China began to actively penetrate Czech market starting from the mid-1990s. By 2021, Japan was the leader in terms of foreign direct investment stock in the Czech Republic ($ 4.7 billion), followed by South Korea ($ 3.4 billion); and China ($ 760 million). The methodological basis of the paper is Dunning’s eclectic paradigm, which makes it possible to explain foreign investment activities from the point of view of the simultaneous availability in these processes of ownership, location and internalization advantages. As a result of a comparative analysis, the author comes to the following conclusions. In the processes of activity of foreign affiliates of Asian companies in the Czech Republic (as part of the implementation of existing ownership advantages), the following features were identified: concentration on the main field of activity of the parent company; concentration of activity in those industries that are most developed in the Czech Republic (industry agglomeration effect); clustering of affiliates around the leading company and main activity; diversification of the activities of foreign affiliates by supplementing the main activities of the parent company with the activities in related sectors. To explain the weak presence of Chinese MNCs in the Czech market and the more deep activity of South Korean and Japanese MNCs, a “wedge-shaped” foreign market entry was proposed; it is based on the idea of internalization advantages of. The leading company represents a spearhead of the “wedge-shaped” foreign market entry. A large MNC possesses powerful and well-developed ownership advantages. It is the first to enter foreign market in the sector that is main one for its activity in the national market; and it is followed by foreign affiliates operating in the main and related sectors in a kind of expanding “wedge”. It is the penetration that enables MNCs to gain a foothold in the market, leveraging both ownership, location and internalization advantages.