Stock Investment Research Articles

The Role of Behavioral Factors on Investment Decision Making: Moderating Role of Financial Literacy

The purpose of this paper is to examine the impact of behavioral finance factors on stock market investment behavior. Moreover, it also determines the moderating role of financial literacy in behavioral finance factors and stock investment in Pakistan. Studies have been conducted on Pakistan Stock market investors. Data has been collected through a structured questionnaire. The survey was performed among 165 investors in the Pakistan stock market. SPSS and Smart PLS 3.0 were used to test the hypotheses. The study concluded that Overconfidence, Herding, Loss Aversion, and Risk Perception significantly impacted the performance of Stock Investment decision-making. Moreover, Stock Investment decision-making was also moderated by Financial Literacy except for risk perception. The findings of this study would help to comprehend the behavior of investors in the Pakistan stock market. Moreover, to achieve favorable outcomes, investors must possess financial literacy about the stock market.

Implementation of IndoNLU Pre-Trained Model for Aspect-Based Sentiment Analysis of Indonesian Stock News

Investors in Indonesia are increasing from year to year, especially mutual fund investors managed by investment managers. News is one of the factors considered by investment managers in making stock investment decisions. Very diverse news sources and different writing styles can make it difficult to retrieve information on each issuer in the news. In this research, the aspect-based sentiment analysis (ABSA) method is implemented to extract news specifically on each aspect (issuer) in the news and evaluate the issuer. The model used is a pre-trained Indonesian Bidirectional Encoder Representations from Transformers (BERT) model, IndoNLU, because the object of research is Indonesian-language stock news. The results show that with a combination of hyperparameters consisting of batch size 8, learning rate 0.00002, and epoch 8 for the IndoNLU model can produce an average evaluation metric value consisting of precision, recall, f1-score, and accuracy of 90%.

Window Dressing Phenomenon on LQ45 Stock Investment Decisions with a Modern Technical Analysis Approach

The anomalous phenomenon of the windows dressing market has the potential to distort stock prices amidst the issue of an economic recession which is predicted to occur in 2023. This research aims to analyze the trend of LQ45 index stock price movements amidst the windows dressing phenomenon. This type of research is descriptive with a qualitative approach using secondary data. The research subjects are the Top 5 Constituents on the LQ45 Fact Sheet as of September 2023 published by the BEI. The object of the research is graphic data and monthly stock price movement trends for 5 issuers in the fourth quarter starting from October-December 2023. The data is analyzed using a modern technical analysis approach using the Relative Strength Index and Bollinger Band indicators via the tradingview.com website. The research results show a weakening of the short-term share price trend for LQ45 index issuers, which is likely due to a temporary correction, while the long-term fundamental prospects for several issuers are still positive.

Nonfragile security control for time‐varying cyber‐physical systems operating over multipath networks

AbstractThe main focus of this article is to explore the finite‐time stabilization of time‐varying cyber‐physical systems (CPS) that are operating over multipath networks and under random denial‐of‐service (DoS) attacks. In contrast to prior studies, we present a set of necessary and sufficient conditions for achieving finite‐time stability in the closed‐loop model of CPS operating over single‐path network. Notably, this equivalent conditions are established based on the analysis of the state transition matrix (STM). Additionally, we utilized auxiliary systems to study more general CPS operating over multipath networks and obtained a sufficient condition based on STM. Finally, we address a sufficient condition based on the Lyapunov function and introduce a linear matrix inequality (LMI)‐based approach that facilitates the computation of nonfragile controllers. The effectiveness of the developed theoretical results is verified through a stock investment model.

The Impact of The Russia-Ukraine War on The Dynamics of The Asean-5 Stock Market

The capital market can be defined as activities related to public offerings, securities trading, public companies, institutions, and certain professions. One of the factors considered in stock investment is the Efficient Market Hypothesis. The Efficient Market Hypothesis is a financial theory that discusses how asset prices in the market already reflect all available information. This study employs an approach to detect market reaction and market efficiency based on the event of the world oil price decline due to the Russian invasion of Ukraine on March 10, 2022, through excess or abnormal return, price impact, and fluctuation patterns observed using a multifractal model. The research results on the abnormal return of the ASEAN-5 stock index showed a significant negative reaction at t-5 and t-3 during the event of the world oil price decline due to the Ukraine and Russia war in 2022 and a significant positive reaction at t-0 during the event. The average abnormal return before and after the announcement of the world oil price decline due to the Ukraine and Russia war in 2022 showed a significant negative reaction, but there was no significant difference in price impact between before and after the event. The efficiency level of the stock index in ASEAN-5 did not show a significant difference after the announcement of the world oil price decline due to the Ukraine and Russia war in 2022.

Navigate The Ins And Outs Of Investing Through Tips And Strategies For Financial Success In LQ45 Stock Selection

This article explains the various important aspects of navigating stock investing to achieve financial success. In this article, we will discuss tips and strategies that can help investors make smart decisions in choosing LQ45 stocks. LQ45 is a stock price index of the 45 largest and most liquid companies on the Indonesia Stock Exchange (IDX). We present a practical guide to understanding the characteristics of LQ45 stocks, Readers will gain valuable insights to understand the intricacies of stock investing and achieve their financial goals. Emphasis is placed on investment strategies that have the potential to provide profitable returns. By understanding these tips and strategies, investors will have a solid guide on LQ45 stocks to achieve their financial goals through stock investing.

Tools for studying the digital development rates of economic systems at country and region level

National economy digitalization is a powerful economic growth engine and one of the key areas for developing and maintaining the competitiveness of the state. Digital economy potential lies in accelerating the pace of economic development of enterprises, industries, regions and countries, and in improving in living standards. Under the conditions of digitalization, a tool for assessing the pace of economic system development at the country, region, industry and enterprise level becomes a source of competitive advantages. Therefore, the relevance of the study is evident. The purpose of the study is to develop tools for studying digital development rates at country and region level. The database of the study was represented by the proceeding of well-known foreign and Russian scientists and statistical data on the main indices of the US and Chinese stock markets. The methodological base was represented by the ISPI (Information System Portfolio Investor) digital model. The effectiveness of the obtained results was verified using the PRM (Profitability-Risk model) tool. The result of the study was an analysis of digital development rates at the country level by the case of the United States and China. The analysis was based on the calculation of the main parameters of the portfolio theory: expected return, risk level, return-to-risk ratio. Scatterplots were constructed for the main US and Chinese stock market indices based on the fitted data. They show the mutual distribution of groups of main indices and allow to determine the most promising areas for investment, including digital development. The findings confirm the possibility of using the proposed tools to determine the most attractive sectors for investment in the world stock markets and countries, and/or countries and regions that need investment for their development, including digital one. The introduction of the proposed tools into practice at the enterprise, industry, region and country level will contribute to the further development of the digitalization in all aspects of society at the enterprise, industry, region and country level.

THE IMPACT OF SUSTAINABILITY COMMITMENT ON CRASH RISK IN ASEAN-4 COUNTRIES

This study aims to analyze the impact of corporate sustainability commitment on stock market crash risk in ASEAN-4 countries during the period 2015-2019. This study examined 76 ASEAN-4 public companies using the ordinary least squares (OLS) regression analysis. Empirical results show that the corporate sustainability commitment has a negative and significant impact on the stock market crash risk, indicating that there was a tendency for the companies with a stronger sustainability commitment to experience a lower crash risk. In relation to the interaction between sustainability commitment and ownership structure associated to the crash risk, there is an interaction in the relationship between dependent and the independent variables, although the nature of the relationship is attenuated and significant. This study also employed the Fama-Macbeth regression method for robustness checking and the results confirm that the sustainability commitment has a negative and significant impact on the crash risk. These findings are expected to provide greater insights for investors regarding stock investment strategies by incorporating corporate sustainability concerns and the regulatory policy implications for market resilience during crises through the sustainability commitment.JEL: G32, G10.

Determining Factors Of Sharia Stock Returns With Bi Rate As A Moderating Variable

Research regarding the factors influencing Shariah stock returns is essential due to the existing disparities where Shariah stock returns continue to exhibit fluctuations amidst the annual increase in the number of issuers and stock investors. The objective of this study is to ascertain the influence of Earnings per Share (EPS), Return on Equity (ROE), and Price to Book Value (PBV) on Shariah stock returns, moderated by the BI rate. The population for this research encompasses all companies listed on the JII for the period 2017-2022. The sampling technique employed is purposive sampling, resulting in a total sample size of 18 companies, yielding 108 observations over a span of 6 years. The data analysis technique utilized is Moderated Regression Analysis (MRA), conducted using Eviews 12 software. The findings of this study reveal that EPS and PBV exhibit a negative and significant impact on Shariah stock returns, while ROE demonstrates a positive and significant influence. The BI rate weakens the influence of ROE on Shariah stock returns, whereas it reinforces the effect of PBV on Shariah stock returns. However, the BI rate does not possess the capability to moderate the impact of EPS. It's important to note that this research is confined solely to companies listed on the JII, consequently suggesting the need for future studies to broaden the population, extend the research period, and incorporate additional variables that may potentially impact Shariah stock returns.

COMPARATIVE ANALYSIS OF STOCK PORTFOLIO RISK & RETURN”WITH SINGLE INDEX METHOD

This study aims to compare the return and risk of investment in blue chip stocks (first liner) and second liner stocks of manufacturing companies listed on the Indonesia Stock Exchange (IDX) during the 2022 period. The method used is qualitative with single index theory, and closing price data is used for analysis. The results show that a portfolio of second liner stocks provides higher expected returns and lower risk compared to first liner stocks. Nonetheless. This research provides insights for investors and the public about the investment alternatives of first liner and second liner stocks, and shows the importance of portfolio diversification in managing investment risk. Future research can expand the scope of industry sectors and other analytical methods to explore a deeper understanding of stock investment on the IDX.

Stock Investment Value Analysis Based on Sports Brand Section

This article briefly analyzes the risks, profitability, and market ratios of the stocks of three sportswear brands and gives investment advice for different types of investors. Lululemon, Nike, and VF Corporation are three sports industry brands. First, none of the three stocks are value stocks. Because of its better upward momentum, Lululemon would be a satisfying choice for momentum investors. Due to its insider buying of more than 4% and its highest ROA among them, Lululemon is also the best choice for insider buying and ratio analysis investors. Due to its PEG ratio of less than 1, dividend yield greater than 6, and DCF valuation higher than the current stock price, VF Corporation is popular with PEG, income, and DCF investors. NIKE has a stock buyback of more than 1B USD, which is the highest among the 3 stocks, so stock buyback investors are more inclined to invest in it. Lululemon and NIKE have market caps higher than 15B USD, so they have less size risk, which makes them more favored by index investors.

Stock Investment Strategies with Time-Varying Co-Movements Between Energy Market and Global Financial Market

One of central challenges in guiding investment mangement is how to intelligently identify investment strategies. This paper sets up a deeping learning model for realizing stock investment strategies with time-varying co-movements between energy market and global financial market: It uses LSTM neural network approach to predict energy stock price, and employs the improved time domain connectedness measures of Diebold and Yilmaz to test the spillover mechanism of market volatility shocks. By the propsed model, this paper explores the time pattern of volatility spillover between energy market and stock price in major global financial markets (mainly including stock market) from January 3, 2000 to December 31, 2020.

A Comprehensive Analysis of Stock Investment Recommendations Based on the Liquor Industry: Risk, Profitability, and Ratio Perspectives

Focusing on the liquor industry, this study takes Kweichow Moutai Liquor Co., LTD., Shanxi Xinghuacun Fen Distillery Co., LTD., and Sichuan Tuopai Shed Liquor Co., LTD., as the objects, and provides targeted investment suggestions for different types of investors by analyzing risk, profitability, valuation and other indicators. The results show that Kweichow Moutai has an excellent performance in market value and ROA, which is suitable for index investment and ratio analysis investors. Shanxi Xinghuacun Fen Distillery attracts the attention of income investors with its high dividend rate; Sichuan Tuopai Shede Wine's low PE Ratio may attract value investors. Depending on the type of investment, we provide investment advice for index investors, ratio analysis investors, income investors, value investors, PEG investors, discounted cash flow investors, momentum investors, insider trading investors and share buyback investors. The results and analysis of this study can help investors more accurately evaluate the investment value of different liquor companies to meet their specific investment objectives and risk preferences.

The influence of financial behavior on capital market investment decision making with mediating of financial literacy in Yogyakarta

The growth of capital market investors and financial literacy has increased every year and investors in making an investment decision However, financial theory argues that there are psychological biases that can influence investors in making inappropriate investment decisions. This study aims to examine the influence and analyze Overconfidence, Loss Aversion and Herding Bias on investment decisions and Financial Literacy as a mediating variable. Financial Literacy is used as mediating variable in the relationship of Overconfidence, Loss Aversion. However Herding Bias variables on Investment Decisions. This study uses non-probability sampling techniques to as many as 163 investors stock in Yogyakarta as respondents. Findings/Results: the study shows that overconfidence, loss aversion and herding bias have a significant effect on investment decisions and overconfidence, loss aversion and herding bias are not mediated by financial literacy in making investment decisions.

Do ESG ratings and COVID-19 severity score predict stock behavior and market perception? Evidence from emerging markets

PurposeThe purpose of this study is to examine the impact of firm environmental, social and governance (ESG) rating scores on market perception and stock behavior from 2017 to 2021 while controlling for COVID-19 severity score.Design/methodology/approachThe authors used panel regression models with robust standard errors based on cross-country and cross-industry sample of 1,324 ESG firms from 25 emerging countries across four regions. Four separate regression analyses are used. Hausman test is used to determine whether fixed-effect (FE) or random-effect approaches should be used in regression models. Lagrange multiplier test is used to test for time FEs, and F-test for individual effects to choose between pooled ordinary least squares model and FE. Two-unit root tests are conducted to check stationarity. Heteroskedasticity and serial correlation were controlled through a robust covariance matrix estimation.FindingsThe authors provide evidence that the stakeholder theory persists in emerging countries. Overall, the results suggest that firms’ stock behavior is positively associated with the level of environmental and social performance in the region. However, the results do not provide empirical evidence to support the link between ESG performance and stock market perception proxied by the price-to-sales ratio. The results suggest that Refinitiv and Bloomberg ESG rating scores have a positive impact on stock performance in emerging markets, albeit the Bloomberg rating score is insignificant.Practical implicationsFavorable impact of environmental and social performance on stock performance suggests that policymakers should take initiatives to raise awareness toward investments in ESG projects. Evidence shows that ESG stock performance in emerging markets does not insulate firms from the COVID-19 severity. Furthermore, this study highlights the inconsistency in calculating the ESG ratings, therefore, a more standardized approach is recommended to support investors seeking sustainable investments.Social implicationsThe findings have social implications for investors with proenvironmental preferences and nonpecuniary motives for ethical investments. Asset fund managers should develop ESG investment strategies to promote investor preferences that are linked to the proenvironmental and prosocial attitudes by increasing their investments in stocks of firms that behave ethically and support the environment. Furthermore, the findings show that investors pay a price for ethical and socially responsible investments as they are evaluating the environmental and social activities, hence, the firm ESG profile influences equity valuation and risk assessment.Originality/valueThe study extends the literature and provides evidence from the unique setting of emerging markets by analyzing the relationship between ESG rating scores and the COVID-19 severity scores on one hand, and stock behavior and market perception on the other.

Value at Risk Calculation of Digital Bank Stocks Portfolio in Indonesia

<p>Nowadays, stock investment has been increasingly growing in society. In investing activities, there are risks that may be experienced by investors. However, sometimes many investors do not realize how much risk that they might suffer in the future. One way that can be done to measure this risk is to calculate the Value at Risk (VaR). This study aims to calculate the VaR value of digital bank stock portfolio in Indonesia. The calculation of VaR will be done using two methods, include the Historical Simulation and Monte Carlo Simulation method. From the calculation, VaR with Historical Simulation and Monte Carlo sequentially generate results of IDR 6,006,718 and IDR 10,797,904 for 99% confidence level, IDR 4,135,857 and IDR 5,376,949 for 95% confidence level, and IDR 3,219,885 and IDR 3,417,553 for 90% confidence level. Based on the results, it is found that VaR result is directly proportional to the confidence level used. Through the calculation results, it also found that VaR value with the Monte Carlo Simulation method are greater than those with the Historical Simulation method.</p>

Stock Market Anomalies and Efficient Market Hypothesis: Empirical Analysis of Monday Effect of Selected Securities from Nigeria

This study was conducted to examine stock market anomalies and efficient market hypothesis with empirical analysis of Monday effect of selected securities from Nigeria. Daily stock prices of 20 quoted firms were sourced from www.cashcraft.com. The study used Friday 4/11/2022, and Friday 3/12/2022 to test against Monday Effect 7/11/2022 and Monday 5/12/2022. The prices of the stocks on Friday against Monday were used to test the market anomalies and the efficient market hypothesis. Findings of the study revealed a mix reaction of stock market anomalies and efficient market hypothesis among the studied securities. Evidence from table 1 and 2 proved that some stocks have return greater or less than zero which implies that investors in such stocks had abnormal return which contrary to the assumptions of efficient market hypothesis. However, some stocks have no return from the price of Friday and the price of Monday which implies that the investor have no return, this is in line with efficient market hypothesis. The study recommends that the regulatory authorities should develop the stock market such that the functioning of the market is in line with the stock market of the developed countries to reflect relevant assumptions and theories

A comparison of CAPM and Fama-French three-factor model under Machine Learning approaching

With the economy experiencing rapid growth in recent years, more individuals have started venturing into the stock market. Precisely forecasting the rate of return can mitigate investment risks for stock investors and significantly enhance their investment returns. The Capital Asset Pricing Model (CAPM) and the 3-factor Fama-French model (FF3) are widely recognized in academic and practical settings. This model comparison provides frameworks to analyze the relationship between portfolio risk and return in inefficient markets. This research utilized the Support Vector Regression (SVR) algorithm to forecast the returns of a diversified portfolio in the Hanoi stock market (HNX) from 2010 to 2022. Subsequently, the explanatory power of the CAPM and FF3 models were compared using the Ordinary Least Squares (OLS) algorithm. Finally, this research incorporated the SVR algorithm within the FF3 framework to develop a predictive model. The research findings demonstrate that the FF3 model provides a superior explanation to the CAPM model. Additionally, the study reveals that the SVR algorithm outperforms the OLS algorithm in terms of efficiency, as it yields lower Root Mean Square Error (RMSE) values. Consequently, the next research direction entails replacing the FF3 model with a more comprehensive multi-factor model, anticipating obtaining an enhanced predictive model.

Stock Price Time Series Data Forecasting Using the Light Gradient Boosting Machine (LightGBM) Model

In the world of stock investment, one of the things that commonly happens is stock price fluctuations or the ups and downs of stock prices. As a result of these fluctuations, many novice investors are afraid to play stocks. However, on the other hand, stocks are a type of investment that can be relied upon during disasters or economic turmoil, such as in 2019, namely the Covid-19 pandemic. For stock price fluctuations to be estimated by investors, it is necessary to carry out a forecasting activity. This study builds stock price forecasting using the Light Gradient Boosting Machine (LightGBM) algorithm, which has high accuracy and efficiency. To forecast stock price time series, the model used is the LightGBM ensemble. At the same time, they were optimizing the determination of hyperparameters using Grid Search Cross Validation (GSCV). This study will also compare the LGBM algorithm with other algorithms to see which model is optimal in forecasting price stock data. In this study, the test used the RMSE metric by comparing the original data (testing data) with the predicted results. The experimental results show that the LightGBM model can compete with and outperform boosting-based forecasting models like XGBoost, AdaBoost, and CatBoost. In comparing forecasting models, the same dataset is used so that the results are accurate, and the comparisons are equivalent. In future research, paying attention to the data during pre-processing is necessary because it has many outliers. In addition, it is necessary to include exogenous variables and external variables, which are determined to involve many parties.

FAKTOR-FAKTOR YANG MEMPENGARUHI PERTUMBUHAN INVESTOR SAHAM SYARIAH DI INDONESIA TAHUN 2015-2021

Factors Influencing Economic Growth on the Growth of Sharia Stock Investors in Indonesia in 2015-2021
 Stocks have recently been increasingly in demand by the majority of people in Indonesia, many phenomena have occurred including economic problems, crises, politics, and others, but these fluctuations do not affect people's interest in buying Islamic stocks. This study aims to determine the effect of the dollar exchange rate, inflation, and economic growth on the growth of stock investors in Indonesia.
 This type of research is descriptive research which is analyzed using quantitative analysis. The data used are the financial reports of Islamic banks in Jambi through the Financial Services Authority (OJK), in the period from March 2015 to December 2021. The prerequisite analysis test was carried out using the normality test, muticolinierity, heteroscedasticity, and linearity tests. Furthermore, the data were analyzed using multiple linear regression analysis.
 Based on the results of the study, it can be concluded that during the period from 2015 to December 2021, the dollar exchange rate has no significant effect on the growth of Islamic stock investors and inflation has a significant negative effect on the growth of Islamic stock investors in Indonesia, GRDP has a significant effect on the growth of stock investors in Indonesia. and simultaneously the Dollar Exchange Rate, Inflation, and Economic Growth are significant for the Growth of Stock Investors in Indonesia.