Stock Market Investors Research Articles

Motivations for Socially Responsible Investing: The Impact of Attitudes, Subjective Norms, and Financial expectations

This study looks forward to exploring and understanding what the reasons for the desire of retail investors in might be making Socially Responsible Investments (SRI) in the Chinese stock market and to get an estimate of how valid the theory of reasoned action (TRA) could be. This is intended to look at how such factors as attitude, subjective norms, financial expectations, and risk propensity influence investors to engage in SRI in China. This research builds on previous studies that introduced financial expectations as a crucial new construct, enhancing the depth and rigor of TRA model in examining investment intentions. This assumption posits that investors comprehensively consider the investment situation, weighing not only its societal impact but also its financial returns, and only after considering these outcomes comprehensively will they make decisions on SRI. Risk propensity has been used as moderator in this research model relationship. Whether risk propensity influences the association between attitude, subjective norms, and financial expectations with investment intentions has been test in this study. The study results show risk propensity plays a significantly moderate role in relations of attitude, subjective norms, and financial expectation to intentions with the analysis indicating a positive effect. Its results will be able to provide more reference for the SRI studies and a new angle for capital market researchers, market information providers, and investors.

From Theory to Practice: Applying the Markowitz Model in Stock Portfolio Management under ESG

The study consisted of a month-long simulated stock market operation focusing on the comprehensive analysis of equity portfolio creation and management. Against the backdrop of growing concern for environmental protection, the S&P 500 Net Zero 2050 Climate Transition ESG Index was deemed the appropriate benchmark for the portfolios due to the average level of risk tolerance of customers. The investigation began with an in-depth assessment of macroeconomic and sector conditions, followed by careful selection of securities using both fundamental and technical analysis techniques. The portfolio was then optimized using the Markowitz model and subsequently managed using a variety of strategies, including trading, monitoring, and rebalancing. The subsequent phase of the research involves a rigorous evaluation of performance utilizing various metrics including single-period returns and the Sharpe ratio. The study culminates in a reflective analysis of the overall investment project. Despite the portfolio's underperformance against the benchmark, the project provides invaluable insights into the intricacies of stock market investment and portfolio management, accentuating the impact of market volatility and the significance of strategic asset allocation.

A Study on Employees Perception From Govche India Private Limited Towards Investing in Indian Stock Market

Stock market investments have become a typical occurrence for all people today. The development of the country's stock markets has a significant impact on the growth of the national economy. Global financial market developments have opened up a wide range of markets and investment opportunities for investors. Making investment decisions is a difficult undertaking that requires extensive analysis. Research has been conducted to identify the variables affecting investors' preferences and investment choices. Through the use of a structured questionnaire, primary data is acquired. The study included 107 respondents as its sample size. Data was analysed in this study using percentages, chi square, and Anova. It has been discovered that economic factors such as currency strength and legal considerations have an impact on investment choices.

Broadband Internet and the Stock Market Investments of Individual Investors

ABSTRACTWe study the effects of broadband internet use on the investment decisions of individual investors. A public program in Norway provides plausibly exogenous variation in internet use. Our instrumental variables estimates show that internet use causes a substantial increase in stock market participation, driven primarily by increased fund ownership. Existing investors tilt their portfolios toward funds, thereby obtaining more diversified portfolios and higher Sharpe ratios, and do not increase their trading activity in stocks. Overall, access to high‐speed internet spurs a “democratization of finance,” with individuals making investment decisions that are more in line with the advice from portfolio theory.

The peer effects of resident stock market participation: Evidence from 2019 CHFS.

Limited resident's participation in the stock market has become a key constraint to the capital market development. Utilizing the 2019 China Household Financial Survey (CHFS) data, our paper designs probit models to examine the peer effects of residents' stock market participation and explore the intermediary mechanisms with a multiple intermediary model. We find that: (1) Resident involvement in stock market decision-making exhibits significant peer effects. (2) Heterogeneity analysis reveals that males and rural residents display more pronounced peer effects than females and urban residents. Additionally, middle-aged residents demonstrate more potent peer effects than their younger and older counterparts, with the intensity of peer effects correlating with education levels. (3)We observe that the peer effects of market participation operate by altering economic expectations and enhancing residents' financial literacy. (4) Further investigation establishes that individuals engaging in stock market investments manifest peer effects when deciding whether to diversify their stock portfolio. This study holds reference value for analyzing the impact of social interaction on financial behaviors and regulating individuals' financial conduct.

Asymmetric impacts of coal prices, fintech, and financial stress on clean energy stocks

The emergence of fintech has revolutionized financial systems, alleviating financial stress through innovative solutions and diversification. This shift towards clean energy stocks has reduced demand for coal, impacting coal prices significantly and highlighting the pressing need to preserve mineral resources for sustainable, cleaner energy alternatives. Therefore, the study examines the interconnectedness between coal price, fintech, financial stress, and green energy stock using quantile-based regression. The findings reveal that the impact of coal price, fintech, and financial stress on the clean energy stock is heterogeneous across all levels of quantiles. Specifically, the findings indicate that variations in the coal price positively influence the clean energy stock index, yet this association displays asymmetry across quantiles. Fluctuations in the fintech index contribute to the susceptibility of renewable energy stock prices. The financial stress index exhibits a consistently adverse influence on clean energy stock across quantiles ranging from lower to higher orders. The study findings would guide stock market investors, ecological activists, and policymakers at administrative levels aiming to promote clean energy investment while controlling for the adverse outcomes from financial stress.

Perceived Behavioral Factors and Individual Investor Stock Market Investment Decision: Multigroup Analysis and Major Stock Markets Perspectives

The study aims to examine the impact of various behavioral biases such are overconfidence, representativeness, availability, anchoring and herding, and their effects on individual investment decisions in the case-developed country context of China. To achieve this, data was meticulously gathered from 362 participants active in the Shanghai stock market. Employing advanced analytical tools, particularly the Smart PLS 3.3.2 software and structural equation modelling (SEM), this study rigorously scrutinized the intricate relationships between behavioral biases and investment decisions. The findings of this study notably reveal that all examined behavioral biases exert a significant positive impact on investment decisions within the Anxin, Haitong, Shanxi, and China Galaxy stock markets. Remarkably, no substantial disparities in the effects of these biases on stock market trading were observed among these markets. Importantly, these findings bear exceptional significance within the context of a developed country like China. The implications extend to a wide spectrum of stakeholders, including government entities, regulatory bodies, practitioners, the academic community, industry professionals, and researchers. Regulatory authorities can leverage these insights to refine their strategies, practitioners can fine-tune their investment advisory approaches, and academia and researchers can build upon these findings to deepen the understanding of behavioral finance in the realm of stock market investments.

Islamic Capital Market Investment Alternatives Facing the 2024 Election Year

This research aims to determine alternative investment instruments that are relevant in the Islamic capital market in the 2024 election period. This research uses a library research method, which involves collecting relevant data or library materials beforehand. The data source in this research is secondary, meaning that the data is obtained from other sources such as documents, books, and related references, not from primary sources. The results of this research are that the development of investment in the Islamic capital market during the election period in the previous year experienced a good increase. from stock instruments, mutual funds, and sharia shares and the recommended investment, namely Sukuk, is considered an instrument that is relatively unaffected because it has a guarantee from the law. Sharia mutual funds show positive long-term growth potential, especially for mutual funds that focus on shares. This performance is influenced by the momentum of the underlying stock. In this context, investors in the Islamic stock market are advised not to make hasty investment decisions. The analysis shows that the infrastructure sector and the information technology (IT) sector have a significant positive influence.

Sambut Tahun Baru Belajar Investasi Seru Bersama Siswa/i SMKN Negeri 3 Bengkulu Tengah

Technological changes and developments must be utilized by all groups, not only for consumption but can be used as a tool for investment, investment in this case is stock and capital market investment which can be done by all groups, including students. The problem that occurs at SMKN 3 Central Bengkulu is that students and teachers do not yet fully understand investment in the capital and stock markets. With this problem, the community service team consisting of lecturers from the Faculty of Economics and Business, Dehasen University, Bengkulu, in collaboration with the Indonesian Stock Exchange, representatives of Bengkulu, provided material regarding the capital and stock markets. The solution that the community service team can provide at SMKN 3 Central Bengkulu is to provide assistance in operating the applicationProfits Anywhere which has been downloaded by students and teachers on their respective smartphones. In this case, the method used is preparation, observation and presentation of the FGD. With this activity, students and teachers understand more about capital and stock market transactions and the importance of cultivating an entrepreneurial spirit in life and will later be able to gain profits without just relying on job vacancies from the government and private sectors.

PRICING OF EQUITY INVESTMENT - AN EMPIRICAL ANALYSIS OF INDIAN CAPITAL MARKET

The investment is stock market is an art as well as science. The objective of stock market investment is to achieve superior returns comparing other investment options. The investment cost is one of the variable contributing towards the performance of the stock. The justified price of the stock is always a matter of discussion but no specific formula or theory exist to recognize the correct price. This paper is an attempt to decompose the market price of the stock listed on Indian exchanges. Using the data for 10 years, explanatory variables are identified which explain market price of the stock. The model identify the significant factors explaining 62 per cent changes in the market price. The findings of the study are useful to all academicians, researchers and market participants to understand the complex dynamics of market price of the stock and its explanatory factors.

Benchmarking asset pricing models in emerging markets: evidence from Borsa Istanbul

PurposeInvestors who can transfer their savings to investments in a well-regulated market benefit not only themselves but also economic development. Hence, it is crucial for fund owners to evaluate their stock market investment decisions. The goal of the study is to understand which model determines the asset returns most efficiently. In this regard, the validity of single and multi-index asset pricing models (capital asset pricing model-CAPM and Fama–French models) has been examined in the Turkish Stock Exchange for 2009–2020, with the quantile regression (QR) approach.Design/methodology/approachOn 18 portfolios comprised of quoted stocks in the Istanbul Stock Exchange 100 (ISE-100/BIST-100), we test the CAPM, the Fama and French three factor model (FF3) and the Fama and French five factor model (FF5). Empirical analyses have been carried out via QR approach regressing the portfolios' average weekly excess returns on risk premium/market factor (Rm-Rf), firm size, book value/market value (B/M), profitability and investments factors. QR estimation has been employed since QR is more effective and provides a better definition of the distribution’s tails.FindingsOur empirical findings have revealed that the average excess weekly returns can be explained more strongly via CAPM. Moreover, Fama and French models are expected to give more reliable result with more data, whereas the market premium would give robust results for the Turkish Capital Market.Practical implicationsIndividuals investing in financial assets must find the price model that best fits the market. The return can be approximated in the most appropriate manner using the right variables.Originality/valueThe study differs from other research by comparing the asset pricing models via examining the assets' weekly returns with QR in the Istanbul Stock Exchange 100 (ISE-100).

Perception of Generation Z on Stock Market Investment in Rajkot City

Perception of Generation Z on Stock Market Investment in Rajkot City

Stock portfolio optimization for risk-averse investors: A novel hybrid possibilistic and flexible robust approach

This study proposes stock portfolio optimization models for risk-averse investors under uncertain conditions. To accomplish this, the study measures risk based on the conditional drawdown-at-risk (CDaR) measure, which can prevent major declines in investment as a conservative investment strategy. Given the uncertain character of the input parameters of the problem, the study first proposes a hybrid possibilistic and flexible model by considering the CDaR measure (CDaR-HPFM) to handle uncertainty. Furthermore, to offer more robust outcomes, the study constructs a hybrid possibilistic and flexible robust model by considering the CDaR measure (CDaR-HPFRM), in the forms of a non-linear and a linear mathematicalprogramming problem. The CDaR-HPFRM can process the robustness of output decisions while dealing with uncertain parameters. The real stock exchange data of 100 companies registered on the Tehran Stock Exchange are investigated to validate the functionality of the proposed models. The results reveal that, when various penalty costs are factored in, the CDaR-HPFRM yields more efficient and more robust results than the CDaR-HPFM. Comparative results also indicate that the proposed models almost always outperform existing methods, in terms of both CDaR and rate of return measures. Proposed models can be used for all types of stock market investments (including micro-investing and investment funds) and can handle portfolio optimization and selection processes in project-based organizations.

An Intelligent Approach for Predicting Stock Market Movements in Emerging Markets Using Optimized Technical Indicators and Neural Networks

Abstract Integrating big data analytics and machine learning algorithms has become increasingly important in the fast-changing landscape of stock market investment. The numerical findings showcase the tangible impact of our methodology on the accuracy and efficiency of stock market trend predictions. Identifying and selecting the most salient features (technical indicators) is critical in predicting the trend direction of exchange-traded funds (ETFs) in emerging markets, leveraging financial and economic indicators. Our methodology encompasses an array of statistical techniques strategically employed to identify critical technical indicators with significant implications for time series problems. We improve the efficacy of our model by performing systematic evaluations of statistical and machine learning methods across multiple sets of features or technical indicators, resulting in a more accurate trend prediction mechanism. Notably, our approach not only achieves a substantial reduction in the computational cost of the proposed neural network model by selecting only 5% of the total technical indicators for predicting ETF trends but also enhances the accuracy rate by approximately 2%.

Deep Learning-Based Stock Market Prediction and Investment Model for Financial Management

This study explores the potential application of deep learning techniques in stock market prediction and investment decision-making. The authors used multi-temporary stock data (MTS) for effective multi-scale feature extraction in reverse cross attention (RCA), combined with improved whale optimization algorithm (IWOA) to select the optimal parameters for the bidirectional long short-term memory network (BiLSTM) and constructed an innovative RCA-BiLSTM stock intelligent trend prediction model. At the same time, a complete RCA-BiLSTM-DQN stock intelligent prediction and investment model was established by combining the deep Q network (DQN) investment strategy. The research results indicate that the model has excellent sequence modeling and decision learning capabilities, which can capture the nonlinear characteristics and complex correlations of the market and provide more accurate prediction results. It can continuously improve the robustness and stability of the model through adaptive learning and automatic optimization.

Herding behaviour in the Indian stock market: An empirical study

The rapid growth of the Indian stock market in recent decades has prompted much study on investing, focusing on understanding and analysing investors' tactics for investment and trading. Over the years, researchers have cited and conducted in-depth investigations into various psychological biases. Herding bias is extensively studied to understand how investors participate in investment and trading in the Indian stock market. The current study on herding provides an investigation into the existence of herd activity in the share market of India. The study attempts to identify herd activity during positive, negative, extreme positive, and extreme negative market conditions, as well as during structural breakpoints and trade volumes that are low as well as high. The researchers have used the modified CSAD (Cross Sectional Absolute Deviation) model to enhance its validity. The findings reveal the rationality of investors during the different market states. However, herding behaviour was evidenced during certain periods at the structural breakpoint. This implies that during positive as well as negative market conditions, herding behaviour is absent, except during certain structural breakpoints and high trading volumes.

The Role of Financial Development in Economic Growth using WPM Method

Financial development is possible investments creating information about and allocation of capital, monitoring of companies and corporate administration, commerce, diversification and risk management, accumulation and accumulation of savings, exchange of goods and services in activities like facilitation includes improvements. provided by financial institutions economic theory, at best and efficient financing institutions-banks, stock markets and bond markets-which capital it’s for high production applications paying is for economic growth beneficial. development of developing Asia strong to retain and efficient financial systems particularly important are because the performance of the investment as a driver of the region's development reduces the amount of investment. Since the early 1990s the region's financial systems are deep and diversified data indicate. 125 countries more formal econometrics on panel data quantitative analysis, financial development significant in development positive effect confirms having, especially in developing countries. of financial development in the development of the region impact than elsewhere significantly different thatno, for the asian financial crisis since then its influence has weakened the results also indicate that financial intermediaries, these teachers are bankers finance in the weakness of the sector effect of liberalization Is it a temporary effect will check that, that is, in the following years only this is observed. beginning of liberalization. this is not the case. of the banking sector weaknesses will only become apparent over time. however, in developing countries financial Liberalization Policy as an important part of the reform has Among some researchers, it is about virtues reflects overall confidence financial liberalization is that of the banking sector lead to weakness significant factor is, also of economics status even after controlling that there is this effect they found, the first one below income in the area earning funds summarize the implications the first one below review the area we do. income, cost and Savings, investment and wealth accumulation financial statements of we briefly reviewed do. The second division financial institutions orrole of intermediaries deals with The third section income, interest and money conventional theories about funding for real development between growth and development for important contacts enough attention that he did not pay some theoretical adaptations proposes and argues. The purpose of this paper is tofield-projectseveral in conjunction with the detain determinations and measurement perceived at a distance water using data for productivity mapping (WPM)methods and protocols is to create. Stock Market Investments, Real Estate Investments, Cryptocurrency Investments, Peer-to-Peer Lending and Startups and Venture Capital. Risk Management, Return on Investment (ROI), Portfolio Diversification and Costs and Fees. the Ranking of Financial development. Real Estate Investments is got the first rank whereas is the Cryptocurrency Investments the Lowest rank.

Impact of Fınancıal Knowledge and Investor’s Personalıty Traıts on Investment Intentıon: Role of Attıtude and Fınancıal Self Effıcacy

In recent years, there has been an upsurge in stock market investment intentions. Researchers are therefore becoming more and more eager to look into the factors that influence investors in general, and individual investors in particular to engage in stock market activities. Under the assumption of the theory of planned behavior this study looked at investor's intentions to invest in the stock market. The study primarily focusses on the impact of financial knowledge, personality traits, subjective norms, attitude, and financial selfefficacy on the stock market investment intentions of individual investors. To gather information from individual investors, the study used a cross-sectional research approach, on the population sample of 298 individuals. The data is collected from the Pakistani investors, from three big cities, i.e. Islamabad, Lahore and Karachi, also considered as business centers of the country. The respondents include both the salaried workers and business owners. The findings indicate that attitude and financial self-efficacy were significant mediators for investors’ investment decisions. The results imply that people with a favorable outlook on investing in the stock market, risk-taking and innovative personalities, and financial expertise are more likely make investments. Those who have a mindset towards investing and financial selfefficacy also have more intentions.

Volatility contagion between cryptocurrencies, gold and stock markets pre-and-during COVID-19: evidence using DCC-GARCH and cascade-correlation network

The rapid rise of Bitcoin and its increasing global adoption has raised concerns about its impact on traditional markets, particularly in periods of economic turmoil and uncertainty such as the COVID-19 pandemic. This study examines the extent of the volatility contagion from the Bitcoin market to traditional markets, focusing on gold and six major stock markets (Japan, USA, UK, China, Germany, and France) using daily data from January 2, 2011, to June 2, 2022, with 2958 daily observations. We employ DCC-GARCH, wavelet coherence, and cascade-correlation network models to analyze the relationship between Bitcoin and those markets. Our results indicate long-term volatility contagion between Bitcoin and gold and short-term contagion during periods of market turmoil and uncertainty. We also find evidence of long-term contagion between Bitcoin and the six stock markets, with short-term contagion observed in Chinese and Japanese markets during COVID-19. These results suggest a risk of uncontrollable threats from Bitcoin volatility and highlight the need for measures to prevent infection transmission to local stock markets. Hedge funds, mutual funds, and individual and institutional investors can benefit from using our findings in their risk management strategies. Our research confirms the utility of the cascade-correlation network model as an innovative method to investigate intermarket contagion across diverse conditions. It holds significant implications for stock market investors and policymakers, providing evidence for potentially using cryptocurrencies for hedging, for diversification, or as a safe haven.

Extreme Connectedness Across Chinese Stock and Commodity Futures Markets

This study examines the price spillovers and connectedness among stock markets, the Shanghai Stock Exchange Composite (SSEC) index, Hang Seng index, Shenzhen Stock Exchange (SZSE) index, commodity futures markets, Aluminum (AL), Gold (AU), Copper (CU), Zinc, Steel Rebar, and Natural Rubber in bearish and bullish market situations. We use the quantile connectedness approach of Ando et al. (2022) to calculate hedge coverage ratios, optimal portfolio weights, and hedge coverage effectiveness. Our empirical analysis yields several important results. First, there is no difference in the results of the TVP-VAR-DY and TVP-VAR models in relation to the magnitude of return transmission during the sample period. Second, CU is the main transmitter and AU is the main receiver of shocks from the network. Third, under the QVAR method estimations, the CU (AU) is the major (minor) contributors to the network during the normal, bearish, and bullish market statuses. Fourth, the results of the hedge ratio strategy confirm that CU and AU are respectively the most and the least expensive assets for a long-term investment in the Chinese stock market in different market conditions.