Stock Market Investors Research Articles

STUDY ON INVESTOR'S PERCEPTION TOWARDS MUTUAL FUND INVESTMENTS IN GUJARAT

The Indian economy is growing with economic reforms in the field of trade, commerce and industry which eventually increases the investment size in the capital market. The need and scope for mutual fund operations has increased tremendously as it is meant for converting savings of small investors into investment. The major reason behind the growth of the Mutual Fund industry is the reduction in the interest rates by the government on different financial instruments meant for small investors. This study mainly focuses on understanding the perception of investors of Gujarat towards Mutual Fund Investments. In this study, focus is given on analysing the preferred asset class and perception of investors falling under different income classes. Moreover, the study is concerned with the objectives of investors and type of mutual fund investment they prefer to meet their objectives in future. It was found that majority of the investors consider Mutual Fund as a systematic option for making investments in Stock market. They consider Mutual funds as an option for long term investment where the majority invest via SIP/STP mode. Hence, the findings from this research are that most of the investors consider mutual funds as a new age investment option and hence, the industry will grow at a rapid pace in the near future.

A Predictive Investment Scheme for Dhaka Stock Exchange

Stock market plays a vital role in industrial development of a country. People invest money to make profit from market. Inexperience investors cannot yield profit due to their weak predictions. This research tries to understand the nature of those investors and their demands. Most investors first analyze the prospect of companies based on rate of up-down in prices of share, given bonus, companies’ goodwill, temptation by others, etc.. This research presents a good prediction methodology for the stock market investors and thus, will help them to achieve a profit. It will improve the stability of a market.

A Study on Investor’s Preference towards Stock Market - Special Reference to Chennai City IT Employees

Stock markets functioning important role in developing countries. It is functioning as intermediate between the investors and the corporates. Investors have differing needs, and for each investor failure to meet those needs poses a risk. Falling short of the nest eggs or amount required for a particular goal is one of the major risks but also returns, failing which he or she could face the risk of outlive his or her investments. The trade-off between risk and returns is the most absorbing and challenging job for most investors. Investor’s perspective there are various investment options are available even though stock market is one of the most preferred investment destinations for maximum of the investors because high return as well as high risk as the concept in financial management. The purpose of the study is to identify and evaluate the investor to make right investment decision. The methodology perspective samples have been used purposive sampling techniques and the target audience are IT employees in Chennai. The primary data have been collected through structured questionnaire & secondary data through research papers, journals. The dependent and independent variables used for the study are stock market investor’s expectation, objectives, risk perception, influencing factor, preference which influences the decision. The findings of the study identified that financial constituents have direct relationship which influences the stock market investors. The result of the study gives an understanding in a better perspective to how and what are the factors influence an investment drive to be a sustainable decision.

Savings and Investment Behaviour of Academicians After the Withdrawal of Income Tax Deductions

This paper attempted to assess the tax-saving investment behavior of the academicians of Hisar district of Haryana after the withdrawal of tax deductions by using primary data. The primary data were collected from 337 respondents through a self-structured questionnaire and analyzed with Cronbach’s alpha, analysis of variance, Welch test, and multiple mean comparisons test (post-hoc test). The study found an insignificant difference in savings and investment behavior of academicians with regard to their savings in banks/post office/and cooperative banks, five-year bank/post office fixed deposits, public provident fund, health insurance, life insurance, term life insurance, unit-linked insurance plan, national saving certificate, employees provident fund/general provident fund, mutual funds, real estate, gold exchange trade fund, stock market, recurring deposits, and systematic investment plan even after the withdrawal of tax deductions across the different income levels. The current study will be helpful for government authorities and policymakers to understand the investment behavior of individuals after the withdrawal of tax deductions.

Corporate Diversification and Risk: Portfolio Effects and Resource Redeployability

By analogy with portfolio diversification by stock market investors, managers and researchers have often expected that firms that spread operations across product or geographic markets reduce risk. However, numerous exploratory studies in corporate strategy and in international business have not been able to robustly confirm this expectation. This study develops a formal model to scrutinize implications of corporate diversification for corporate risk. The model incorporates the key distinction of corporate diversification, economies of scope, that qualifies the analogy between corporate and portfolio diversification. The presence of a particular type of economies of scope, resource redeployability, not only inherently increases risk but it can also raise risk over the level in undiversified firms. The model uses determinants of resource redeployability from previous research to derive conditions with which corporate diversification enhances risk. The developed elaborate operationalization of corporate risk should facilitate future research and help corporate managers.Supplemental Material: The online appendix is available at https://doi.org/10.1287/stsc.2021.0154 .

Fundamental analysis and the use of financial statement information to separate winners and losers in frontier markets: evidence from Vietnam

PurposeThe pupose of the paper is to study the usefulness of Piotroski (2000)'s F-score in separating winners and losers in Vietnam.Design/methodology/approachThe authors adopt a portfolio analysis and regression analysis on a sample of 501 of listed firms between 2009 and 2019 in Vietnam.FindingsThe authors find that a hedge strategy that buys high-F-score firms and sells low-F-score firms yield market-adjusted return of over 30 percent annually, which is statistically and economically significant. The hedge strategy based on F-score is not only profitable for value (high book-to-market [BM]) firms but also earn abnormal returns in a sample of growth (low BM) firms, suggesting that the usefulness of F-score strategy is not just a phenomenon in value firms as documented in previous literature.Research limitations/implicationsWhilst the authors' paper documents economically significant returns obtained from the F-score strategy, the authors do not examine what drives the abnormal returns.Practical implicationsThe results provide supporting evidence for the use of financial statement analysis as a screening tool to improve the performance of value investment in Vietnam stock market and for the training of financial reporting and fundamental analysis in universities.Originality/valueThe authors' research is the first study examining the F-score strategy in Vietnam that provides insights about the usefulness of fundamental analysis in separating winners and losers in a frontier market and contributes to the literature on fundamental analysis and market efficiency in emerging and frontier markets.

Use of Econometric Predictors and Artificial Neural Networks for the Construction of Stock Market Investment Bots

Use of Econometric Predictors and Artificial Neural Networks for the Construction of Stock Market Investment Bots

Stock Market Investment Behavior Based on Behavioral Finance Based on Data Fusion Algorithm

The stock market is developing rapidly and the study of its investment behavior is indispensable. In this paper, based on the framework of fusion algorithm, information on various investor behaviors is federated based on IoT technology. Psychological experimental method is used to collect experimental sample data in the form of questionnaires. And based on the theoretical knowledge of behavioral finance, some investment recommendations on individual investors’ investment behavior are proposed. The results of this empirical study show that when individual investors face investment risks, the psychological bias of their perceptions is unfavorable to most of them. And the results prove that more than 50% of them are influenced by their own limited cognition.

The EFFECT Of Foreign Portfolio Investment (FPI) On The Performance Indicators: A Standard Analytical Study Of The Qatar Stock Exchange For The Period (2010-2020)

The aim of the research is to shed light on importance of foreign portfolio investment to attract foreign capital in order to revitalize the stock market. It also investigates the most important advantages provided by foreign portfolio investment and the extent of its reflection on market performance indicators. Furthermore, it measures the impact of foreign portfolio investment on the performance indicators of the Qatar stock exchange. The study was applied to the Qatar stock market for an annual data series from (2010-2020), and the statistical program (Eviews10) was obtained in analyzing the data. Results showed there is an impact of foreign portfolio investment on the performance indicators of the Qatar stock market. The results also proved the significance of both the market capitalization index and the financial depth index in the regression model used. It is recommended to developing investment agencies in order to provide accurate information regarding available investment opportunities. It also suggested providing tax incentives to investors who keep shares for a certain period in order to encourage long-term investment in stock market.

Impact of currency fluctuation on the Indian stock market and related investment opportunities

This paper assesses the impact of currency fluctuation on the Indian Stock Market and relative investment opportunities for an investor during the period 2013–2018. For this purpose, a descriptive as well as causal research is conducted where we have tested the hypothesis to come out with the major findings, conclusions, limitations and recommendations of this study. In order to achieve the main objectives of our study that is how currency fluctuation and several other factors impact the Indian Stock Market, how investors design their portfolio by investing in particular sectors to take advantage of currency fluctuation to gain maximum returns andfinally to establish a relationship between exchange rates and Nifty sectors we have used statistical techniques of data analysis like correlation, regression and ANOVA. Data is collected through primary as well as secondary sources. We established that Nifty50 and currencies like USD, Yen, Euro and GBP have a negative correlation and that USD is the most influential currency that affects Nifty50. Also, the auto index, power sector, oil and gas sector show negative correlation and IT index and healthcare show no significant correlation with USD. This paper recommends investors to sell their shares of the power, oil and gas sector when the Indian Rupee depreciates to reduce losses or go on a short position. Similarly, investors can go on a long position if the Indian Rupee appreciates. Also, Investors can either hold their existing positions or exit the market when it comes to IT and pharmaceutical sector as they can move in any direction due to currency fluctuation. All in all, to obtain maximum returns investors can look at inflation or interest rates to predict the currency movements, and thereby design their portfolio in the respective Nifty50 sectors.

The Long-Run Relationship Between ICT Indicators and Stock Market Indexes for G7 And E7 Countries

Since the late 1990s, information and communication technology (ICT) has caused changes in all fields, particularly in the stock markets. By using ICT technology, stock market investors had a chance to get information, reduce the trading cost and make optimal investing decisions. This study aims to examine the long-run relationship between stock market indexes and ICT indicators for G7 and E7 countries. The stock market indexes are taken as dependent and ICT indicators as independent variables,

Research on Short-Term Stock Price Trends Based on Machine Learning

With the increasing emphasis on economic development, China’s economy is growing steadily and significantly, and the stock market is becoming more diversified and richer in products and derivatives, resulting in a larger and larger base of investors in the Chinese stock market over the years, with more significant changes in the investment environment of the primary stock market. In the analysis and research around stocks, the fitting and prediction of stock price changes have been one of the keys in the field of stock analysis, however, the current models and solutions for stock price fitting and prediction have not been well received, and are lacking in terms of realistic operability and applicability. In recent years, machine learning and its related models and methods have been widely used in the financial field, which has also promoted the development of stock price fitting forecasting. In order to further improve the accuracy of stock price fitting prediction, this paper introduces the multi-factor prediction model in traditional quantitative stock analysis into the stock price fitting prediction method and improves the general stock price fitting prediction method. This paper finds that the screening of factors that can significantly affect stock prices can indeed be accomplished by using the methodological properties of GBDT and FFM.

INFLUENCE OF MAIN DIRECTIONS OF BEHAVIORAL ECONOMY DEVELOPMENT ON SOCIO-ECONOMIC PROCESSES

The article investigates the main stages and aspects of behavioral economics based on the works of foreign and Ukrainian scientists. The scientists’ main stages and achievements in the process of development of behavioral economics are highlighted. In accordance with the scientists’ economic and psychological approaches, the main scientific areas of behavioral economics are identified, among which we can indicate behavioral finance, which is based on the irrationality of human behavior. The main purpose of research in the field of behavioral finance is to study the impact of price changes or resource allocation on the market situation, investment sentiment, the ability to predict investor behavior, stock market value, consumption, investment and savings, and asset pricing. Knowing the main reasons for irrational actions of subjects, it is possible to manage similar situations therefore to avoid negative consequences. The main achievements of behavioral economics in the decision-making process of individuals based on the works of Nobel laureates G. Simon, D. Kahneman, M. Alli are studied. People's propensity to take risks, derive dependencies between income and losses, and people's behavior are studied using the utility function and basing on the scientists’ research and experiments. The research uses mathematical tools, such as game theory and prediction, but with the use of cognitive factors. It is determined that the study of irrationality of human behavior in trade and marketing activities for the strategic interaction of economic agents is of particular importance. It is especially important to study human social nature in the needs, desires, and goals, i.e. the use of social benefits by people. The impact of the COVID-19 pandemic on the country's economy and financial markets is becoming particularly relevant. It was found that the reaction of investors to the pandemic varies in different countries due to peculiarities of their national culture, different levels of individuality and uncertainty. This aspects are very important because the behavioral approach factors influence psychological factors, which are the most important in explaining many tasks of financial behavior for economic entities.

Volatility correlation structure, dynamic network and portfolio implications of Chinese stock market

This study combines complex networks and sliding window technology to construct a static and dynamic network of volatility of the stocks in CSI 300 index using the COVID-19 epidemic as an example to analyze the impact of public health emergencies on the correlation structure of stock volatility, as an extended application to mine low-risk stock portfolios that are more resistant to risks under the "mean-variance" framework. Research shows three implications. (i) During the outbreak period, the density of the stock market volatility network was significantly higher than before and after the outbreak, and the network structure was more intense during the outbreak period. The leading industries are the manufacturing and financial industries, and the source of market risk transmission comes from the key nodes of the two industries. (ii) The dynamic network shows that under the impact of the epidemic, the correlation structure of stock market volatility has undergone abrupt changes and the overall market risk is time-changing, which indicates that the sudden impact of degeneration breaks the original structure and triggers new information connections in the stock market. (iii) The degree of stock centrality affects investment portfolio returns, which means that core stock portfolios with greater network centrality during the relatively stable market period and the upward period perform better, and the peripheral stock portfolio has an advantage in the period when the market fluctuates due to sudden external shocks. Interestingly, peripheral stock portfolios with lower centrality are more resistant to risks under sudden shocks. The results of this paper can provide important enlightenment for stock market supervision and investment portfolio risk management.

Does supplier concentration matter to investors during the COVID-19 crisis: evidence from China?

The literature shows that investor attention to customer–supplier disclosure increases when suppliers’ information arrival is anticipated. Due to the widespread of city lockdowns in China and the implementation of social distancing to control the COVID-19 pandemic, investor attention to potential disruption of the supply chain spikes, leading to a price devaluation for firms with high supplier concentration risk. We find that a higher degree of supplier concentration is related to more serious stock price declines over the short-term and medium-term windows right after the Wuhan lockdown. This result lends support to the argument that the concentration risk of suppliers is a significant consideration for China stock market investors, especially under the potential financial distress at the firm level induced by the COVID-19 crisis.

Stock Tender Offer and Stock Prices: Evidence from the Indonesian Stock Exchanges

This study is to investigate the movement of stock price in a tender offer strategy by the firm. The ultimate of success and failure of tenders offers of a firm can be predicted by the stock prices movements. Twenty-three firms listed in Indonesian Stock Exchange are selected as a sample to be analyzed which carry out the tender offer during COVID-19 Pandemic period of year 2020 to 2022. The tender offer positively affects the stock price at the first day after tender offer period and the average stock price of one month period after the tender offer period. This study also shows that the difference between tender offer price and stock price of one day prior the tender offer period will negatively affect the stock price of one day after tender offer period and the average stock price of one month period after the tender offer period. The proportion of number of stocks to be offered in tender offer has no effect on stock price both in one day after stock tender offer period and the average stock price of one month period after the tender offer period. The result of the study is important for the stock market investors to get abnormal returns by buying stocks which will carry out a tender offer strategy and consider the motivation of firm to enhance the firm performance and good reputation of the prospective buyer.

Stock Price Prediction Using Machine Learning

Shares in publicly traded companies, or equity shares, can be purchased and sold on the stock market. There are three basic types of stock market investors. All three types of investors: FII (foreign institutional investors), DII (domestic investors), and retail investors. Foreign Institutional Investors, such as mutual funds and banks, who have the experience and knowledge necessary to make their investment. Non-professional investors are known as retail investors. Machine learning is used to make an accurate prediction with less risk management in the stock market because there is a lot of uncertainty there. Through forecasting and LSTM (Long/Short Term Memory), we can theoretically predict stock prices through the use of machine learning. Effective stock market prediction gives us some suggestions on trading strategies, which is why stock market prediction is so important when it comes to investments. There is, however, no way to guarantee that the data will be 100% accurate because of future uncertainty in the field of study. For stock price prediction, this paper reviews studies on machine learning techniques and algorithms.

Effect of financial literacy and risk aversion on the relationship between self-control and financial security of individual investors in Tehran Stock Exchange

Capital markets play an important role in the economy and naturally, the proper functioning of the capital market will play a key role in ensuring economic growth. So, if capital markets are efficient, economic development will be ensured. On the other hand, since the Iranian stock market is currently very popular among investors, it is undoubtedly important to examine the behavioral biases of individual investors. Therefore, in this study, the effect of positive self-control behavioral bias on financial security was investigated with the moderating role of financial literacy and risk aversion of individual investors. For this purpose, the statistical population consisted of individual investors, traders and brokers of Tehran Stock Exchange who are directly participating in the market. Also, the statistical sample was calculated to be 421 using Cochran’s formula. A structural equation model using PLS method was used to analyze the data. The results showed that the self-control variable has a significant positive effect on risk aversion and financial security. Also, by using the financial literacy variable as a moderating variable, the intensity of the relationship between self-control and financial security of individual investors increases; that is, the financial literacy of individual stock market investors intensifies the positive relationship between self-control and security of their financial behavior. In addition, by using risk aversion as moderating variable, the intensity of the relationship between self-control and financial security of individual investors is reduced. This means that the risk aversion of individual stock market investors reduces the positive relationship between self-control and the security of their financial behavior.

MID cap emerging companies and capital impact in stock market

Mid-cap companies are those with a market value between $2 billion and $10 billion. 1 The market capitalisation of a company is calculated by multiplying shareholders’ equity by the stock price. It is a well-known company with a great deal of potential for growth.ETFs that track midcap companies are another option. Fees for mutual funds are much higher. Because an ETF will never outperform the market, it has a downside. Consequently, they may keep an eye on the market. It's common for new investors to have a hard time deciding which stocks to buy. Even seasoned investors might be overwhelmed by these questions. If you're going to be a successful stock market investor, you need to have a good grasp of the fundamentals. You may suffer losses if you don't know which stocks to invest in. Stocks on the stock market are subject to inherent risk, which can vary greatly from one company to the next.

Statistical Machine Learning Model and Commodity Futures Volatility Information for Financial Stock Market Forecasting

A country's economy and social structure are greatly influenced by the stock market. It is extremely difficult for investors, expert analysts, and scholars in the financial industry to forecast the stock market accurately because of the pretty unstable, parametric, non-linear dynamical, and unstable character of stock price time series. In the financial sector, stock market forecasting is a critical activity and a prominent study subject because stock market investments carry greater risk. It's conceivable, however, to reduce most of the risk through the development of computationally intelligent approaches. This paper introduces the support vector machine regression to make a model forecasting the stock market financial.