Share Market Research Articles

BDB: Branding and Developing Business Algorithm Via Corporate Social Responsibility (CSR)

Abstract: In today’s era there are speed economic developments, the corporate Social responsibility has become the main focus. In corporate world marketing through advertisement and Corporate Social Responsibility has become a major factor. Generally, the corporate gains profit via marketing, advertisements, QoS and corporate Social responsibility (CSR). There are more possibilities of raise in corporate share market when they collaborate with government social responsibility. The paper investigates a novel algorithm named as “Branding and developing business (BDB) algorithm via CSR. The proposed system handles both the economy of Government and Corporate mutually. The corporate profit chances tax Benefits and share rate increase are checked continuously. Moreover, when the government subsidizes the corporate and the retailer simultaneously, only the retailer's profit increases in the corporate CSR effort. Further in this paper, the profit perspectives of corporate and Government through CSR are also proposed. Keywords: corporate social responsibility (CSR), BDB, Government, Share Market.

A CONCEPTUAL STUDY ON INDIAN STOCK MARKET'S RESPONSE TO COVID-19 PANDEMIC- A COMPARATIVE STUDY WITH OTHER CRISES

The 2020 pandemic has shattered all most all the activities around the world, resulting to a great depression in the economy. Pandemic has poisoned all economic activities. The pandemic has affected public health in the country. If we make a keen look, every 10 years, there is some crash or scam happening in the country. However, after every crash if we make an analysis, there is a new revolution in the economy. The Harshad Mehta's scam which is one of the major scams in Indian share market history brought remarkable changes in banking sector, the Covid-19 crises has made India to depend immensely on technology which would otherwise not be possible in a country like India. With the spread of Covid virus across the country, the Government, after seeing the medical expert's opinion, announced nationwide lockdown to prevent the spread of the virus across the country. Life of millions of people was shattered as they could not earn their livelihood. Many youth lost their jobs, there was unemployment problem gearing up across the country. Due to the lockdown, the financial markets also reacted to the pandemic and there was lot of volatility in the share market. The present paper aims to examine the impact of Covid-19 on stock market volatility in India. The paper also considers some of the crashes that have happened in the past and to make a comparative study of various crashes with that of the Covid19 crash.

Hyper-Wiener index for fuzzy graph and its application in share market

Topological indices have an important role in molecular chemistry, network theory, spectral graph theory and several physical worlds. Most of the topological indices are defined in a crisp graph. As fuzzy graphs are more generalization of crisp graphs, those indices have more application in fuzzy graphs also. In this article, we introduced the fuzzy hyper-Wiener index (FHWI) and studied this index for various fuzzy graphs like path, cycle, star, etc and provided some interesting bounds of FHWI for that fuzzy graph. A lower bound of FHWI is established for n-vertex connected fuzzy graph depending on strength of a strong edges. A relation between FHWI of a tree and its maximum spanning tree is established and this index is calculated for the saturated cycle. Also, at the end of the article, an application in the share market of this index is presented.

Future Trend Prediction in Share Market with Machine Learning

In Stock Market Prediction, the point is to estimate the future worth of the monetary loads of an organization. The new pattern in securities exchange forecast advances is the utilization of AI which makes expectations dependent on the upsides of current financial exchange lists via preparing on their past qualities. AI itself utilizes various models to make expectation simpler and credible. The thought centers on the utilization of dissimilar Machine learning algorithms to anticipate stock qualities. Variables considered are open, close, low, high and volume. The principal thing we have considered is the dataset of the securities exchange costs from earlier year. The dataset was pre-handled and adjusted for genuine examination. What's more, the proposed thought inspects the utilization of the forecast framework in verifiable settings and issues related with the accuracy of the general qualities given. The thought additionally portrays AI model to foresee the life span of the stock in a serious market. The effective forecast of the stock will be an extraordinary resource for the securities exchange establishments and will give genuine answers for the issues that stock financial backers face.

Data analytics to evaluate the impact of infectious disease on economy: Case study of COVID-19 pandemic

SummarySARS-CoV-2 (COVID-19) is a new strain of coronavirus that is regarded as a respiratory disease and is transmittable among humans. At present, the disease has caused a pandemic, and COVID-19 cases are ballooning out of control. The impact of such turbulent situations can be controlled by tracking the patterns of infected and death cases through accurate prediction and by taking precautions accordingly. We collected worldwide COVID-19 case information and successfully predicted infected victims and possible death cases around the world and in the United States. In addition, we analyzed some leading stock market shares and successfully forecast their trends. We also scrutinized the share market price by proper reasoning and considered the state of affairs of COVID-19, including geographical dispersity. We publicly release our developed dashboard that presents statistical data of COVID-19 cases, shows predicted results, and reveals the impact of COVID-19 on leading companies and different countries' job markets.

A Regression Analysis of Stock Market Prediction Using Machine Learning Algorithms

Securities exchange or Share market is quite possibly the most confounded and modern approach to work together. Little proprietorships, business companies, banking area, all rely upon this very body to make income and gap chances; an extremely muddled model. Nonetheless, this paper proposes to utilize AI calculation to anticipate the future stock cost for trade by utilizing open source libraries and previous calculations to help make this capricious configuration of business somewhat more unsurprising. We will perceive how this basic execution will bring adequate outcomes. The result is totally founded on numbers and expects plenty of adages that might possibly continue in reality so as the hour of expectation.

Does Ramzan Effect the Returns and Volatility? Evidence from GCC Share Market

Does Ramzan Effect the Returns and Volatility? Evidence from GCC Share Market

Forecast Share Price Using Technical analysis Tool

In recent years many of us have been interesting in investing in the share market. This study focuses on the prediction of share price using a technical analysis tool (candlestick chart). In this study we use 30 companies' one-year data of share prices, top companies of the individual sector in NSE (National Stock Exchange) to forecast the share prices. The sample charts are taken from moneycontrol.com. In this study, we predict the share price using the previous price changes in the share market. Compare them with an actual price, find how many decisions are correct, how many decisions are wrong.

Impact of Demographic Variables on Investment Awareness Level Among People in Himachal Pradesh

Household saving and investment are some of the major factors for supplying capital in the economy. As investment habits of households depend upon their awareness about different available investment avenues, it is necessary to know their awareness level. The present study is an attempt to analyse the awareness level of people in Himachal Pradesh about various investment avenues on the basis of their demographic profile. The research was conducted by using a structured questionnaire from 540 sample respondents on the basis of multi stage sampling. The collected data was analysed with the help of different statistical tools like, mean, standard deviation, skewness, and chi square. The findings of the study reveal thatpeople are highly aware about Bank Deposit schemes followed by Life Insurance Schemes, Post Office Saving Schemes, Provident Funds and Gold & Jewellery whereas, very less people are aware about Derivatives, Share Market and Mutual Funds.

Share Market Response to the Announcement of Dividend Payment Plan in the Food and Beverage Sector Registered in Indonesia Stock Exchange

The purpose of this study is to determine investors' reactions to the announcement of the 2017-2019 dividend payment plan in the food and beverage sector listed on the Indonesia Stock Exchange. This type of survey is an empirical survey using the event survey method which aims to investigate the market reaction to events whose information is published as announcements. The data used in this study is secondary data, namely data taken from other data sources, not collected by the researcher himself. Data obtained from the Indonesia Stock Exchange Corner. The data analysis method is to calculate the actual daily stock return for each stock during the event and use the expected model to estimate the expected return. When we tested the comparison of the average rate of return (AAR) of stocks during the pre-announcement period, the average rate of return was -0.065813, but seven days after the announcement, the average rate of return was -0.000720. We tested the difference between 15 days before the announcement and 15 days after the announcement and found that the t-value was 2.996 and the significance was 0.001.

The Mediating Effect of E - Satisfaction on E - Service Quality and E - Loyalty Link in Securities Brokerage Industry

The rising popularity and use of the internet - based e in India offers huge potential in the internet connected (e-commerce) market and economy, and in specific for the stock brokerage category, leading to improved electronic service quality (e-SQ), electronic satisfaction (e-Satisfaction), and electronic loyalty (e-Loyalty) and becomes powerful components for investment bankers and stock brokers to attract and keep traders in the online market. To cope and handle with advances in Technology (ICT) and the varying expectations and demands of stock traders, the relationship between e-SQ, e-Satisfaction, and e-Loyalty should be continuously reviewed. Nonetheless, the design of e-SQ for retailers in any industry remains an open question. In this study, E-SERVQUAL was combined with several other e-SQ scales to assess the e-SQ of major share brokers in India. The e-SQ frameworks in particular are Design, Functionality, Privacy, Reliability, and Recovery. An online questionnaire is used in the research and the sampling method used was convenience sampling. From the distributed questionnaire, 50 sets of finished and productive responses were returned by the traders and investors. The findings suggested that the five proposed dimensions of e-SQ for stock brokers in the share market be developed. Every aspect of e-SQ was observed to have significant positive and notable effect on stock dealers' e-satisfaction. The responsiveness of e-SQ had the greatest impact on online shoppers' e-satisfaction. The customer's e-Loyalty to use an online retailer's website on a regular basis was significantly influenced by their e-Satisfaction. The study's findings serve as the foundation for discussion on managerial and theoretical implication.

Major reasons behind the whitewash of lakshmi vilas bank from the indian stock market – an analysis with mathematical approach

Banks play a pivotal role in India's economic development. They sustain the country’s GDP growth through turning people’s static money into capital for investment and thus directing cash flow via dynamic market systems. Bank deposits provide secured and fixed return unlike the share market that holds higher risk of investment and offer a variable return which is uncertain. Whenever an individual or a company is at financial crisis, Banks lend their hands and offer loans and help them as much as possible to cut down the financial burden. But on the other hand, when the financial health of a bank itself is very weak which in turn will certainly affect the entire movement of the banking sector in the stock market and further that would lead to unreliable market circumstances. In this paper, we will be analyzing the major reasons behind the complete wash out of Lakshmi Vilas Bank from the Indian Stock Market and try to figure out the alarming indicators so as to be more cautious in the mere future to avoid such financial breakdown caused due to the bankrupted scenario.

A Study on Profitability Position of Ports and Special Economic Zone Limited

Profitability Ratio Analysis plays a vital role in corporate world, as it helps the investors to compute the returns earned out of the investments. Profitability Ratio Analysis is necessary for Adani Ports and Special Economic Zone Limited, as they are expanding their business throughout India and the shares of Adani Group also traded at highest cost in the share market. The Paper computes the Profitability Ratios Analysis on the data of Adani Ports and Special Economic Zone Limited which is sufficient to compare the return with its investment. The Data of Adani Ports and Special Economic Zone Limited was collected for past five years from its secondary source and analysed. The Study helps to analyse the Profitability of the company and compare its return out of its performance with its previous years. It analyses the overall performance of the company which resulted in less profitability. Hence, we suggest to increase its revenue by expanding its business operation and by taking up new-revenue generating projects through diversification.

Share Market Prediction by using ML

Share Market Prediction by using ML

Assessment of Control Drive Technologies for Induction Motor: Industrial Application to Electric Vehicle

Nowadays electric vehicle has increasingly gained much popularity indicated by growing global share market targeted at 30% by 2030 after recording 7.2million global stock in 2019. Compared to Internal Combustion Engine (ICE) counterpart, Battery Electric Vehicles (BEV) produce zero tailpipe emission which greatly reducing carbon footprints. Induction motor has been widely used and its control technology has evolved from scalar type volt/hertz to recent predictive control technology. This allows induction motor’s application to expand from being the workhorse of industry to become prime mover in electric vehicle, where high performance is expected. Among vector control scheme, Direct Torque Control (DTC) has gained interest over Field Oriented Control (FOC) with simpler structure, better robustness and dynamics performance yet suffer from high torque and flux ripple. In electric vehicle applications, high ripple at low speed is highly undesirable, potentially causing torsional vibration. High performance control requires speed sensor integration, which often increase complexity in the design. The work aims to review the best control technology for induction motor in electric vehicle application through performance parameter evaluation such as improvement on dynamic response, torque and flux ripple reduction, and component optimization. Several arise issues in motor control and possible methods to circumvent are highlighted in this work. In conclusion, model predictive torque control (MPTC) is the most promising scheme for electric vehicle with excellent dynamic response, good low speed performance, and 50% torque ripple reduction compared to conventional DTC and potential integration with sliding mode observer for sensorless solution.

Online Trading Effectiveness in Nepal Share Market: Investors Awareness, Challenges and Managerial Solution

Over a long time, the developing businesses have a brief history of victory all due to web. The online exchange forms of back comprehensive of buying and offering of bonds, stocks and other ventures, these all comes beneath online exchanging. Even though the world has already adopted the online trading, in Nepal it was recently introduced. This paper aims to explore online trading effectiveness in Nepal Share Market. Explanatory research design is applied in this study. Both primary and secondary sources are used for collecting various data and information in the study. Quantitative technique is used for data analysis. Most of the respondents responded that they are involved and fully aware of the online trading. Majority of respondent agreed that they use both fundamental analysis as well as technical analysis for online trading. Similarly, most of the respondents expressed their opinion that technological factor caused problem on online trading.

Comparative Study of Stock Value Prediction

The stock market is a very robust business model, that is nonlinear in nature, it is also generally referred to as the share market. Investors prefers to use some forecasting methods or techniques, to invest in the share market, maximizing the benefit, and minimizing the risks involved with it. In this paper, we have used the linear regression model to forecast future stock prices. Experiments are conducted on common stocks such as AMAZON and ZUMIEZ, which shows that our model achieves a very high degree of reliability and makes this volatile type of company a little more predictable. 96.54% and 98.12% respectively are the reliability calculated on AMAZON and ZUMIEZ stocks.

Human Capital Reporting (HCR) and Shareholder Value Maximization in Listed Manufacturing Firms in Nigeria

This study examines the impact of human resource reporting (HCR) or disclosures on share price and earnings potential measured by the earnings per share. It adopts an ex-post causal research design and employs secondary data retrieved from annual reports of 30 selected manufacturing firms in Nigeria. Data was analyzed using descriptive statistics, correlation analysis and the quantile regression techniques. The research outcome from the distributional dynamics for share price tends to highlight that the effect of HRD-Index is significant at 5% for firms at high levels above average financial performance at Q[0.2.] - Q[0.4] and also significant at 5% for firms at average levels of firm value Q[0.5] and even below average levels Q[0.6]-Q[0.9]. Finding thus highlights that the impact of human resource disclosures on share price or market value may not necessarily be a function of the share price levels. The distributional dynamics for EPS used as the measure for earnings potential is similar to that which was observed for Share price and tends to highlight that the effect of human resource disclosure is significant at 5% for firms at high levels above average earnings per share measure of financial performance at Q[0.1], Q[0.2.], Q[0.3.] and Q[0.4.] and also significant at 5% for firms at average levels of financial performance Q[0.5] and even below average levels Q[0.6]-Q[0.8]. The recommendation is that human resource investments should not been looked at as an expense but as a competitive strategy of the firm.

Do Market and Herding Effect Really Impact on Investment Decision Making in the Indian Share Market?

“Mad March – 2020, witnessed dramatic down-slide in the world’s top stock exchanges due to COVID-19 pandemic with worrying volatility which resulted in traders panic sold off their holdings out of fear”.2020’s first quarter witnessed substantial losses in the several well-recognized stock indices, especially between March 6 to 18, more than 20% that were triggered downward by the outbreak of COVID-19. Dow Jones Industrial Average and S&P 500 experienced the worst first quarter ever in the history during the year 2020 reducing its value by 23.2%. The year 2020 witnessed several historical landmark changes in the Indian share market movements along with other prominent stock exchanges of the globe. On March 23rd, 2020, Benchmark index SENSEX touched intraday lowest value of 25880 and NIFTY fell to the lowest value of 7583. Throughout the globe, including Indian investors, started to rush for clearing their holdings ahead of dark lines created by the pandemic in spite of most of the financial analysts’ suggestion for fresh buy and/or to hold previous purchase for long. Supporting financial experts’ views, within the next nine months SENSEX has gained around 100% and stood at 48834.34 on 8th Jan 2021.
 There are many studies both in India and outside the country that have provided evidence for the role of behavioral factors on investment decision-making at respective stock markets. Here authors attempted to verify, ‘weather market factor and herding effect of behavioral variables do influences on investment decision making of Indian share market investors?’

Are Corporate Dividend Policy, Earnings per Share and Share Price Affect Tax Aggressiveness Using Interest Coverage as an Intermediary Variable?

The purpose of this research is to investigate the interaction and the nature of relation between corporate dividend policy, earnings per share and the market price of the stock and planning of the corporate toward tax aggressiveness using interest coverage ratio as an intermediary variable. Ordinary least square regression model has been applied on panel data, it has been used to examine the required impact and to see how tax aggressiveness is significantly - and in what direction - affected by the management decision (agency theory) toward dividends payout and how the earnings per share and stock market price affect the tax planning in Egypt using a sample of 48 non-financial listed companies for the period of 2012-2019. This research runs three multiple regression models to examine the relationships between research variables. In cross-sectional tests, the statistical results indicate that earnings per share have a positive significant impact on interest coverage, while dividend payout, return on assets, return on equity and gross profit margin have a significant negative relationship with interest coverage. The findings revealed that also that dividend payout; earnings per share, return on assets and gross profit margin have a positive significant impact on tax aggressiveness, while stock market price and return on equity have a significant negative relationship with tax aggressiveness. Furthermore, it was found that return on assets and gross profit margin have a positive significant impact on tax aggressiveness, while interest coverage and return on equity have a significant negative relationship with tax aggressiveness. These results are important for investors who are most concern about the financial conditions of firms they are planning to invest in especially in emerging markets like Egypt. Firm’s financial conditions determine the associated risks and, in turn the required rate of returns in terms of dividends payout and the share market price.