Stock Exchange Market Research Articles

Effect of Dividend Policy on Share Price Movement: Focusing on Companies Listed on the Nigerian Stock Exchange Market

This study examined the relationship between dividend policy and share price movements with evidence from firms listed on the Nigerian Stock Exchange. A systemization literary approach for data analysis was panel regression analysis and Generalized Methods of Moments (GMM). Panel data covering the year 2011-2020 were obtained from the financial statements of twenty firms listed on the Nigerian stock exchange. It was discovered that dividend yield has negative relationship with share price movement. It was discovered that Dividend yield has negative and significant relationship with Share price. It was revealed thatfirms’ size has positive and significant relationship with stock price volatility. The study therefore recommends that the stakeholders of quoted firms must make sure that percentage of earnings disbursed as dividends to shareholders have good influence on the value of the company’s common stock at the stock market on a continuous base. It was recommended that Stake holders should ensure that the ratio of a quoted company’s annual dividend compared to its share price have good influence on the value of the company’s common stock at the stock market on a frequent base. Also, the stake holders of quoted firms must map out strategies of increasing their sizes in terms of asset, branch creation etc., this will increase patronage and profit of quoted firms which can have good influence on the value of the company’s common stock at the stock market.

Long-Term General Index Prediction Based on Feature Selection and Search Methods: Amman Stock Exchange Market

Stock markets are an essential backbone for the economy worldwide; their indices provide all interested parties with indicators regarding the performance of firms listed in the financial market due to tracking the daily transactions. This study aims to investigate factors that affect the stock exchange directly so that it simplifies building a prediction model for the exchange index in Jordan’s financial market. The study hypothesis assumes that some sub-sectors are most influential in creating the stock market prediction model. Therefore, this study applies four feature selection methods on 23 sub-sectors and Amman Stock Exchange Index (ASEI100) for the period 2008–2018. The top 10 attributes from each selection method are combined, and the frequency table is used to find the highly trusted attributes. Moreover, linear regression with ordinary least square regression is used to test the validity of the top factors that frequently occurred in the four methods and their effect on ASEI. The results found that there are six main sub-sectors directly affecting the general index in Jordan: Health Care Services, Mining and Extraction Industries, Textiles, Leather and Clothing, Real Estate, Financial Services and Transportation. These sectors can be utilised to predict the movements of the Amman Stock Exchange Index in Jordan. Also, the linear regression model output showed a statistically significant relationship between the six sub-sectors (independent variables) and ASEI (dependent variable). Investors can use this paper’s findings to signal the most important sectors in Jordan. Thus, it helps in taking investment decisions.

Determinants of dividend policy in Palestinian banks

This study aims to examine whether the dividend theories that were principally developed for non-financial companies in developed institutional environments can explain the dividend policies of banks in Palestine, an emerging market with a high level of uncertainty. It also aims to determine the main factors affecting the banks’ propensity to pay dividends and the banks’ dividend payout ratios. The study uses pooled Probit and ordinary least squares regressions to analyze 10 years of data from all listed banks in the Palestine Stock Exchange Market. The results indicate that agency cost, signaling, and regulatory pressure theories are valid for Palestinian banks. In addition, the analysis shows that bank size, profitability, and capital adequacy are the main positive determinants of Palestinian banks’ propensity to pay dividends and of the dividend payout ratios. Furthermore, after winsorizing the data, the results were found to remain consistent. Finally, the results of a general dominance analysis revealed that bank size is the most important determinant, followed by bank profitability and bank capital adequacy, all three of which positively influence dividend policy decisions in Palestinian banks. This study is among the first to investigate dividend policy determinants in the financial sector. Moreover, this study is conducted in Palestine, an emerging economy. Furthermore, unlike prior studies, this study considers banks’ propensity to pay dividends and banks’ dividend payout ratios concurrently when analyzing the dividend determinants in order to make a significant contribution to solving the dividend determinant puzzle.

Investigating the effect of US dollar, gold and oil prices on the stock market

The capital market, as one of the main components of the financial markets, plays an important role in the economic development of countries. As financial markets become more globalized through the free flow of capital and international trade, price fluctuations in financial assets also affect other assets and markets. Due to the high impact of foreign exchange, gold, and oil markets on other financial markets, this study examined the impact of these markets on the Tehran Stock Exchange market from April 2015 to March 2021. In this regard, US dollar, ounces of gold, and crude oil are used as independent variables, and Tehran Price Index (TEPIX) is considered as a dependent variable. The results of the final model indicate that the prices of dollars, gold, and oil had significant effects on the total price index of the Tehran Stock Exchange.

The COVID-19 pandemic and the performance of the stock exchange market: Evidence from the Bahrain Stock Exchange indexes

Numerous studies confirmed that COVID-19 still has a negative impact on financial market performance worldwide, which inversely affected investors’ perceptions and decisions by creating uncertainty and a risky investment environment (Bagão, Dias, Heliodoro, & Alexandre, 2020). Therefore, the current study tries to assess the influence of the COVID-19 pandemic on Bahrain Stock Exchange indexes during the pandemic peak period in 2021. The effect of the COVID-19 pandemic on the Bahrain Stock Exchange is analysed using the autoregressive distributed lags (ARDL) approach. Daily observations from January 1, 2021, to September 30, 2021, in Bahrain, encompassing the pandemic peak period. COVID-19 pandemic used to represent independent variables by new daily cases (positive), death cases and recovered patient cases. Meanwhile, the study utilized the Bahrain Stock Exchange for the dependent variables, including both Bahrain all-share index (BASI) and the Bahrain Islamic index (BII). The findings showed a negative and negligible association between BASI, BII, and COVID-19. The study found that both indexes and daily retrieved cases exhibit a favorable correlation during the research period. Additionally, the analysis concluded that both indexes are roughly moving in the same way in reaction to the present epidemic

The main drivers of investment decision in the Malaysian stock exchange market: A PLS-SEM Based Approach

The main drivers of investment decision in the Malaysian stock exchange market: A PLS-SEM Based Approach

CEO Power, Corporate Risk-Taking, and the Role of Institutional Owners: Pieces of Evidence of Tehran Stock Exchange Market and Iran Fara Bourse

"Corporate governance" includes mechanisms to monitor CEO's performance to assure efficient decision adoption and maximize firm value. One of the most effective aspects of firm performance is the degree of risk-taking. This study investigates the relationship between CEO power and institutional ownership with risk-taking behavior of member firms of Tehran Stock Exchange and Iran Fara Bourse during 2010-2019 by utilizing quintile regression. According to the results, by the increase of CEO's power and the company's benefit from powerful managers, the company risk (total risk and systemic risk) will decrease. As a result, managers are eager to safeguard their reputation as expert decision-makers and, as a result, they try to reduce company risk. In addition, the existence of institutional ownership among the shareholders of the company will reduce the risk, which can be referred to in the agency theory. Also, if the impact of these two variables is considered together, the risk will increase significantly. This very fact reflects the exercise of the power and influence of institutional owners. As a result, large shareholders have a supervisory role in the discipline of managers, but despite their impact on the relationship between managers' power and corporate risk, they do not alter the main negative relationship.

ASSESSMENT OF THE QUALITY OF THE STATISTICAL FORECAST FOR THE SHARE PRICE

The stock market is an important part of the world's economy, but the values of stocks change at a significant speed and finding an effective method of forecasting the price of stocks will be a significant victory for investors. The article is devoted to the use of statistical methods in the stock market, evaluating their effectiveness on the example of determining the forecast share price and comparing it with the real share price. In addition, work was carried out to determine the relevance of the research topic by means of bibliographic analysis based on the results of searching a selection of publications in the Scopus database with the subsequent use of the VOSviewer software toolkit. A time series covering the period of daily values of stock prices of Apple Inc. was chosen as the input test sample for developing the forecast. from December 12, 2016 to December 12, 2021. At the same time, the median values of the prices of the monthly financial shares of the Apple com corporation were used to build forecast models, since there is no information that fell on weekends for the studied time period. Forecasts are published using Statgraphics 19 software, which generates 17 forecast models: random walk, random walk with drift, constant mean, linear trend, quadratic trend, exponential trend, S-shaped trend, simple moving average, simple exponential smoothing with a smoothing coefficient α = 0.9999, linear exponential Brownian smoothing with smoothing factor α= 0.5705, linear exponential Holt smoothing with smoothing coefficients α = 0.9999 and β = 0.0359, quadratic exponential Brownian smoothing with smoothing coefficients α = 0.3046, ARIMA model. Akaike's information criterion was used to assess the quality of the models. As a result of the analysis, the ARIMA(1,0,0) model has the lowest value according to Akaike's criteria. On the basis of ARIMA(1,0,0), a forecast of stock market exchange rates was built 6 months ahead of the age of the final value of the input array. In the process of comparison with real data, a significant discrepancy between the forecasting results and the real share price in the forecasted period was found, however, the obtained models were tested for statistical significance. The conducted research showed that it is possible to use classical statistical methods to develop a forecast on the stock market only for a short-term period, while it is necessary to take into account the risk factors inherent in the stock market (the frequency of share price changes during the day, liquidity risks, operational risks, political situation in the world).

Financial Market Prediction and Simulation Based on the FEPA Model

Since the birth of the financial market, the industry and academia want to find a method to accurately predict the future trend of the financial market. The ultimate goal of this paper is to build a mathematical model that can effectively predict the short-term trend of the financial time series. This paper presents a new combined forecasting model: its name is Financial Time Series-Empirical Mode Decomposition-Principal Component Analysis-Artificial Neural Network (FEPA) model. This model is mainly composed of three components, which are based on financial time series special empirical mode decomposition (FTA-EMD), principal component analysis (PCA), and artificial neural network. This model is mainly used to model and predict the complex financial time series. At the same time, the model also predicts the stock market index and exchange rate and studies the hot fields of the financial market. The results show that the empirical mode decomposition back propagation neural network (EMD-BPNN) model has better prediction effect than the autoregressive comprehensive moving average model (ARIMA), which is mainly reflected in the accuracy of prediction. This shows that the prediction method of decomposing and recombining nonlinear and nonstationary financial time series can effectively improve the prediction accuracy. When predicting the closing price of Australian stock index, the hit rate (DS) of the FEPA model decomposition method is 72.22%, 10.86% higher than the EMD-BPNN model and 3.23% higher than the EMD-LPP-BPNN model. When the FEPA model predicts the Australian stock index, the hit rate is improved to a certain extent, and the effect is better than other models.

The Reasoning of a Responsible Investment Position in the Structure of the Stock Exchange Market

Purpose: To substantiate the place and role of the responsible investment in the structure of the stock exchange market.
 Methods: Structure-functional in order to form an idea of the structure of the stock exchange market, determining the place and role of responsible investment elements in the stock market organization; systematic analysis to identify current trends and patterns in the functioning of the socially responsible investment segment by geographical regions of the world; statistical and graphical methods for quantitative and visual presentation of the results of the stock market sectors analysis, represented by responsible investment elements.
 Findings: The definition of «responsible investment» and «stock market» has been clarified; a number of subjects, objects and forms of responsible investment, which are elements of the stock market, are singled out and substantiated; the generalization of activities of stock exchanges in the field of responsible investing is carried out; the dynamics of stock market sector indicators, which are represented by elements of responsible investment, are analyzed; key reporting standards used by stock exchanges in disclosing ESG issues are analyzed.
 Theoretical Implications: A comprehensive assessment of the functioning of socially responsible investment segment as part of the stock market is carried out, the place and role of responsible investing in the stock market structure are substantiated, which creates a basis for the development of effective measures to increase the stock market efficiency of Ukraine and its transformation into an effective and stable source of investment resources.
 Future Research: The results can be used in the context of further study of the stock market transformation in Ukraine on the basis of a socially responsible trajectory and fractal analysis.
 Paper Type: Theoretical.
 
 The study was performed within the state budget research «Fractal model of the stock market transformation in Ukraine: socially responsible investment to achieve the Sustainable Development Goals» № 0121U100473.

Effectiveness of CAPM Model for Funds Based on Margin Trading in Chinese Market under the COVID-19 Pandemic

The applicability of CAPM model in China was studied under the situation that the global economy was greatly affected. The results show that the stock exchange market in China is less affected by the epidemic. Still in China's securities market, the linear impact of systematic risk on the return on assets is not significant, while the non-systematic risk has a relatively significant linear impact on the return on assets. The CAPM model is not fully applicable in China's securities market. Except that the financial market in China is not sound enough, the reason for the inapplicability of the model would be the drawbacks of the model itself as the model is too sophisticated in its assumptions and there are many factors not considered, and the research direction of improving the model are summarised as pay attention to 6 types of asset pricing anomalies represented by value anomalies, and provide explanations for the causes of these pricing anomalies.

FOREIGN PORTFOLIO INVESTMENT AND CAPITAL MARKET DEVELOPMENT IN NIGERIA

The poor performance of Nigeria’s stock market is a source of concern and has generated contentious debates among the stakeholders in the Nigerian Stock Exchange Market (NSE). This study investigates the impact of foreign portfolio investment on the performance of the stock market in Nigeria for the period of 30years (1989-2018). Secondary and time-series data were used and the variables such as; stock market capitalization proxy for capital market performance, portfolio investment, exchange rate and inflation rate were sourced from the Central Bank of Nigeria (CBN) statistical bulletin, 2019 To avoid spurious results, unit-root test and regression analysis were used as the tools of data analysis. Findings show that all the predictors have no significant impact on stock market capitalization except the exchange rate that is statistically significant at 5% critical value. However, the f-statistic results (18.83660) indicate that the combine variables have a significant impact on stock market performance in Nigeria. It was therefore concluded that foreign portfolio investment if properly encouraged serve as a Potent variaable for enhancing the performance of the stock market in Nigeria. The study recommends that, there is a need for the government through the central bank of Nigeria to implement a policies that will increase the level and size of market capitalization in the capital market. Such an increase in the capital market will provide the necessary funds for investors for further investments thereby increasing productivity in Nigeria.

The Impact of Board Characteristics on Information Disclosure of Vietnamese Enterprises

The study investigates the impact of board characteristics on listed companies' information disclosure level in Vietnam. The data is collected from the audited financial statements and annual reports of 648 listed companies on HOSE and HNX. Based on the suggested items of Standard and Poor's and the Vietnamese stock exchange market context, the information disclosure index is calculated, which is used for measuring the level of information disclosure of the listed companies. The findings show that the information disclosure level is strongly influenced by board characteristics, namely the positive effect of the board size, state ownership, and duality role, and negative effect of non-executive directors. Additionally, we also find the positive effect of the quality of financial statements and the marketplace on information disclosure. Besides that, we find evidence that the relationship between information disclosure and board characteristics is also significant influenced by firm size, firm profitability, and firm leverage.

Corporate Governance on Environmental Protection Index of Sustainability Reporting in Oil and Gas Companies Quoted in Nigeria

Adequate sustainability of environmental reporting reveals the extent of transparency and corporate efforts in protecting the environment. The study investigated the effect of corporate governance on environmental protection index of sustainability reporting in oil and gas companies quoted in Nigeria. The research design adopted was expost-facto. The population of the study is the entire 12 oil and gas companies listed in the Nigerian stock exchange market from which 8 companies were selected using judgmental sampling technique. The data analyzed were obtained from the financial statement of the selected companies for the period of 15 years ranging from 2006 to 2020. Environmental disclosure checklist in line with Global Reporting Initiatives was adopted to measure the proxies of environmental protection index of sustainability. Multiple regression was used in analyzing the data.it was revealed that corporate governance had significant effect on environmental protection, (AdjR2 = 0.123; Walt-test = 39.29; P-value = 0.000). Also, Firm size and firm leverage significantly moderated the effect of corporate governance on environmental protection, (AdjR2 = 0.216; F-Statistics = 34.58; P-value = 0.000). the study concluded that corporate governance significantly impact on environmental protection and also that firm size and firm leverage moderated the effect of corporate governance on environmental protection, it was recommended that the management should ensure strong commitments and adequate disclosure of all environmental protection policies, and set full compliance as priority; also that government should provide an enabling business operating environment which will enhance effective environmental sustainability reporting.

What Factors Affect Stocks’ Abnormal Return during the COVID-19 Pandemic: Data from the Indonesia Stock Exchange

This study identifies Indonesian investors’ reactions to the drop in stock prices on the Indonesia Stock Exchange market, during the early months of the COVID-19 crisis, before and after the World Health Organization (WHO) announced that its global spread constitutes a pandemic. It also explores variables that influence stock returns on this market during the financial crisis caused by the COVID-19 pandemic. This study uses a regression analysis of 70 firms, listed on the Indonesia Stock Exchange to examine the pandemic’s influence on trading volume, market capitalization, profitability, and book value for the period December 31, 2019, to April 30, 2020. The results show that stock returns were lower in the early period of the financial crisis caused by the pandemic. Firms’ trading volumes, profitability and book values positively affected stock returns and their market capitalization negatively affected stock returns during the study period. This study contributes useful insights to the finance literature and stock-market participants in terms of dealing with stock markets during financial crises. This study recommends that in any crisis investors should begin buying stocks or increasing their stock purchases to achieve abnormal returns by choosing stocks that perform well in terms of firm profitability and book value by looking a number of financial factors.

Machine Learning Model Approaches for Price Prediction in Coffee Market using Linear Regression, XGB, and LSTM Techniques

Investors and other business persons have a desire to know about the future market price because, if the investors know about the future price of a certain commodity or stock it will help them to make appropriate business decisions and they can also get profit out of their investment. There are many previous researches that has been done on stock market predictions but there is no related research that has been done on Ethiopia commodity exchange (ECX). Performing future price prediction with better accuracy and performing comparative analysis between the algorithms for two of Ethiopia commodity exchange (ECX) items which are Coffee and Sesame as the research key objectives. Three different types of prediction algorithms to predict the future price, such as Linear Regression (LR), Extreme Gradient Boosting (XGB), Long Short-Term Memory (LSTM) was utilized. There are limited researches worked on price prediction of ECX items specifically, the idea of the price prediction on different Stock markets like New York stock market Exchange and other commodity market items prediction in order to develop our research in ECX was presented. The study apart from predicting the future price, comparative analysis was implemented between the prediction algorithms that we used based on their performance. Two different datasets from ECX: coffee and sesame were used. The reason for the utilization of these datasets is, the commodity items are the largest export items in Ethiopia which makes them very important for Ethiopian economy, and the different datasets helps us to get the advantage of evaluating the algorithms with different number of datasets, since sesame dataset has 7205 instances and coffee dataset has 1540 instances and both of them has 11 attributes. We build an android application in order two implement our algorithms on mobile applications and see if it is possible to implement the prediction algorithms on mobile platforms and make it easy and accessible to users. We call this mobile application Ethiopia Coffee Prices Predictor (ECPP). This application will be used to display the prediction result of Ethiopia Coffee price for short period and it is designed in the way to be user friendly. The programming environment used to implement the prediction algorithms is python, java programming language to design our android application and we used PHP to implement the API, and finally we used MySQL database in order to store information’s online and make them accessible everywhere.

Portfolio Diversification and Capital Accumulation of Rwanda Stock Exchange of Listed Financial Companies: A Case of Selected Financial Companies Listed on Rwanda Stock Exchange

The fluctuation in stock markets disturbs the genuine investors and they build the mind of that it is not there for the new investors to be more creative due to price fluctuation. Despite the encouragement of investors in Rwanda, the problem existing is that the capital market is no longer growing at the pace expected and there are still few listed financial institutions in stock exchange and this slow the capital accumulation of stock exchange among listed financial institutions. The purpose of this study was to assess effects of Portfolio diversification on capital accumulation of Rwanda stock exchange of listed financial companies and to assess the role of market efficiency on capital accumulation of Rwanda stock exchange of listed companies. The study used three theories such as Model portfolio theory, risk aversion theory and Markowtz portfolio theory. The study used a descriptive research design with two mixed methods such as qualitative and quantitative. A descriptive statistic such as mean, standard deviation was determined while inferential statistics such as regression analysis and correlation analysis established. Therefore, data were analyzed through SPSS version 21 and the presentation was done using frequency tables, pie charts and bar charts. Research findings showed that the relationship between the study variables is significant with p-value 0.000 < 0.05). Therefore, the p-value for portfolio diversification is 0. 025. All these components are statistical significant since p=values <0.05. Based on the problems arising at capital market in that the capital invested in stock exchange market is raised on market situation and in fact that an increase in capital in almost firms do not stimulate enough capital accumulation for listed financial companies, researcher advice the management of I&M Bank Rwanda and Bank of Kigali to apply capital price model to achieve capital accumulation in Rwanda stock exchange operations. There is need to implement strategies regulating and encouraging investment decision in stock exchange operations Keywords: Portfolio Diversification, Capital Accumulation, Stock Exchange Listed Financial Companies

Moderating Effect of Financial Constraint on Relationship Between Accounting Conservatism and Investment Efficiency of Nigerian Consumer Goods Firms

This study explores the moderating effect of financial constraint on relationship between Accounting conservatism and investment efficiency of consumer goods firms listed on the Nigerian Stock Exchange market. The study used correlational and ex-post facto research design in a sample of 27 consumer goods firms. Secondary data for a period of 10 years (2010-2019) was used, and Advanced panel multiple regression was employed in data analysis. The results obtained from this research indicate that there is a significant relationship between accounting conservatism and investment efficiency. The study also found that there is a significant moderation effect between accounting conservatism and financial constraint on defining investment efficiency of consumer goods firms in Nigeria. The study concludes by showing that financial constraint has antagonistic role to accounting conservatism on explaining investment efficiency thus, conservatism may not improve investment efficiency in firms facing financial constraints. The study suggests that consideration of firms financial conditions should form an essential part of any analysis towards understanding the impact of Accounting conservatism more especially on investment behaviour, because of the influence financial constraint has on accounting conservatism is antagonistic in nature

Money Supply and Stock Prices – A Case Study of Nigeria

This study examined the relationship between money supply and stock prices, using E-view version 10. The empirical results of the Augmented Dickey Fuller (ADF) unit root test at 5 percent critical levels indicates that all the variables (M2 and MCAP) were not stationary at levels. However, all the variables became stationary after first differencing. Hence, the variables are of the same order of integration I (1). A cointegration test tells us that there exists a long run relationship between or among the variables and that they will not wander far apart away even though on the short run they exhibit random walk behavior. The Vector Error Correction test shows that Money supply (M2) has a significant relationship with market capitalization of the Nigerian stock exchange. The value of the Adjusted R-Squared of 0.726710 implies that Money supply (M2) explained about 72.67% systematic variations in the dependent variable (MCAP) over the observed years while the remaining 27.33% variations are explained by other determining variables outside the model. In order to further establish the relationship between money supply and stock market price, a granger causality test was carried out and it was established that there is a bi-directional causality between money supply and stock prices. The researcher therefore recommends that there should be collaboration among agencies of government in charge of money supply and stock exchange in order to make sure that sound policies are made to achieve the objective of government. Furthermore, that there should be a deliberate and concerted policy and effort to improve the Nigerian stock exchange market in line with other stock exchanges of the world, since stock prices cause money supply and vice versa.

Identification of the Most Critical Factors in Bankruptcy Prediction and Credit Classification of Companies

Banks and financial institutions strive to develop and improve their credit risk evaluation methods to reduce financial loss resulting from borrowers' financial default. Although in previous studies, many variables obtained from financial statements - such as financial ratios - have been used as the input to the bankruptcy prediction process, seldom a machine learning method based on computing intelligence has been applied to select the most critical of them. In this research, the data from companies that are were listed in Tehran's Stock Exchange and OTC market during 26 years since 1992 to 2017 has been investigated, with 218 companies selected as the study sample. The ant colony optimization algorithm with k-nearest neighbor has been used to feature the selection and classification of the companies. In this study, the problem of the imbalanced dataset has been solved with the under-sampling technique. The results have shown that variables such as EBIT to total sales, equity ratio, current ratio, cash ratio, and debt ratio are the most effective factors in predicting the health status of companies. The accuracy of final research model is estimated that the bankruptcy prediction ranges between 75.5% to 78.7% for the training and testing sample.