The Role of Information in the Analysis of Stock Market Prices: Case of Botswana Stock Exchange

Author(s):  
Onkokame Mothobi ◽  
Keoagile Thaga
2019 ◽  
Vol IV (I) ◽  
pp. 10-18
Author(s):  
Muhammad Arif

The study focused on the moderation role of information asymmetry (IA) that plays a vital role between Stock market liquidity (SML) and Institutional investors (I.I) in textile sector of Pakistan stock exchange (PSX). Among total population of 155 companies, a sample of 150 textile companies is chosen with the help of convenient sampling technique for a period of 10 years (2009-2018). The results of Pre-moderation panel data regression analysis show that there is insignificant effect of I.I on SML while size (SZ), leverage (LEV) and growth (GR) have significant effect on SML. Further, post-moderation effect of IA, which is the uniqueness of the study, indicates a stronger significant effect of SZ, LEV and GR on SML as compare to pre-moderation regression results, which evident that IA do has a significant role between explanatory variables and SML. The results of the study are supporting the signaling theory on the base of moderation of IA that increases the significance level between I.I and SML.


2021 ◽  
Vol 39 (11) ◽  
Author(s):  
Wasan Yahia Ahmed ◽  
Suaad Adnan Noaman Al-Shammari ◽  
Ahmed Taher Kadhim Al-Anbagi

The subject of green accounting is one of the modern topics in accounting science, which has received great attention by researchers and writers because of its great role in measuring and disclosing environmental activities and in line with the interests of internal and external users of accounting information.  The research stems from a fundamental problem that taking into account the costs of green accounting within the financial statements of economic units would improve the quality of accounting information provided to users. To achieve the goal of the research, a questionnaire was designed and submitted to the stakeholders of users of information and employees of a number of economic units listed on the Iraq Stock Exchange, as well as the use of different statistical methods and methods to extract results related to the role of information on green accounting in improving the quality of accounting information provided by Before economic units. The research reached several results, the most important of which was the need to take into account the costs of green accounting and manifested within the financial statements of economic units, because of its role in improving the quality of accounting information and commensurate with the interests of users, so it should work to measure those costs and disclosed to contribute to Meet the wishes and interests of users of financial statements.


2019 ◽  
Vol 1 (1) ◽  
pp. 82-92
Author(s):  
Ardy Indra Lekso Wibowo Putra ◽  
Aditya Dwiansyah Putra ◽  
Murni Sari Dewi ◽  
Denny Oktavina Radianto

An investor must be able to consider all kinds of steps that will be taken or that will be carried out, assessing stocks - shares that will provide optimal benefits in making an investment decision. By analyzing the intrinsic value of the price of a company's stock, investors can assess the fairness of the stock price. The method used to analize intrinsic value is fundamental analysis using the Price Earning Ratio (PER) approach. The samples to be taken in this research are manufacturing companies in Indonesia which are listed on the Indonesia Stock Exchange (IDX) for the period 2016 - 2017 with certain criteria. The results of this research will show that the shares of companies listed are in overvalued, undervalued or correctly valued conditions. So investors can decide to buy, hold or sell their shares.


2019 ◽  
Vol 19 (3) ◽  
pp. 404-418 ◽  
Author(s):  
Ojonugwa Usman ◽  
Umoru Adejo Yakubu

Purpose The purpose of this study is to investigate the role of corporate governance practices on the post-privatization financial performance of the firms listed on the Nigerian Stock Exchange (NSE) over the period 2005-2014. Design/methodology/approach The study uses a two-step dynamic system Generalized Method of Moments (GMM) estimation technique for 27 privatized firms by considering a wide range of controlled variables such as managerial shareholdings, board composition, debt financing and stock market development. Findings The empirical result suggests that the improvement in the firms’ financial performance is attributed to good corporate governance practices through effective board composition, debt financing (leverage) and stock market development. The result further shows no substantial evidence to support that managerial shareholding improves firms’ financial performance. Research limitations/implications Therefore, based on the empirical findings of this study, the authors recommend that the firms need to maintain the optimum board composition and the ratio of debt to share capital as well as developing the stock market to function effectively. Originality/value This study contributes to the existing literature in several ways: (1) the first time that the role of corporate governance is considered in explaining the post-privatization financial performance of firms listed on the Nigerian Stock Exchange; (2) the paper applies a two-step dynamic system GMM estimation technique, proposed by Arellano and Bover (1995) and Blundell and Bond (1998) to control for the serial correlation and heterogeneity, which remain the major weaknesses of the panel data modeling in the literature.


Author(s):  
Mustafa Mohammed Zain, Asim Hassan Mohammed

This research aimed primarily to clarify the extent of the significance of financial analysis tools in the rationalization of investors’ decisions in the Khartoum Stock Exchange. This is, however, will be effected by identifying the role of financial analysis using financial ratios to provide information to make a sound decision. To achieve this objective, the research used the analytical descriptive approach, since the same conforms to such types of researches. To affect this, the research relied basically on the annual financial data of the case study. Based on said account, the research has reached a number of findings, the most significant of which, are the following: The utilization of trend analysis reporting in the Khartoum Stock Exchange has a great significance in the performance evaluation of the stock market. The liquidity ratios as a tool for financial statements analysis deemed as a perfect indicator in the process of decision making in the stock market. The debt ratios are the most significant tools in the financial analysis of the published financial statements, which help investors to take sound investment decisions.


2019 ◽  
Vol 8 (3) ◽  
pp. 1224-1228

Prediction of Stock price is now a day’s an existing and interesting research area in financial and academic sectors to know the scale of economies. There did not exists any significant set of rules to estimate and predict the scale of share in the stock exchange. Many evolutionary technologies are existing such as technical, fundamental, time, statistical and series analysis which help us to attempt the prediction process, but none of the methods are proved as reliable and accurate tool to the society in the estimation of stock exchange or share market scales. Here in this paper we attempted to do innovative work through Machine Learning approach to predict or sense the behaviour tracking of the stock market sensex. Linear regression, Support Vector regression, Decision Tree, Ramdom Forest Regressor and Extra Tree Regressor are the Machine Learning models implemented effectively in predicting the stock prices and define the activity between the exchanges the securities between the buyers and sellers. We predicted the price of the stock based on the closing value and stock price. An algorithm with high accuracy we do the process of comparison for the accuracy of each of the model and finally is considered as better algorithm for predicting stock price. As share market is a vague domain we cannot predict the conditions occur, and also share market can never be predicted, this job can be done easily and technically through this work and the main aim of this paper is to apply algorithms in Machine Learning in predicting the stock prices.


2021 ◽  
Vol 15 (1) ◽  
pp. 41-56
Author(s):  
Catherine Dwiputri ◽  
Vina Christina Nugroho

Purpose of this study is to obtain empirical evidence about the role of liquidity in asset pricing in the Indonesian stock market. This study compares the role of liquidity as a characteristic of stocks and liquidity as a source of systematic risk. This study uses a total of 280 sample companies listed on the Indonesia Stock Exchange during the period 2006 - 2016. In measuring liquidity, this study uses the proportion of zero returns and because liquidity predicts future returns and also moves according to the past. For this reason it is necessary to have innovations to avoid stationarity issues because of the high persistence in liquidity so we use ARMA structure in the portfolio as data analysis method. Data processing was performed using the Fama-Macbeth (1973) model. The results of this study prove that market liquidity has a negative influence on stock returns on the Indonesian market. Thus, the role of liquidity as a systematic risk has an effect on asset pricing on the Indonesian stock market.


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