Search results for: Dhaka stock exchange

Authors: Yaojun Wang, Yaoqing Wang

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Stock selection is an important decision-making problem. Many machine learning and data mining technologies are employed to build automatic stock-selection system. A profitable stock-selection system should consider the stock’s investment value and the market timing. In this paper, we present a hybrid system including both engage for stock selection. This system uses a case-based reasoning (CBR) model to execute the stock classification, uses a decision-tree model to help with market timing and stock selection. The experiments show that the performance of this hybrid system is better than that of other techniques regarding to the classification accuracy, the average return and the Sharpe ratio.

Keywords: case-based reasoning, decision tree, stock selection, machine learning

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Authors: Aristeidis Samitas, Evangelos Vasileiou

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The aim of this study is to examine the month and the trading month effect under changing financial trends. We choose the Greek stock market to implement our assumption because there are clear and long term periods of financial growth and recession. Daily financial data from Athens Exchange General Index for the period 2002-2012 are considered. The paper employs several linear and non-linear models, although the TGARCH asymmetry model best fits in this sample and for this reason we mainly present the TGARCH results. Empirical results show that changing economic and financial conditions influences the calendar effects. Especially, the trading month effect totally changes in each fortnight according to the financial trend. On the other hand, in Greece the January effect exists during the growth periods, although it does not exist when the financial trend changes. The findings are helpful to anybody who invest and deals with the Greek stock market. Moreover, they may pave the way for an alternative calendar anomalies research approach, so it may be useful to investors who take into account these anomalies when they draw their investment strategy.

Keywords: month effect, trading month effect, economic cycles, crisis

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Authors: Mussa Hussaini, Supasith Chonglerttham

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Stocks are usually classified according to their characteristics which are unique enough such that the performance of each category can be differentiated from another. The reasons behind such classifications in the financial market are sometimes financial innovation or it can also be because of finding a premium in a group of stocks with similar features. One of the major classifications in stocks market is called momentum strategy. Based on this strategy stocks are classified according to their past performances into past winners and past losers. Momentum in a stock market refers to the idea that stocks will keep moving in the same direction. In other word, stocks with rising prices (past winners stocks) will continue to rise and those stocks with falling prices (past losers stocks) will continue to fall. The performance of this classification has been well documented in numerous studies in different countries. These studies suggest that past winners tend to outperform past losers in the future. However, academic research in this direction has been limited in countries such as Thailand and to the best of our knowledge, there has been no such study in Thailand after the financial crisis of 1997. The significance of this study stems from the fact that Thailand is an open market and has been encouraging foreign investments as one of the means to enhance employment, promote economic development, and technology transfer and the main equity market in Thailand, the Stock Exchange of Thailand is a crucial channel for Foreign Investment inflow into the country. The equity market size in Thailand increased from $1.72 billion in 1984 to $133.66 billion in 1993, an increase of over 77 times within a decade. The main contribution of this paper is evidence for size category in the context of the equity market in Thailand. Almost all previous studies have focused solely on large stocks or indices. This paper extends the scope beyond large stocks and indices by including small and tiny stocks as well. Further, since there is a distinct absence of detailed academic research on momentum strategy in the Stock Exchange of Thailand after the crisis, this paper also contributes to the extension of existing literature of the study. This research is also of significance for those researchers who would like to compare the performance of this strategy in different countries and markets. In the Stock Exchange of Thailand, we examined the performance of momentum strategy from 2010 to 2014. Returns on portfolios are calculated on monthly basis. Our results on momentum strategy confirm that there is positive momentum profit in large size stocks whereas there is negative momentum profit in small size stocks during the period of 2010 to 2014. Furthermore, the equal weighted average of momentum profit of both small and large size category do not provide any indication of overall momentum profit.

Keywords: momentum strategy, past loser, past winner, stock exchange of Thailand

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Authors: Almoutassem Bellah Nasser

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This paper is aimed at calculating the intangible assets of Jordanian economy. This effort is a response to the demand from corporations for these services which reflects a perceived gap in internal and external financial reporting on intangible investments. The main conclusion of the paper is to suggest that the way forward to a standardized, more comparable approach to measuring intangible capital is to employ CIV method of valuation. Published macroeconomic data traditionally exclude most intangible investment from measured GDP. This situation is beginning to change as some attempts have been made to measure the amount of intangible assets. It was found that intangible assets account for $164.20 million in all the listed companies of Jordan. All this money does not appear on the balance sheets of these companies and hence requires special attention of policy makers for better utilization.

Keywords: intangible capital, stock prices, Amman Stock Exchange

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Authors: Sumit Sen, Sohan Khedekar, Umang Shinde, Shivam Bhargava

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This study has been undertaken to investigate whether the deep learning models are able to predict the future stock prices by training the model with the historical stock price data. Since this work required time series analysis, various models are present today to perform time series analysis such as Recurrent Neural Network LSTM, ARIMA and Facebook Prophet. Applying these models the movement of stock price of stocks are predicted and also tried to provide the future prediction of the stock price of a stock. Final product will be a stock price prediction web application that is developed for providing the user the ease of analysis of the stocks and will also provide the predicted stock price for the next seven days.

Keywords: Autoregressive Integrated Moving Average, Deep Learning, Long Short Term Memory, Time-series

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Authors: Hasnun Wara Khondker, M. Tarek Morad

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Bangladesh is one of the most populous countries of the world in terms of density. Dhaka, the capital of Bangladesh currently has a population of approximately 15-16 million of which around 9 million people are accommodated in Dhaka South City Corporation (DSCC) within around 109 square kilometer area. Despite having various urban issues, country is at its pick of economic progress and Dhaka is the core of this economic growth. To ensure the proper economic development and citizens wellbeing, city needs an ingenious, congestion-free public transportation network. Bus stop/bus bay is an essential infrastructure for ensuring efficient public transportation flow within the city along with enhancing accessibility, user comfort, and safety through public amenities. At present, there is no established Mass Rapid Transit or Bus Rapid Transit network within the city and therefore these private owned buses are the only major mode of mass transportation of Dhaka city. DSCC has undertaken a project to re-design several bus stops and bus bays according to the universal standard for better urban mobility and user satisfaction. This paper will analyze the design approach of the bus stop/bay infrastructure within Dhaka South, putting the research lens on sustainable urban mobility with case studies of similar kind of urban context. The paper will also study the design process with setting several parameters, i.e., accessibility, passenger safety, comfort, sustainability, etc. Moreover, this research will recommend a guideline for designing a bus stop based on the analysis of the design methods.

Keywords: bus stop, Dhaka, public transportation, sustainable urban mobility, universal accessibility, user safety

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Authors: Nikolaos Konstantopoulos, Aristeidis Samitas, Vasileiou Evangelos

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The purpose of this study is to examine if the financial trends influence not only the stock markets’ returns, but also their anomalies. We choose to study the day of the week effect (DOW) for the Greek stock market during the Euro period (2002-12), because during the specific period there are not significant structural changes and there are long term financial trends. Moreover, in order to avoid possible methodological counterarguments that usually arise in the literature, we apply several linear (OLS) and nonlinear (GARCH family) models to our sample until we reach to the conclusion that the TGARCH model fits better to our sample than any other. Our results suggest that in the Greek stock market there is a long term predisposition for positive/negative returns depending on the weekday. However, the statistical significance is influenced from the financial trend. This influence may be the reason why there are conflict findings in the literature through the time. Finally, we combine the DOW’s empirical findings from 1985-2012 and we may assume that in the Greek case there is a tendency for long lived turn of the week effect.

Keywords: day of the week effect, GARCH family models, Athens stock exchange, economic growth, crisis

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Authors: Seyedmohsen Mortazavi

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The purpose of this research is to investigate the personality types of internal auditors on the quality of financial reporting in companies admitted to the Tehran Stock Exchange. Personality type is one of the issues that emphasizes the field of auditors' behavior, and this field has attracted the attention of shareholders and stock companies today, because the auditors' personality can affect the type of financial reporting and its quality. The research is applied in terms of purpose and descriptive and correlational in terms of method, and a researcher-made questionnaire was used to check the research hypotheses. The statistical population of the research is all the auditors, accountants and financial managers of the companies admitted to the Tehran Stock Exchange, and due to their large number and the uncertainty of their exact number, 384 people have been considered as a statistical sample using Morgan's table. The researcher-made questionnaire was approved by experts in the field, and then its validity and reliability were obtained using software. For the validity of the questionnaire, confirmatory factor analysis was first examined, and then using divergent and convergent validity; Fornell-Larker and cross-sectional load test of the validity of the questionnaire were confirmed; Then, the reliability of the questionnaire was examined using Cronbach's alpha and composite reliability, and the results of these two tests showed the appropriate reliability of the questionnaire. After checking the validity and reliability of the research hypotheses, PLS software was used to check the hypotheses. The results of the research showed that the personalities of internal auditors can affect the quality of financial reporting; The personalities investigated in this research include neuroticism, extroversion, flexibility, agreeableness and conscientiousness, all of these personality types can affect the quality of financial reporting.

Keywords: flexibility, quality of financial reporting, agreeableness, conscientiousness

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Authors: Shamshiri Mitra, Abedi Rahim

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This paper investigates corporate investment behavior and its relationship with ownership structure and financial leverage for the listed company of Tehran stock exchange during 2008-2012. The results show that the concentration of ownership has s significant positive effect on corporate investment. The results for the kind of major owners show that institutional ownership had a positive significant effect and state and individual ownership had negative significant effects on the corporate investment but the effect of corporate ownership was not significant. Furthermore the effect of financial leverage was negative and significant.

Keywords: corporate investment behavior, financial leverage, ownership structure corporate investment behavior

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Authors: Khandoker Upama Kabir, Mohammad Fuhad Anwar Sinha

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Dhaka, the capital of Bangladesh, is known not only for its fast growing economy, lively atmosphere, rich history, and culture but is also known for having a reputation of being a vastly populated city. The historic city centre of Dhaka (currently known as Puran Dhaka or Old Dhaka) which was conceived around the Pre-Mughal era and holds a lot of history and heritage of the region. This historic site has further been neglected, and most of the urban development has been done without integrating this part of the city into the plans. As a result, the festivals that take place traditionally throughout the year in this area create a greater impact on the urban fabric of the whole city. These festivals generate a huge amount of visitors and play a huge role in shaping the identity of the people. This paper will attempt to look at the importance of these traditions, the way these festivals are influencing the urban life of the community, and whether or not it has any significant effect on the economy. Through the use of both primary and secondary sources and SWOT analysis, this paper will attempt to identify the issues faced during these festivals. This paper will also try to suggest some basic remedies based on general comparisons between case studies of similar festivals celebrated globally and how these countries are dealing with such issues while also promoting tourism.

Keywords: urban fabric, festivals, cultural celebration, impact, historic city centre urban memory, mega events

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Authors: H. Florianová, J. Nešleha

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Financial derivatives are considered to be risky investment instruments which could possibly bring another financial crisis. As prevention, European Union and its member states have released new legal acts adjusting this area of law in recent years. There have been several cases in history of capital markets worldwide where it was shown that legislature may affect behavior of subjects on capital markets. In our paper we analyze main events on selected European stock exchanges in order to apply them on three chosen markets - Czech capital market represented by Prague Stock Exchange, German capital market represented by Deutsche Börse and Polish capital market represented by Warsaw Stock Exchange. We follow time series of development of the sum of listed derivatives on these three stock exchanges in order to evaluate popularity of those exchanges. Afterwards we compare newly listed derivatives in relation to the speed of development of these exchanges. We also make a comparison between trends in derivatives and shares development. We explain how a legal regulation may affect situation on capital markets. If the regulation is too strict, potential investors or traders are not willing to undertake it and move to other markets. On the other hand, if the regulation is too vague, trading scandals occur and the market is not reliable from the prospect of potential investors or issuers. We see that making the regulation stricter usually discourages subjects to stay on the market immediately although making the regulation vaguer to interest more subjects is usually much slower process.

Keywords: capital markets, financial derivatives, investors' behavior, regulation

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Authors: Jagbir Singh Kadyan, C. A. Suman Kadyan

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The researchers attempts to establish whether a relationship exists between the social activities undertaken & the funds that has been spent by the selected corporate organisations. Corporate listed on the (NSE) National Stock Exchange of India, under different categories shall be selected as a sample for the purpose of this study. The researches shall also study the dynamics of corporate social responsibility funding, financing & management of corporate social responsibility funds by the above selected organisations in the Indian context. The rationale behind selecting & undertaking specific corporate social responsibility activities shall be analysed & interpreted to discover the real drivers of corporate social responsibility. Besides above, an attempt shall further make an effort to understand & analyse the nature of impact on the selected corporate organisations on its overall performances due to the activities undertaken under their specific corporate social responsibility programs.

Keywords: corporate social responsibility, organisational performance, national stock exchange, sustainability, society, health, education, sanitation, environment

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Authors: Bisi S. Olawoyin

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This study attempts an exploration into behavioural finance in which the traditional assumptions of expected utility maximization with rational investors in efficient markets are dropped. It reviews prior research and evidence about how psychological biases affect investors behaviour and stock selection. This study examined the relationship between demographic variables and financial behaviour biases among public sector retirees who invested in the Nigerian Stock Exchange prior to their retirement. By using questionnaire survey method, a total of 214 valid convenient samples were collected in order to determine how specific demographic and psychological trait affect stock selection between dividend paying and non-dividend paying stocks. Descriptive statistics and OLS were used to analyse the results. Findings showed that most of the retirees prefer dividend paying stocks in few years preceding their retirement but still hold on to their non-dividend paying stock on retirement. A significant difference also exists between senior and junior retirees in preference for non-dividend paying stocks. These findings are consistent with the clientele theories of dividend.

Keywords: behavioural finance, clientele theories, dividend paying stocks, stock selection

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Authors: Mahdi Azizzadeh, Ali Nabizadeh

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This paper investigates whether ownership structure has significant effects on dividend policy and the percentage of cash dividend payout ratio in Iranian companies listed on the Tehran Stock Exchange. We use a sample of 300 firm-years for 2010-2014. Results indicate that there is no significant relationship between family ownership and/or institutional ownership and dividend policy. Furthermore, there is no significant relationship between dividend policies in family-owned firms with high or low institutional ownership. However, our empirical test shows that family firms with a low level of institutional investors distribute more cash dividends on average than family firms with a high level of institutional ownership.

Keywords: family ownership, institutional ownership, dividend policy, dividend payout ratio

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Authors: Fatin Fadhilah Hasib, Dewi Nuraini, Nisful Laila, Muhammad Madyan

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A big political event such as Cabinet reshuffle mostly can affect the stock price positively or negatively, depend on the perception of each investor and potential investor. This study aims to analyze the movement of the market and trading activities which respect to an event using event study method. This method is used to measure the movement of the stock exchange in which abnormal return can be obtained by investor related to the event. This study examines the differences of reaction on abnormal return and trading volume activity from the companies listed in the Jakarta Islamic Index (JII), before and after the announcement of the Cabinet Work Volume II on 27 July 2016. The study was conducted in observation of 21 days in total which consists of 10 days before the event and 10 days after the event. The method used in this study is event study with market adjusted model method that observes market reaction to the information of an announcement or publicity events. The Results from the study showed that there is no significant negative nor positive reaction at the abnormal return and abnormal trading before and after the announcement of the cabinet reshuffle. It is indicated by the results of statistical tests whose value not exceeds the level of significance. Stock exchange of the JII just reflects from the previous stock prices without reflecting the information regarding to the Cabinet reshuffle event. It can be concluded that the capital market is efficient with a weak form.

Keywords: abnormal return, abnormal trading volume activity, event study, political event

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Authors: Ying Guo, Miaochan Li, David Yang, Xiao-Yan Li

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This paper examines the relevance of accounting information to stock prices at different periods using manufacturing companies listed in China’s Growth Enterprise Market (GEM). We find that both the average stock price at fiscal year-end and the average stock price one month after fiscal year-end are more relevant to the accounting information than the closing stock price four months after fiscal year-end. This implies that Chinese stock markets react before the public disclosure of accounting information, which may be due to information leak before official announcements. Our findings confirm that accounting information is relevant to stock prices for Chinese listed manufacturing companies, which is a critical question to answer for investors who have interest in Chinese companies.

Keywords: accounting information, response time, value relevance, stock price

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Authors: Hy Dang, Bo Mei

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The development of machine learning methods and techniques has opened doors for investigation in many areas such as medicines, economics, finance, etc. One active research area involving machine learning is stock market prediction. This research paper tries to consider multiple techniques and methods for stock movement prediction using historical price or price factors. The paper explores the effectiveness of some deep learning frameworks for forecasting stock. Moreover, an architecture (TimeStock) is proposed which takes the representation of time into account apart from the price information itself. Our model achieves a promising result that shows a potential approach for the stock movement prediction problem.

Keywords: classification, machine learning, time representation, stock prediction

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Authors: Deniz Peksen

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This thesis aims to predict trend movement of closing price of stock and to maximize portfolio by utilizing the predictions. In this context, the study aims to define a stock portfolio strategy from models created by using Logistic Regression, Gradient Boosting and Random Forest. Recently, predicting the trend of stock price has gained a significance role in making buy and sell decisions and generating returns with investment strategies formed by machine learning basis decisions. There are plenty of studies in the literature on the prediction of stock prices in capital markets using machine learning methods but most of them focus on closing prices instead of the direction of price trend. Our study differs from literature in terms of target definition. Ours is a classification problem which is focusing on the market trend in next 20 trading days. To predict trend direction, fourteen years of data were used for training. Following three years were used for validation. Finally, last three years were used for testing. Training data are between 2002-06-18 and 2016-12-30 Validation data are between 2017-01-02 and 2019-12-31 Testing data are between 2020-01-02 and 2022-03-17 We determine Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate as benchmarks which we should outperform. We compared our machine learning basis portfolio return on test data with return of Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate. We assessed our model performance with the help of roc-auc score and lift charts. We use logistic regression, Gradient Boosting and Random Forest with grid search approach to fine-tune hyper-parameters. As a result of the empirical study, the existence of uptrend and downtrend of five stocks could not be predicted by the models. When we use these predictions to define buy and sell decisions in order to generate model-based-portfolio, model-based-portfolio fails in test dataset. It was found that Model-based buy and sell decisions generated a stock portfolio strategy whose returns can not outperform non-model portfolio strategies on test dataset. We found that any effort for predicting the trend which is formulated on stock price is a challenge. We found same results as Random Walk Theory claims which says that stock price or price changes are unpredictable. Our model iterations failed on test dataset. Although, we built up several good models on validation dataset, we failed on test dataset. We implemented Random Forest, Gradient Boosting and Logistic Regression. We discovered that complex models did not provide advantage or additional performance while comparing them with Logistic Regression. More complexity did not lead us to reach better performance. Using a complex model is not an answer to figure out the stock-related prediction problem. Our approach was to predict the trend instead of the price. This approach converted our problem into classification. However, this label approach does not lead us to solve the stock prediction problem and deny or refute the accuracy of the Random Walk Theory for the stock price.

Keywords: stock prediction, portfolio optimization, data science, machine learning

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Authors: Jagbir Singh Kadyan

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This research paper critically analyse the performance of those Indian Automobile Companies which are listed and traded on the National Stock Exchange (NSE) of India and which are also included in the NSE nifty auto Index. In India, CSR–Corporate Social Responsibility is mandatory for certain qualifying companies under the Indian Companies Act 2013, which replaces the erstwhile Companies Act 1956. There has been a significant shift in the focus and approaches of the Indian Corporates towards their CSR obligations with the insertion of section 135, revision of section 198 and introduction of schedule VII of the Indian Companies Act 2013. Every such qualifying companies are required to mandatorily spend at least 2% of their annual average net profit of the immediately preceding three financial years on such CSR activities as specified under schedule VII of the Companies act 2013. This research paper analyzes the CSR performance of such Indian companies. This research work is originally based on the secondary data. The annual reports of the selected Indian automobile companies have been extensively used and considered for this research work.

Keywords: board of directors, corporate social responsibility, CSR committees, Indian automobile companies, Indian companies act 2013, national stock exchange

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Authors: Tri Wijayanti Septiarini, Agus Maman Abadi, Muhammad Rifki Taufik

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The exchange rate of IDR/USD can be the indicator to analysis Indonesian economy. The exchange rate as a important factor because it has big effect in Indonesian economy overall. So, it needs the analysis data of exchange rate. There is decomposition data of exchange rate of IDR/USD to be frequency and time. It can help the government to monitor the Indonesian economy. This method is very effective to identify the case, have high accurate result and have simple structure. In this paper, data of exchange rate that used is weekly data from December 17, 2010 until November 11, 2014.

Keywords: the exchange rate, fuzzy mamdani, discrete wavelet transforms, fuzzy wavelet

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Authors: Nariman O. Kandil, Ehab K. Abou-Elkheir, Amr M. Kotb

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Effective IT governance guarantees the strategic alignment of IT and business goals, risk mitigation control, and better IT and business performance. This study seeks to examine empirically the extent of IT governance implementation within the firms listed on the Egyptian stock exchange (EGX30) and its determinants. Accordingly, 18 semi-structured interviews face to face, phone, and video-conferencing interviews using various tools (e.g., WebEx, Zoom, and Microsoft Teams) were undertaken at the interviewees’ offices in Egypt between the end of November 2019 and the end of August 2020. Results suggest that there are variances in the extent of IT Governance (ITG) implementation within the firms listed on the Egyptian stock exchange (EGX30), mainly caused by the industry type and internal and external triggers. The results also suggest that the organization size, the type of auditor, the criticality of the industry, the effective processes & KPIs, and the information intensity expertise of the CIO have a significant impact on IT governance implementation within the firms.

Keywords: effective IT governance, Egyptian market, information security, risk controls

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Authors: Carol Anne Hargreaves

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A key issue in stock investment is how to select representative features for stock selection. The objective of this paper is to firstly determine whether an automated stock investment system, using machine learning techniques, may be used to identify a portfolio of growth stocks that are highly likely to provide returns better than the stock market index. The second objective is to identify the technical features that best characterize whether a stock’s price is likely to go up and to identify the most important factors and their contribution to predicting the likelihood of the stock price going up. Unsupervised machine learning techniques, such as cluster analysis, were applied to the stock data to identify a cluster of stocks that was likely to go up in price – portfolio 1. Next, the principal component analysis technique was used to select stocks that were rated high on component one and component two – portfolio 2. Thirdly, a supervised machine learning technique, the logistic regression method, was used to select stocks with a high probability of their price going up – portfolio 3. The predictive models were validated with metrics such as, sensitivity (recall), specificity and overall accuracy for all models. All accuracy measures were above 70%. All portfolios outperformed the market by more than eight times. The top three stocks were selected for each of the three stock portfolios and traded in the market for one month. After one month the return for each stock portfolio was computed and compared with the stock market index returns. The returns for all three stock portfolios was 23.87% for the principal component analysis stock portfolio, 11.65% for the logistic regression portfolio and 8.88% for the K-means cluster portfolio while the stock market performance was 0.38%. This study confirms that an automated stock investment system using machine learning techniques can identify top performing stock portfolios that outperform the stock market.

Keywords: machine learning, stock market trading, logistic regression, cluster analysis, factor analysis, decision trees, neural networks, automated stock investment system

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Authors: Prateep Wajeetongratana

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This study investigates the management accountant’s roles that link with the creation of corporate shared value to enable more effective decision-making and improve the information needs of stakeholders. Mixed method is employed to collect using triangulation for credibility. A quantitative approach is employed to conduct a survey of 200 Thai companies providing annual reports in the Stock Exchange of Thailand. The results of the study reveal that environmental and social data incorporated in a corporate social responsibility (CSR) disclosure are based on the indicators of the Global Reporting Initiatives (GRI) at a statistically significant level of 0.01. Environmental and social indicators in CSR are associated with environmental and social data disclosed in the annual report to support stakeholders’ and the public’s interests that are addressed and show that a significant relationship between environmental and social in CSR disclosures and the information in annual reports is statistically significant at the 0.01 level.

Keywords: corporate social responsibility, creating shared value, management accountant’s roles, stock exchange of Thailand

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Authors: Ben Kwame Agyei-Mensah

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This study investigated the influence of firm-specific characteristics which include proportion of Non-Executive Directors, ownership concentration, firm size, profitability, debt equity ratio, liquidity and leverage on the extent and quality of financial ratios disclosed by firms listed on the Ghana Stock Exchange. The research was conducted through detailed analysis of the 2012 financial statements of the listed firms. Descriptive analysis was performed to provide the background statistics of the variables examined. This was followed by regression analysis which forms the main data analysis. The results of the extent of financial ratio disclosure level, mean of 62.78%, indicate that most of the firms listed on the Ghana Stock Exchange did not overwhelmingly disclose such ratios in their annual reports. The results of the low quality of financial ratio disclosure mean of 6.64% indicate that the disclosures failed woefully to meet the International Accounting Standards Board's qualitative characteristics of relevance, reliability, comparability and understandability. The results of the multiple regression analysis show that leverage (gearing ratio) and return on investment (dividend per share) are associated on a statistically significant level as far as the extent of financial ratio disclosure is concerned. Board ownership concentration and proportion of (independent) non-executive directors, on the other hand were found to be statistically associated with the quality of financial ratio disclosed. There is a significant negative relationship between ownership concentration and the quality of financial ratio disclosure. This means that under a higher level of ownership concentration less quality financial ratios are disclosed. The findings also show that there is a significant positive relationship between board composition (proportion of non-executive directors) and the quality of financial ratio disclosure.

Keywords: voluntary disclosure, firm-specific characteristics, financial reporting, financial ratio disclosure, Ghana stock exchange

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Authors: Rosdyana Mangir Irawan Kusuma, Wei-Chun Kao, Ho-Thi Trang, Yu-Yen Ou, Kai-Lung Hua

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Stock market prediction is still a challenging problem because there are many factors that affect the stock market price such as company news and performance, industry performance, investor sentiment, social media sentiment, and economic factors. This work explores the predictability in the stock market using deep convolutional network and candlestick charts. The outcome is utilized to design a decision support framework that can be used by traders to provide suggested indications of future stock price direction. We perform this work using various types of neural networks like convolutional neural network, residual network and visual geometry group network. From stock market historical data, we converted it to candlestick charts. Finally, these candlestick charts will be feed as input for training a convolutional neural network model. This convolutional neural network model will help us to analyze the patterns inside the candlestick chart and predict the future movements of the stock market. The effectiveness of our method is evaluated in stock market prediction with promising results; 92.2% and 92.1 % accuracy for Taiwan and Indonesian stock market dataset respectively.

Keywords: candlestick chart, deep learning, neural network, stock market prediction

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Authors: Jitendra Aswani

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In the first section of this study, impact of Global Financial Crisis (GFC) on the synchronization of fourteen Asian Stock Markets (ASM’s) of countries like Hong Kong, India, Thailand, Singapore, Taiwan, Pakistan, Bangladesh, South Korea, Malaysia, Indonesia, Japan, China, Philippines and Sri Lanka, has been analysed using the network science and its metrics like degree of node, clustering coefficient and network density. Then in the second section of this study by introducing the US stock market in existing network and developing a Minimum Spanning Tree (MST) spread of crisis from the US stock market to Asian Stock Markets (ASM) has been explained. Data used for this study is adjusted the closing price of these indices from 6th January, 2000 to 15th September, 2013 which further divided into three sub-periods: Pre, during and post-crisis. Using network analysis, it is found that Asian stock markets become more interdependent during the crisis than pre and post crisis, and also Hong Kong, India, South Korea and Japan are systemic important stock markets in the Asian region. Therefore, failure or shock to any of these systemic important stock markets can cause contagion to another stock market of this region. This study is useful for global investors’ in portfolio management especially during the crisis period and also for policy makers in formulating the financial regulation norms by knowing the connections between the stock markets and how the system of these stock markets changes in crisis period and after that.

Keywords: global financial crisis, Asian stock markets, network science, Kruskal algorithm

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Authors: Dewan Hasin Mahtab, Farzana Sadia

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At present, wastewater treatment has become essential to maintain a constant supply of safe water as well as to protect the environment. Due to overpopulation and overconsumption, the water quality from various surface water sources is degrading every day. Being one of the megacities in the world, Dhaka City, is going through rapid industrialization and urbanization. The effluents from these industries and factories are mostly discharged directly into the rivers without any treatment. As such, the quality of water of Buriganga is being afflicted with a noisome problem of pollution. The water of the Buriganga River has become detrimental to humans, animals, and the environment. It has become crucial to conserve the environment so that we can save both ourselves and the environment. The first step towards it should be analyzing the wastewater to decide the further steps of the treatment process. Increased population and increased consumption both contribute to water pollution. Mohammadpur is a developing area of Dhaka City, and Kamrangirchar is one of the largest slum areas in Dhaka City. The total study area is 6.13 sq. Km of Dhaka city with a population of 4,73,310 people. Of them, 86.47% had their own latrine, 47% were directly connected to the drain, 55% had septic tanks, and 70.09% of them cleaned their septic tank once a year. The pH, Dissolved Oxygen, Chemical Oxygen Demand, Biochemical Oxygen Demand, Total Dissolved Solid, Total Suspended and total coliforms of wastewater from two samples of both Mohammadpur and Kamrangirchar was analyzed. The DO level from the water bodies of Kamrangirchar was found very low, making the water bodies inhabitable for aquatic plants and animals. The BOD and COD level was extremely high from samples collected from Mohammadpur. The total coliforms count was found too high during the wet season, making it a potential health concern in the wet season in these two areas.

Keywords: Dhaka, environmental conservation rule, sanitation, wastewater

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Authors: Apedzan Emmanuel Kighir

Abstract:

This research investigates dividends smoothing among non-financial companies trading on the Nigerian Stock Exchange in an era of unclaimed dividends from 2004 to 2013. There has been a raging controversy among Regulatory Authorities, Company Executives, Registrars of Companies, Shareholders and the general public regarding the increasing incidence of unclaimed dividends in Nigeria. The objective of this study is to find out if corporate earnings management through dividends smoothing is implicated in unclaimed dividends among Nigerian non-financial firms. The research used panel data and employed Generalized Method of Moment as method of analysis. The research finds evidence of dividends-smoothing in this era of unclaimed dividends in Nigeria. The research concludes that dividends-smoothing is a trigger and red flag for unclaimed dividends, an output of earnings management. If earnings management and hence unclaimed dividends in Nigeria is allowed to continue, it will lead to great consequences to the investors and corporate policy of government. It is believed that the research will assist investors and government in making informed decisions regarding dividends policy in Nigeria.

Keywords: dividends smoothing, non financial companies, Nigerian stock exchange, unclaimed dividends, corporate earnings management

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Authors: Algia Hammami, Abdelfatteh Bouri

Abstract:

In this work, our objective is to study the transmission of volatility between oil and stock markets in developed (USA, Germany, Italy, France and Japan) and emerging countries (Tunisia, Thailand, Brazil, Argentina, and Jordan) for the period 1998-2015. Our methodology consists of analyzing the monthly data by the GARCH-BEKK model to capture the effect in terms of volatility in the variation of the oil price on the different stock market. The empirical results in the emerging countries indicate that the relationships are unidirectional from the stock market to the oil market. For the developed countries, we find that the transmission of volatility is unidirectional from the oil market to stock market. For the USA and Italy, we find no transmission between the two markets. The transmission is bi-directional only in Thailand. Following our estimates, we also noticed that the emerging countries influence almost the same extent as the developed countries, while at the transmission of volatility there a bid difference. The GARCH-BEKK model is more effective than the others versions to minimize the risk of an oil-stock portfolio.

Keywords: GARCH, oil prices, stock market, volatility transmission

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Authors: Chih-Hsiang Chang, Chia-Ching Tsai

Abstract:

The aim of this study is to examine the stock price effect of the enterprises being classified as socially responsible. We explore the stock price response to the announcement that an enterprise is selected for the Taiwan Corporate Sustainability Awards. Empirical results indicate that the announcements of the Taiwan Corporate Sustainability Awards provide useful informational content to stock market. We find the evidence of insignificantly positive short-term and significantly positive long-term price reaction to the enterprises being classified as socially responsible. This study concludes that investors in the Taiwan stock market tend to view an enterprise being selected for the Taiwan Corporate Sustainability Awards as one with superior quality and long-term price potential.

Keywords: corporate social responsibility, stock price effect, Taiwan stock market, investments

Procedia PDF Downloads 126