P. S. Sanju

Bio: P. S. Sanju is an academic researcher from Pondicherry University. The author has contributed to research in topics: Dividend & Error correction model. The author has an hindex of 3, co-authored 3 publications receiving 63 citations.

Determinants of share prices in India

Abstract: The focus of this study is to identify the determinants of share prices in the Indian market. The study uses panel data pertaining to three sectors viz., auto, healthcare and public sector undertakings over the period 2000-2009 and employs the fully modified ordinary least squares method. The results indicate that the variables dividend, price-earnings ratio and leverage are significant determinants of share prices for all the sectors under consideration. Further, profitability is found to influence share prices only in the case of auto sector.

Long-run causal nexus between share price and dividend

Abstract: Purpose – The purpose of this paper was to examine the long-run causal relations between share price and dividend in the Indian market. Design/methodology/approach – Panel vector error correction model is estimated to examine the long-run causal relations between share price and dividend. Prior to this, panel unit root tests and panel cointegration tests are carried out to test the unit root properties of the data and test for the existence of long-run cointegrating relationship between the variables, respectively. Findings – The results of empirical investigation reveal that there exists bi-directional long-run causality between share price and dividends. Research limitations/implications – For the chosen sample, data on share price are available only for limited years. This limits the time dimension of the sample. Hence, in the future, the analysis can be extended to cover longer time series. Practical implications – The interplay between share prices and dividends needs to be given due consideration by...

Are dividend and investment decisions separable

Abstract: In this study, we address an econometric issue which has so far been neglected by the empirical studies on separation principle. The earlier studies largely applied Granger causality test by differencing the data if they are integrated time series. Such an approach produces specification bias if integrated variables in level are cointegrated and thus, ignoring the long run dynamics among the variables. To circumvent this problem, we test for cointegration between investments and dividends and estimate a dynamic panel vector error correction model. Annual time series data over the period 1995 to 2008 for various sectors chosen on the basis of the available sectoral indices of National Stock Exchange are considered for empirical analysis. The empirical evidence derived from group mean and lambda-Pearson tests seem to indicate that there is long run causal link between investments and dividends and therefore, firms’ decisions regarding dividend payout and investments are inseparable.

Enhancing Intrusion Detection in IoT Systems: A Hybrid Metaheuristics-Deep Learning Approach with Ensemble of Recurrent Neural Networks

Abstract: Significant benefits have been brought to various industries by IoT (Internet of Things), but new security challenges have also been introduced due to the sheer volume and complexity of IoT systems. The protection of IoT systems from attacks and the assurance of their security posture are ensured by intrusion detection systems (IDSs). Recently, machine learning (ML) strategies have been broadly adopted for IDSs in IoT systems. However, there is still room for improvement, particularly in addressing the physical and functional diversity of IoT systems. A hybrid metaheuristics-deep learning approach is proposed in this paper for enhancing intrusion detection in IoT systems. An advanced metaheuristics algorithm with an ensemble of recurrent neural networks (RNNs) can be utilized to enhance the intrusion detection in IoT. Different types of attacks in IoT systems are identified by employing LSTM and GRU models, which constitute the RNNs. Feature selections are performed using Harris hawk optimization and fractional derivative mutation, as employed in this paper. To assess the proposed approach, publicly available datasets were utilized, and the empirical analysis demonstrated that the proposed approach works well than the other related methods in terms of accuracy and efficiency. Overall, the proposed work presents a promising solution for enhancing intrusion detection in IoT systems, and it has the potential to serve as a foundation for future research in this field.

Analysis of Factors Affecting Share Prices: The Case of Bahrain Stock Exchange

Abstract: The 2007 global financial crisis caused unprecedented upheavals in the global stock markets and has shaken investor’s confidence due to the turbulent fluctuations and volatilities in stock prices. The present study is instrumental in identifying the main determinants affecting share prices in the Bahrain financial market. The study analyzes a panel data set of 41 companies listed in the Bahrain stock exchange for the period 2006-2010. The year 2006 is used as the first year of data collection as most of the companies were incorporated in 2005. Since the Bahrain bourse witnessed a turbulent period during the first half of 2010 due to political unrests causing 25.5% slump in the aggregate value of traded shares in the first half of 2010 and 7.59% drop in the Global Bahraini Index in the following year, the post-2010 period was deliberately ignored in this study. The estimation method is based on pooled OLS regression with robust standard errors, fixed effects and random effects models. Eight firm specific variables namely return on equity, book value per share, earnings per share, dividend per share, dividend yield, price earnings, debt to assets and controlled by firm size, have been studied to infer their impact on market price of shares in the respective market. The results indicate that the variables return on equity, book value per share, dividend per share, dividend yield, price earnings, and firm size are significant determinants of share prices in the Bahrain market. A high R2 (0.80) revealed under both the applied models further documents the significant impact of these variables on the market price of shares. This suggests that investors can make optimum investment decisions and be assured fair returns if they consider these determinants which have evolved to be the significant contributors to the market price of shares in Bahrain.

Determinants of Equity Share Prices in India: A Panel Data Approach

Abstract: The present study examines the fundamental determinants of share price in India. The study employs panel data consisting of annual time series data over the period 2006-2011 and cross-section data pertaining to 6 major sectors of the Indian economy, namely, Heavy and Manufacturing, Pharmaceutical, Energy, IT and ITES, Infrastructure and Banking. The panel data techniques, viz. Fixed Effects model and Random Effects model have been employed to investigate the objective. The empirical results reveal that the dividend per share has a negative and significant impact on the share price of manufacturing, pharmaceutical, energy and infrastructure sectors. These results are consistent with findings of Zahir and Khanna (1982), Malhotra (1987) and Sharma (2011), that dividend has influenced market price of share significantly in negative direction. The evidences show that earning per share and price-earnings ratio are being the crucial determinants of share prices of manufacturing, pharmaceutical sector, energy, infrastructure and commercial banking sectors. The findings indicate that size is being a significant factor in determining the share prices of all sectors under consideration except manufacturing. Moreover, the book value per share positively influences the share prices of pharmaceutical, energy, IT & ITES and Infrastructure. The present study confirms that performance of the fundamental ratios of the industry will be essential and immense helpful to investors and analysts in assessing the better stocks that belong to different industry groups.

The Determinants of Stock Prices in Pakistan

Abstract: Stock Investment is always a risky proposition and investors are reluctant to invest in Stock Market. If they came to know about the exact factors influencing the stock prices, they will invest in stocks confidently. This study examines the empirical relationship between the stock prices, financial fundamentals and macroeconomic factors in Karachi Stock Exchange. By applying the dynamic panel Generalized Method of Moments (GMM) technique on the data of 221 firms during 1995-2006, the analysis attempts to obtain efficient parameter estimates and to check the consistency of the link between stock price behavior, company fundamentals and macroeconomic factors. Several studies have been conducted to identify the factors of stock prices for a variety of countries, and the results have been mixed. It is found that previous behavior of stock prices, company size, previous earnings per share are the most important factors. In addition, macroeconomic indicators like, GDP growth, rate of interest and financial depth have significant relationship with the stock prices. Market to book value, share turnover ratio and inflation can also influence the stock price behavior. The corporate reforms of 2002 are responsible of increase in stock prices from 2002 to 2006. Investors in Pakistan have to decide which stock should be purchased. The results of this study will provide guideline to the investors in stock selection. While taking decisions they should take into account company informations as well as macroeconomic situation of the country simultaneously. The companies can set their policies and strategies in the light of relatively important factors, for business survival and success. The possible impact of macroeconomic factors may help the policy makers while setting monetary and fiscal policies.

An Assessment of the Determinants of Share Price in Nigeria: A Study of Selected Listed Firms

Abstract: This study examined the determinants of share prices in the Nigerian stock exchange market. To achieve the objective of this study, a total of 30 listed firms in the Nigerian stock exchange market were selected and analyzed for the study using the judgmental sampling technique. Also, the Nigerian stock exchange fact book and the corporate annual reports for the period 2006- 2010 were used for the study. The paper basically modelled the effects of financial performance, dividend payout and financial leverage on the share price of listed firms operating in the Nigerian stock exchange market using the regression analysis method. The study as part of its findings observed that there is a significant positive relationship between firms’ financial performance and the market value of share prices of the listed firms in Nigeria. Consequently, the paper concludes that firms’ financial performance, dividend payouts and financial leverage are strong determinants of the market value of share prices in Nigeria

Determinants of Share Price Movements in Bangladesh : Dividends and Retained Earnings

Abstract: Background and Problem Discussion: Financial scholars have been conducting studies of dividend policy for several decades; but different researchers have come to different conclusions. Financial economists have come to different conclusion about factors determining dividend policy and effect of dividend policies on common stock price. A general question may arise in the mind of the shareholders that the corporate dividend policy affects the value of their stocks. So, in addition to the theory of dividend policy, it is necessary to discuss the empirical evidence on the dividend payment practices of the corporations and their possible impacts on common stock prices. Empirical testing of dividend policy may focus on whether the determinants carry information in pricing the common stocks and whether the dividends are the only determinants serving as signals in conveying information about the current and future earnings of the corporation. Purpose: The present study will strives on the relative importance of dividends, retained earnings, and other determinants in the explanation of stock prices in Bangladesh with particular stock price of the companies associated with Dhaka Stock Exchange (henceforth DSE), an emerging capital market of Bangladesh. The prime objective of this study is to study determinants of market share price and to examine their functional relationships with the market price of common stocks trades in DSE. Method: Applied several pre-reviewed models to examine the dynamic relations between stock price and different financial variables. Data for selected companies listed in DSE for the period from 2000 to 2006 were collected from the annual reports of the respective companies, daily price quotation of DSE. Theory: Different related theories like, dividend theory, information contents, theory of information asymmetry, signalling theory, clientele effect theory were discussed to explain the basic concepts that is used to analyze the results. Different related models are also discussed to determine the appropriate model for my study. Analysis: I have used different models to explain the dynamic relationships of market price of common stocks with the determinants of market share price like dividends, retained earnings, lagged price earnings ratio and market price of previous year. Conclusion: The results of the empirical analysis evidences that dividends, retained earnings and other determinants have dynamic relationship with market share price. Findings also suggest that the overall impact of dividend on stock prices is comparatively better that that of retained earnings and expected dividends play an important role in the determination of stock prices whatever determinants, like lagged price earnings ratio or lagged price, are considered.