Stock Market Returns before and after Brokerage Firms' Fiscal Year-End: The Case of Tehran Stock Exchange

2017 ◽  
Author(s):  
Mahmood Pakbaz ◽  
Shahin Ahmadi ◽  
Majid Feshari
Author(s):  
Sampson Atuahene ◽  
Kong Yusheng ◽  
Geoffrey Bentum-Micah

In every economy, Stock markets are part of the key elements the build it up. A few decades ago, there has been a significant change in Ghana stock market returns (GSE). Our study examines the statistical and economic significance of investor sentiment, based on weather conditions/changes, on stock market returns. OLS models, assisted by unit root tests were employed in analyzing the data obtained from the Ghana stock exchange platform from 2000 to 2017. From our literature review, we discovered that investors’ perceptions play a central role in finalizing the direction of stock market returns. Regarding our empirical results, we tested whether weather variations influence the investment decisions of investors; we discovered that temperature and cloud cover significantly influences stock market returns. This is because of mood changes is associated with weather conditions variations. However, sunshine per our regression coefficient shows a statistically insignificant impact on investors’ investment choices. Precipitation to a large extend influence stock market activities further affecting its results negatively as our regression results depicted. We concluded stock brokerage firms, companies, and investors (foreign/local) must incorporate weather changes/effects when strategizing about their investment outcomes.


2021 ◽  
Vol 18 (4) ◽  
pp. 280-296
Author(s):  
Abdel Razzaq Al Rababa’a ◽  
Zaid Saidat ◽  
Raed Hendawi

Different models have been used in the finance literature to predict the stock market returns. However, it remains an open question whether non-linear models can outperform linear models while providing accurate predictions for future returns. This study examines the prediction of the non-linear artificial neural network (ANN) models against the baseline linear regression models. This study aims specifically to compare the prediction performance of regression models with different specifications and static and dynamic ANN models. Thus, the analysis was conducted on a growing market, namely the Amman Stock Exchange. The results show that the trading volume and interest rates on loans tend to explain the monthly returns the most, compared to other predictors in the regressions. Moreover, incorporating more variables is not found to help in explaining the fluctuations in the stock market returns. More importantly, using the root mean square error (RMSE), as well as the mean absolute error statistical measures, the static ANN becomes the most preferred model for forecasting. The associated forecasting errors from these metrics become equal to 0.0021 and 0.0005, respectively. Lastly, the analysis conducted with the dynamic ANN model produced the highest RMSE value of 0.0067 since November 2018 following the amendment to the Jordanian income tax law. The same observation is also seen since the emerging of the COVID-19 outbreak (RMSE = 0.0042).


Author(s):  
Adekunle Orelope Koleosho ◽  
Folajimi Festus Adegbie ◽  
Ayooluwa Olotu Ajayi- Owoeye

Sustainability of shareholder’s wealth has been a subject of discussion globally due to various decisions of the managers and the effect it has on company’s performance. Various corporate actions and information about the companies are disseminated over time and studies have shown the effect on shareholder's wealth. This study examined the effect of capital market returns on sustainability of shareholder's wealth in Nigeria Listed Companies. The study adopted ex-post facto research design. A sample of 57 companies from a target population of 168 companies listed on the Nigerian Stock Exchange (NSE) as December 2018 was randomly drawn across the various market sectors for the panel data. The study used secondary data from the NSE, CBN and companies’ data on the Bloomberg Terminals. Validity and reliability were premised on the statutory audit of the financial statement. The study adopted descriptive and inferential (Regression and Correlation) statistics to analyze the data. The study found that the stock market returns indicators (dividend per share, earnings and Leverage) have joint and statistically significant relationship with market price per share: DPS, EPS and LEV with Adjusted R2 = 0.738, F(3, 796) = 54.74, p = 0.108 > 0.05. The study concluded that stock market returns measured by dividend and earnings have a significant effect on the shareholders' wealth while leverage exerts a negative effect on Market Price per share. The study recommended that the management of the companies should embrace the payment of dividend to shareholders while ensuring the growth of earnings over the period to sustain shareholder's wealth.


2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Isiaka Akande Raifu ◽  
Terver Theophilus Kumeka ◽  
Alarudeen Aminu

AbstractGiven the effects COVID-19 pandemic on the financial sectors across the world, this study examined the reaction of stock returns of 201 firms listed in the Nigerian Stock Exchange to the COVID-19 pandemic and lockdown policy. We deployed both Pooled OLS and Panel VAR as estimation methods. Generally, the results from POLS show the stock market returns of the Nigerian firms reacted negatively more to the global COVID-19 confirmed cases and deaths than the domestic COVID-19 confirmed cases and deaths and lockdown policy. The results of the impulse response functions revealed that the effects of COVID-19 confirmed cases and deaths and lockdown policy shocks on stock returns oscillate between negative and positive before the stock market returns converge to the equilibrium in the long run. The FEVD results showed that growth in the COVID-19 confirmed cases, deaths and lockdown policy shocks explained little variations in stock market returns. Given our finding, we advocate for the relaxation of policy of lockdown and the combine use of monetary and fiscal policies to mitigate the negative effect of COVID-19 pandemic on stock market returns in Nigeria.


2012 ◽  
Vol 4 (5) ◽  
pp. 239-244 ◽  
Author(s):  
Hammad Hassan Mirza ◽  
Naveed Mushtaq .

Financial economists believe that the arbitrage forces in the market are the main reason of market efficiency and these forces are the fundamental concept of efficient market hypothesis (EMH). During last few years, various theoretical and empirical evidences have been presented to support the work of financial modeling for the markets with less than rational investors whose trading strategies are based on psychological factors like mood and emotions. Weather condition is among the substantial factors affecting investors’ mood and emotions. Present study investigates the impact of temperature on stock market returns in emerging economy of Pakistan. Using the daily temperature records and stock market indices of Karachi and Islamabad, the study has employed auto regressive (AR) – generalized autoregressive conditional heteroscedasticity (GARCH) model from 2006 to 2010. Based on AR (1)-GARCH (1, 1) estimation the study has found that weather temperatures of both Karachi and Islamabad are negatively related with Karachi Stock Exchange (KSE) and Islamabad Stock Exchange (ISE) index returns, respectively.


2020 ◽  
Vol 12 (2) ◽  
Author(s):  
Abdul Samad Shaikh ◽  
Muhammad Kashif ◽  
Sadia Shaikh

This paper investigates the financial ratios prediction on Stock Market Returns for Pakistan Stock Exchange. The research includes three financial ratios; Dividend Yield (DY), Earning Yield Ratio (EYR) and Book-to-Market Ratio (B/M); that have been observed through past researchers as predictors of Stock Market Returns. The theoretical framework is based on Arbitrage Pricing Theory and Capital Asset Pricing Model CAPM by Roll and Ross (1977) and Fama-French 3 factor (1992). Generalized Least Squares (GLS) is applied to estimate the predictive regressions, Cointegration runs are applied to evaluate the long-term relationship, and Generalized Methods of Moments (GMM) to measure the moments over the years and fluctuations in stock returns. The study results show financial ratios as strong predictor of stock return in Pakistan Stock Exchange, the GMM analyses reveal that the EYR has the higher predictive power than DY and B/M respectively. Furthermore, it is found that the financial ratios predictability is enhanced when ratios are combined in the multiple predictive regression models. The research findings are useful for the stock market investors to evaluate their decisions and for academic researchers to evaluate the stock market and investment predictability.


2017 ◽  
Vol 9 (2) ◽  
pp. 206
Author(s):  
Saseela Balagobei

The stock market is one of the most energetic sectors that play an important role in contributing to the wealth of the economy. It plays a crucial role in the economic growth and development of an economy which would benefit industries, trade and commerce as a whole. The aim of this study is to investigate the impact of macroeconomic variables on stock market returns in Sri Lanka. Dependent variable of this study is stock market return measured by All Share Price Index (ASPI) and All Share Total Return Index (ASTRI) and independent variables are macroeconomic variables, such as Interest Rate (IR), Inflation Rate (INF), Exchange Rate (ER), Factory Industry Production Index (FIPI) and money supply (MS).  The study targets all the companies listed and active in Colombo Stock Exchange (CSE) from 2006 to 2015. For analysis, secondary data was collected from annual reports of Central bank of Sri Lanka, Colombo Stock Exchange, Securities and Exchange Commission and Department of Census and Statistics. The results of the study reveal that the stock market returns is influenced by macroeconomic variables except money supply in Sri Lanka. Interest rate and factory industry production have negative influence on stock market return in Colombo Stock exchange while inflation rate and exchange rate have positive influence on stock market return. The findings of the study may be useful to public and economy especially stock market investors to focus the macroeconomic variables for making their effective decisions in order to enhance their stock market returns.


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