A logistic regression model is has also become a popular model because of its ability to predict, classify and draw relationships between a dichotomous dependent variable and dependent variables. On the other hand, the R programming language has become a popular language for building and implementing predictive analytics models. In this paper, we apply a logistic regression model in the R environment in order to examine whether daily trading volume at the Botswana Stock Exchange influence daily stock market movement. Specifically, we use a logistic regression model to find the relationship between daily stock movement and the trading volumes experienced in the recent five previous trading days. Our results show that only the trading volume for the third previous day influence current stock market index movement. Overall, trading volumes of the past five days were found not have an impact on today’s stock market movement. The results can be used as a basis for building a predictive model that utilizes trading as a predictor of stock market movement.

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Trading Volume as a Predictor of Market Movement: An Application of Logistic Regression in the R environment

The formation of Islamic capital market under the subcomponent of Islamic financial system scratch a milestones development of Islamic finance in Malaysia. The Islamic capital market operates in mirror with convention capital market in expending, deepening and broadening Malaysia financial system. Malaysia is one of the REIT markets that value both the Islamic and conventional practices, such flexibility makes the attract not only to the local investor but also Islamic investors and foreign investor. The major source that generates income for REIT is the rental of the commercial real estate invested and hold as portfolio by the REIT management company. Furthermore, Malaysia REIT is known to be defensive stocks which consist of cyclic income producing assets that has some potential of asset appreciation. On the other hand, it witnessed by the moderation of Malaysia government bond yields created a lower pressure on the REIT stock price and analyst’s report highlighted the uncertainties on global crude oil prices and inflation is main concerned to REIT investors. In addition, the revision of 2019 tax system in Malaysia furnished a long run affected the dividend payout and volatility of REIT stock price. Therefore, this impact on the REIT stock liquidity and trading volume experiencing anil liquid trading. Therefore, the impact of external forces towards the mirror of two type of Malaysia REITs is significant to the investors, policy makers and government to outline the short-run relationship and facilitate future growth. The Vector auto regression model, granger causality and variance decomposition employed in this study to analyze the mirror of two types Malaysia REIT stock return. The empirical finding shows that the variability of dividend yield is vital explanatory variables to explain the both type of REIT stock return in Malaysia followed by interest rate for Islamic REIT stock return. The mirror of conventional REIT further implicated that trading volume and global crude oil price are useful to forecasting the changes in the stock return. Nutshell, this study provides a discussion of Malaysia REIT stock return behavior and it should be given necessary attention by researchers in ensuring the newly develop Islamic REIT are competitive and stability as the conventional REIT.

https://turcomat.org/index.php/turkbilmat/article/download/760/553

The Mirror of Malaysia Real Estate Investment Trust Stock Return in the Short-Run Dynamics

This research is aim to investigate the relationship between the stock return, trade volume and volatility of the Pakistani banking sector listed in the Karachi Stock Exchange. The study is aimed to take a sample period from Jan 2012 to June 2014. The estimation techniques applied to check the volatility by ARCH and GARCH. To test the relationship between the stock return, trading volume, the technique of VAR applied. The results show the causal relationship between the stock return and the trade volume. The variance equation of the GARCH Model shows the interaction between the trading volume and stock return. The results show that previous day volume has significant effects on the current stock return, it shows that the both the last days return and volume has power to effect the current returns. Keywords: Pakistan Banking Sector, VAR, ARCH-GARCH, Volatility

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Shajar Hussain

Papers

Analysis of Relationship between Stock Return, Trade Volume and Volatility: Evidences from the Banking Sector of Pakistani Market