scholarly journals Price-Volume Granger Causality Tests in the Egyptian Stock Exchange (EGX)

2019 ◽  
Vol 8 (3) ◽  
pp. 48
Author(s):  
Kobana Abukari ◽  
Tov Assogbavi
Keyword(s):  
Trading Volume ◽  
Stock Exchange ◽  
Price Change ◽  
Wall Street ◽  
Diffusion Of Information ◽  
Bull Markets ◽  
Volume Relationship ◽  
Causality Tests ◽  
Sequential Information ◽  
Egyptian Stock Exchange

Using weekly Egyptian stock exchange data on the 34 most active companies stretching from 2011 to 2017, this study finds that price changes Granger cause trading volume up to 8 weeks (lags), supporting the sequential information arrival model in the EGX. We also find a robust contemporaneously positive asymmetric relationship between price change and trading volume, confirming two well-documented characteristics of the price-volume relationship as well as two major adages of Wall Street: “it takes volume to move prices” and “volume in bull markets is heavier than volume in bear markets”. Overall, our results imply that although there is some sequential diffusion of information, the EGX’s efforts at improving its microstructure through initiatives such as the 2009 Presidential Degree on structure and governance, appear to have helped in improving instantaneous access to information – as exemplified by our evidence of strong contemporaneous positive price-volume relationship.

scholarly journals The Price-Trading Volume Relationship in the Brazilian Stock Market, the Impact of Stock Lending and a Role for Technical Analysis

2015 ◽  
Vol 13 (4) ◽  
pp. 631
Author(s):  
Antonio Zoratto Sanvicente ◽  
Antonio Zoratto Sanvicente ◽  
Antonio Zoratto Sanvicente
Keyword(s):  
Stock Market ◽  
Trading Volume ◽  
Price Change ◽  
Absolute Value ◽  
Daily Data ◽  
Volume Relationship ◽  
Current Price ◽  
The Impact ◽  
The Relationship ◽  
Positive Covariance

We examine the relationship between price and volume in the Brazilian stock market. It tests the “V-shaped relationship” developed by Karpoff (1987), identified in several empirical papers for the U.S. market. This is expressed by positive covariance between a stock’s market turnover and the absolute value of that stock’s price change in the same period. This would contradict the implication from weak market efficiency that current price would impound all information. We analyze daily data for 47 stocks covering the period from January 04, 2010 to June 28, 2013. The results indicate that the V-shaped relationship is significant.

scholarly journals Type of Traders’ Effect on Risk and Return: The Case of Egyptian Stock Exchange

2016 ◽  
Vol 8 (2) ◽  
pp. 256
Author(s):  
Aly Saad Mohamed Dawood ◽  
Khairy El-Giziry
Keyword(s):  
Stock Market ◽  
Capital Market ◽  
Trading Volume ◽  
Stock Exchange ◽  
Garch Model ◽  
Market Returns ◽  
Market Values ◽  
Market Return ◽  
Lag Structure ◽  
Egyptian Stock Exchange

<p>This research paper aims to estimate the effect of investor categories (Foreigners, Arab, Egyptian institutions and individuals) trading volume, value and number of transactions on capital market returns and volatility.  </p><p>We depend on data Foreigners, Arabian and Egyptian trading volume, values and number of transaction of buying and selling for institutions and individuals and capital market values for the period from January 1st 2009 to December 31 2013.</p><p>We used descriptive statistics to identify normal distribution of data. Then, performing lead lag structure approach to obtain the optimum lag for the independent variable which has the maximum correlation with the dependent variable. Next, Garch model utilized to estimate the effect of trading volume, value, number of transactions on capital market return and volatility. Finally, the same model utilized to estimate the effect of investor categories on capital market return and volatility for the six periods starting from January 1<sup>st</sup> 2009 to December 31 2013 which represents the whole period and five yearly periods for the same period.</p><p>We found that institutions are the main source of volatility in the Egyptian stock market. Garch models showed weak effect on volatility for all periods. In the light of this study Foreigners and trading value items are the main source of effect on volatility. Finally, consistent with Chou (1988), the findings of GARCH model indicated that volatility persistence is less than unity which revealed that the Egyptian stock market could absorb shocks across time.</p>

scholarly journals Integration of Financial Markets: A Study of Egypt and Palestine Stock Markets

2016 ◽  
Vol 3 (1) ◽  
pp. 1
Author(s):  
Abdul Razak Abdul Hadi ◽  
Shadi Hamad ◽  
Eddy Yap Tat Hiung
Keyword(s):  
Financial Markets ◽  
Time Series Data ◽  
Stock Exchange ◽  
Series Data ◽  
Impulse Response Functions ◽  
Estimation Model ◽  
Dynamic Interactions ◽  
Causality Tests ◽  
Dynamic Relations ◽  
Egyptian Stock Exchange

The objective of this study is to determine the existence of equilibrium and dynamic relations between Egyptian Stock Exchange (EGX) and Palestine Stock Exchange (PEX). Utilising the framework of international trade theories, this paper employs the Engle-Granger Co-integration (1987) procedure as an estimation model on monthly time series data from February 1998 to April 2012. Results indicate that there is a significant equilibrium nexus between EGX and PEX but no empirical evidence was found on the existence of dynamic relations between them via Granger Causality tests. However, analysis of dynamic interactions of the post-sample period by means of Impulse-Response Functions and Variance Decomposition indicate sensitivity in EGX towards changes in PEX.

scholarly journals Investment Strategies, Trading Information And Option Market: Evidence From The Toronto Stock Exchange

2011 ◽  
Vol 8 (12) ◽  
Author(s):  
Tov Assogbavi ◽  
Siméon Fagnissè
Keyword(s):  
Trading Volume ◽  
Stock Exchange ◽  
Price Change ◽  
Seemingly Unrelated Regression ◽  
Investment Strategies ◽  
Option Markets ◽  
Toronto Stock Exchange ◽  
Equity Issues ◽  
Option Trading ◽  
Option Market

This paper empirically investigates the relationship between equity price change and volume in order to determine the extent to which option trading affects the absolute price?volume relationship. The analysis is based on Zellner's 'Seemingly Unrelated Regression, (SUR) method shows that, on average, the trading volume of option eligible equity issues is less sensitive to price changes than the volume of equity issues without options. This result supports the hypothesis (Ross, 1976) that investors may be more inclined to turn to the option market rather than acting directly on the securities in order to carry out their different investment strategies on the stock market. A direct implication of this finding suggests that investment strategies that use both volume and price change to make inferences for investment decisions have to integrate, at least when dealing with an option eligible equity, both stock and option markets into their analysis.

scholarly journals Equity Price-Volume Relationship On The Russian Stock Exchange

2011 ◽  
Vol 6 (9) ◽  
Author(s):  
Tov Assogbavi ◽  
Jennifer Schell ◽  
Siméon Fagnissè
Keyword(s):  
Stock Price ◽  
Stock Exchange ◽  
Price Change ◽  
Investment Strategies ◽  
Weak Support ◽  
Volume Relationship ◽  
Valuation Process ◽  
Equity Price ◽  
Relationship Of ◽  
Auto Regression

This paper analyses the stock price?volume relationship of individual equities in the Russian Stock Exchange. Using a vector auto-regression analysis on weekly data, we present a strong evidence of bi-directional relationship between volume and price change. This finding confirms the evidence reported by studies on many developed markets. However, the weak support for the positive price-volume relationship may imply that the differences in institutions and information flows in the Russian Stock Exchange might be important enough to affect the valuation process of their securities. Consequently, investors who based their investment strategies on momentum, have to adjust their strategies when trading on Russian Stock Markets.

Statistical characteristics of price impact in high-frequency trading

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Can Jia ◽  
Tianmin Zhou ◽  
Handong Li
Keyword(s):  
High Frequency ◽  
Trading Volume ◽  
Stock Exchange ◽  
Price Change ◽  
Price Impact ◽  
High Frequency Trading ◽  
Statistical Characteristics ◽  
Long Term Memory ◽  
Time Interval ◽  
Trade Volume

AbstractTrading volume changes based on market microstructure will impact asset prices, which will lead to transaction price changes. Based on the extended Hasbrouck–Foster–Viswanathan (HFV) model, we study the statistical characteristics of daily permanent price impact and daily temporary price impact using high-frequency data from Chinese Stock Markets. We estimate this model using tick-by-tick data for 16 selected stocks that are traded on the Shanghai Stock Exchange. We find the following: (1) the time series of both the permanent price impact and temporary price impact exist in stationarity and long-term memory; (2) there is a strong correlation between the permanent price impact among assets, while the correlation coefficient of the temporary price impact is generally weak; (3) the time interval has no significant influence on the trade volume and the price change at the tick frequency, which means that it is not necessary to take into account the time interval between adjacent transaction in high-frequency trading; and (4) the bid-ask spread is an effective factor to explain trading price change, but has no significant impact on trade volume.

scholarly journals The Price-Volume Relationship In The Chilean Stock Market

2011 ◽  
Vol 7 (10) ◽  
Author(s):  
Ravindra R. Kamath
Keyword(s):  
Stock Price ◽  
Trading Volume ◽  
Price Index ◽  
Stock Exchange ◽  
Equity Market ◽  
Test Results ◽  
Volume Changes ◽  
Causality Test ◽  
Volume Relationship ◽  
Daily Returns

This study focuses on the econometric relations between daily returns and daily trading volume changes on the Santiago Stock Exchange of Chile. To meet this task, the study utilizes the data of the Selective Stock Price Index, IPSA, from January, 2003 through October, 2006. A significant contemporaneous relation is found between volume and returns. The evidence also indicates that the said relation is asymmetric. Moreover, the results support the notion that the trading volume makes the market move. The causality test results provide a clear evidence of daily returns Granger causing daily trading volume changes in the Chilean equity market.

Uji Komparasi Abnormal Return, Trading Volume, Trading Frequency, Dan Bid-Ask Spread Sebelum Dan Sesudah Share Split

2016 ◽  
Vol 8 (2) ◽  
pp. 24-45
Author(s):  
Tania Hayu Safira ◽  
Febryanti Simon
Keyword(s):  
Abnormal Return ◽  
Trading Volume ◽  
Stock Exchange ◽  
Distributed Data ◽  
Trading Frequency ◽  
Bid Ask Spread ◽  
Analysis Technique ◽  
Before And After ◽  
Test Of Hypothesis ◽  
Kolmogorov Smirnov

This study is event study that was conduct to examine the differences of abnormal return, trading volume, trading frequency and bid-ask spread before and after the events of share split. The object of this research is the companies that did share split and listed in Indonesia Stock Exchange in 2008 - 2015. The samples are 30 companies chosen by purposive sampling method. The criteria are the company did not do corporate action right issue, pre-emptive rights, a share dividend and bonus shares in the same year with share split. Event window used in this study was 30 days consisting of 15 days before and 15 days after the share split. Data analysis technique begins with a test of normality using Kolmogorov – Smirnov and transform for unnormally distributed data. Then, test of hypothesis using Paired t – test to compare the differences before and after share split. The results of this study showed that volume trading activity and trading frequency had significant differences before and after the share split. While, variable abnormal return and bid-ask spread had not significant differences before and after the share split. Keywords: Abnormal return, bid-ask spread, share split, trading frequency, trading volume.

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