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 Expiration-Day Effects of Index Futures in a Frontier Market: The Case of Ho Chi Minh Stock Exchange

2021 ◽  
Vol 10 (1) ◽  
pp. 3
Author(s):  
Anh Thi Kim Nguyen ◽  
Loc Dong Truong ◽  
H. Swint Friday
Keyword(s):  
Regression Models ◽  
Trading Volume ◽  
Stock Exchange ◽  
Market Volatility ◽  
Market Returns ◽  
Index Futures ◽  
Daily Return ◽  
Market Return ◽  
Index Stock ◽  
Level Of Significance

This study employs OLS, GARCH and EGARCH regression models to test the expiration-day effects of index stock futures on market returns, volatility and trading volume for the Ho Chi Minh Stock Exchange (HOSE). Data used in this study is from a daily return series of the VN30-Index for the period from 10August 2017 through 30 June 2020. The results derived from GARCH(1,1) and EGARCH(1,1) models consistently confirm that Index futures expiration-day effects on market returns exists in the HOSE. Specifically, the average market return for expiration days is significantly lower than other trading days, by 0.13% at the 5% level of significance. However, the results obtained from the regression models indicate that the expiration-day has no impact on market volatility and trading volume.

scholarly journals Macroeconomic Variables and Stock Market Returns in Sri Lanka

2017 ◽  
Vol 9 (2) ◽  
pp. 206
Author(s):  
Saseela Balagobei
Keyword(s):  
Exchange Rate ◽  
Sri Lanka ◽  
Stock Market ◽  
Inflation Rate ◽  
Stock Exchange ◽  
Market Returns ◽  
Stock Market Returns ◽  
Macroeconomic Variables ◽  
Market Return ◽  
Stock Market Return

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.

FIIs herding in energy sector of Indian stock market

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Veena Madaan ◽  
Monica Shrivastava
Keyword(s):  
Stock Market ◽  
Trading Volume ◽  
Driving Forces ◽  
Stock Exchange ◽  
Energy Sector ◽  
Content Type ◽  
Market Return ◽  
Distributed Lag ◽  
The Individual ◽  
Run Test

PurposeThis paper investigates herding behavior and its persistence among foreign institutional investors (FIIs) in the individual stocks of the energy sector of Indian stock exchange by focusing on post turmoil period. The study also examines the relation of herding with the individual return, market return, trading volume and conditional volatility of individual and market return.Design/methodology/approachThe presence of herding is investigated by Lakonishok et al. (1992) model, value-based and count-based herd ratio measure among FIIs in individual stock of energy sector post turmoil period. Further, run test was employed to check the persistency in herding and multivariate distributed lag to investigate the relationship with the market determinant.FindingsThe result indicates the existence of herding in most of the companies and strong persistence in all the companies. The intensity of buy side herding is higher than sell side. Herding and individual return both are significant driving forces of FIIs herding, while trading volume and market volatility in few companies exhibit inverse relationship.Research limitations/implicationsThis study is limited to investigation of energy sector stock.Social implicationsStock market is significantly influenced by FIIs and their propensity to herd may generate instability in the stock market. Therefore, regulatory authority should continuously monitor the flow of fund by FIIs.Originality/valueHerding in the individual stock of the energy sector was not previously performed.

scholarly journals PENGARUH BID ASK SPREAD, VARIANS RETURN, VOLUME PERDAGANGAN , DAN HARGA SAHAM TERHADAP HOLDING PERIOD SAHAM

2019 ◽  
Vol 3 (1) ◽  
pp. 11
Author(s):  
Ida Subaida
Keyword(s):  
Stock Market ◽  
Capital Market ◽  
Stock Price ◽  
Trading Volume ◽  
Stock Exchange ◽  
Financial Assets ◽  
Holding Period ◽  
Bid Ask Spread ◽  
Return Variance ◽  
The Capital Market

The capital market or stock market is a container to bring together sellers and buyers of financial instruments with investment objectives. The existence of the capital market provides a role for various parties such as companies, investors, and even for the national economy. The correct information about the company's shares in the stock market is needed by investors as a decision to buy and sell shares and also for the decision to hold or release ownership of financial assets. The purpose of this study is to analyze and provide empirical evidence about the effect of bid ask spread, return variance, trading volume, and stock price on the holding period of shares in companies listed on the Indonesia Indonesia Stock Exchange which are categorized as LQ45 companies. The research sample was 45 samples in the form of companies listed on the Indonesia Indonesia Stock Exchange which included the LQ45 company category in 2017. Hypothesis testing was done by path analysis using SPSS version 22. The results of the study were bid ask spread, variance return, trading volume, and stock price does not affect the holding period.

Application of CAPM in the Indian Stock Market A Comprehensive Reassessment

2005 ◽  
Vol 1 (2) ◽  
pp. 1-12 ◽  
Author(s):  
Raj S. Dhankar ◽  
Rohini Singh
Keyword(s):  
Stock Market ◽  
Capital Market ◽  
Stock Exchange ◽  
Capital Asset Pricing ◽  
Pricing Model ◽  
Capital Asset ◽  
Asset Pricing Model ◽  
Conflicting Evidence ◽  
Empirical Tests ◽  
Indian Stock Market

There is conflicting evidence on the applicability of Capital Asset Pricing Model in the Indian stock market. Data for 158 stocks listed on the Bombay Stock Exchange was analyzed using a number of tests from 1991–2002, the period which roughly coincides with the period after liberalization and initiation of capital market reforms. Taken in aggregate the various empirical tests show that CAPM is not valid for the Indian stock market for the period studied.

scholarly journals Ramadan Effect and Volatility Risk by Garch Model: Evidence in Indonesia Stock Market

2021 ◽  
pp. 73-82
Author(s):  
Dery Westryananda Putra ◽  
Sri Hasnawati ◽  
Muslimin Muslimin
Keyword(s):  
Stock Market ◽  
Sampling Method ◽  
Stock Exchange ◽  
Garch Model ◽  
Analytical Tool ◽  
Volatility Risk ◽  
Purposive Sampling ◽  
Model Evidence ◽  
The Garch Model

This study aims to analyze the effect of the Ramadan effect and volatility risk on the Indonesian stock market using the GARCH model. The population in this study are companies listed on the LQ45 index on the Indonesia Stock Exchange during 2019. There are 42 companies used as samples in this study. The research sample was taken using purposive sampling method. This study uses the GARCH model as an analytical tool. The results of this study indicate that there is no Ramadan effect on the LQ45 index, but the volatility in the month of Ramadan affects the volatility in the LQ45 index. Keywords: Ramadan Effect, Volatility Risk, GARCH Model Abstrak Penelitian ini bertujuan untuk menganalisis pengaruh Ramadhan effect dan risiko volatilitas terhadap pasar saham Indonesia dengan menggunakan model GARCH. Populasi dalam penelitian ini adalah perusahaan yang terdaftar pada indeks LQ45 di Bursa Efek Indonesia selama tahun 2019. Terdapat 42 perusahaan yang dijadikan sampel dalam penelitian ini. Sampel penelitian diambil dengan menggunakan metode purposive sampling. Penelitian ini menggunakan model GARCH sebagai alat analisis. Hasil penelitian ini menunjukkan bahwa tidak ada pengaruh Ramadhan terhadap indeks LQ45, namun volatilitas pada bulan Ramadhan berpengaruh terhadap volatilitas pada indeks LQ45. Kata Kunci: Ramadhan Effect, Risiko Volatilitas, Model GARCH

scholarly journals Forecasting stock returns on the Amman Stock Exchange: Do neural networks outperform linear regressions?

2021 ◽  
Vol 18 (4) ◽  
pp. 280-296
Author(s):  
Abdel Razzaq Al Rababa’a ◽  
Zaid Saidat ◽  
Raed Hendawi
Keyword(s):  
Stock Market ◽  
Regression Models ◽  
Linear Models ◽  
Stock Exchange ◽  
Market Returns ◽  
Stock Market Returns ◽  
Statistical Measures ◽  
Amman Stock Exchange ◽  
Non Linear ◽  
Ann Models

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).

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