scholarly journals Modelling the Effects of Trading Volume on Stock Return Volatility Using Conditional Heteroskedastic Models

2018 ◽  
Vol 6 (5) ◽  
pp. 193-200
Author(s):  
Edwin Moyo ◽  
Antony Gichuhi Waititu ◽  
Antony Ngunyi
Keyword(s):  
Trading Volume ◽  
Stock Return ◽  
Return Volatility ◽  
Stock Return Volatility

A THRESHOLD MODEL FOR STOCK RETURN VOLATILITY AND TRADING VOLUME

2000 ◽  
Vol 03 (03) ◽  
pp. 467-472 ◽  
Author(s):  
GIULIA IORI
Keyword(s):  
Transaction Costs ◽  
Trading Volume ◽  
Stock Return ◽  
Cross Correlation ◽  
Threshold Model ◽  
Feedback Mechanism ◽  
Return Volatility ◽  
Volatility Clustering ◽  
Stock Return Volatility ◽  
Future Trading

We propose a model with heterogeneous interacting traders which can explain the observed cross-correlation between stock return volatility and trading volume. Transaction costs are introduced which, by responding to price movements, create a feedback mechanism on future trading and generates volatility clustering.

scholarly journals Foreign Ownership, Return Volatility, Trading Volume, and Risk of Stocks in Indonesia

2018 ◽  
Author(s):  
Ahmad Maulin Naufa ◽  
I Wayan Nuka Lantara
Keyword(s):  
Panel Data ◽  
Trading Volume ◽  
Stock Return ◽  
Stock Exchange ◽  
Foreign Ownership ◽  
Return Volatility ◽  
Stock Return Volatility ◽  
Indonesian Government ◽  
The Relationship

This study examines the relationship between foreign ownership and return volatility, trading volume, and risk of stocks at the Indonesia Stock Exchange (IDX). Panel data of selected companies listed on the LQ45 index of the IDX was employed for the period between 2011 and 2017. Foreign ownership was found to positively affect stock return volatility, trading volume, and risk. Hence, more substantial foreign ownership of stocks meant more drawbacks to Indonesian stocks. Therefore, there is a need for the Indonesian government to limit and regulate foreign shareholders in Indonesia.  

scholarly journals Stock Return Volatility And Trading Volume Relationships Captured With Stable Paretian GARCH And Threshold GARCH Models

2012 ◽  
Vol 11 (1) ◽  
pp. 47 ◽  
Author(s):  
Atsuyuki Naka ◽  
Ece Oral
Keyword(s):  
Stock Returns ◽  
Trading Volume ◽  
Stock Return ◽  
Goodness Of Fit ◽  
Garch Models ◽  
Return Volatility ◽  
Font Size ◽  
Gaussian Models ◽  
Stock Return Volatility ◽  
Dow Jones Industrial Average

<span style="font-family: Times New Roman; font-size: small;"> </span><p style="margin: 0in 0.5in 0pt; text-align: justify;" class="MsoNormal"><span style="font-size: 10pt; mso-fareast-language: JA;"><span style="font-family: Times New Roman;">This paper examines the volatility of Dow Jones Industrial Average stock returns and the trading volume by employing stable Paretian GARCH and Threshold GARCH (TGARCH) models. Our results indicate that the trading volume significantly contributes to the volatility of stock returns. Additionally, strong leverage effects exist with negative shocks having a larger impact on volatility than positive shocks. The likelihood ratio tests and goodness of fit support the use of stable Paretian GARCH and TGARCH models over Gaussian models.</span></span></p><span style="font-family: Times New Roman; font-size: small;"> </span>

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