scholarly journals The Sukuk Effect on Stock Return Volatility in Indonesia

2020 ◽  
Vol 3 (2) ◽  
pp. 125-153
Author(s):  
Legina Legina ◽  
Harjum Muharam ◽  
Ahmad Maulin Naufa
Keyword(s):  
Stock Returns ◽  
Trading Volume ◽  
Stock Return ◽  
Sampling Technique ◽  
Return Volatility ◽  
Stock Return Volatility ◽  
Finance Company ◽  
Egarch Model ◽  
Autoregressive Conditional Heteroscedasticity ◽  
Observation Period

The purpose of this research is to examine the effect of the announcement of Sukuk issuance to stock return volatility and to examine the phenomenon of time the varying volatility that occurs in the movement of stock returns and volatility. The data used in this research are daily closing price and trading volume incorporate Sukuk issued during the year 2009-2013 in the D-100 D+100 of Observation period. Samples utilized the purposive sampling technique to obtain the Samples of 13 companies. This study uses EGARCH (Exponential Generalized Autoregressive Conditional Heteroscedasticity) method of analysis. The results show that the best model for each sample in the EGARCH model is different. The results show that the phenomenon of time-varying volatility occurred in 13 samples. From 13 samples, event announcement of the Sukuk issuance does not affect the volatility of stocks returns except for Multi Adira Finance company. Furthermore, the trading volume affects the stock returns volatility on 9 companies, hence do not affect the other four companies.

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>

scholarly journals Contemporaneous Relationship between Trading Volume and Stock Returns Volatility : Evidence from Nepalese Stock Market

2017 ◽  
Vol 10 (1) ◽  
pp. 40-63
Author(s):  
Shivaram Shrestha
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Trading Volume ◽  
Stock Return ◽  
Efficient Market Hypothesis ◽  
Least Square ◽  
Return Volatility ◽  
Monthly Data ◽  
Stock Return Volatility ◽  
Mixture Of Distribution Hypothesis

This paper examines the contemporaneous relation between trading volume and stock returns volatility for Nepalese stock market using monthly data for the period 2005 mid-July to 2017 mid-April. The study uses ordinary least square method and analyzes whether rising price leads to higher volume or vice versa. The study also investigates the association between trading volume and stock returns volatility based on monthly data of NEPSE index and examines the effects of trading volume on stock returns volatility using GARCH (1, 1) model. The study finds positive contemporaneous relationship between trading volume and stock return volatility. The study result indicates that the relationship between trading volume and return volatility is asymmetric. The findings strongly support the hypothesis that higher trading volume is associated with an increase in stock return volatility, but offers little support to the sequential arrival hypothesis and the mixture of distribution hypothesis. Finally, the findings support the weak-form efficient market hypothesis in Nepalese stock market.

scholarly journals Does Sustainability Engagement Affect Stock Return Volatility? Evidence from the Chinese Financial Market

2018 ◽  
Vol 10 (10) ◽  
pp. 3361 ◽  
Author(s):  
Junru Zhang ◽  
Hadrian Djajadikerta ◽  
Zhaoyong Zhang
Keyword(s):  
Stock Returns ◽  
Portfolio Management ◽  
Stock Return ◽  
Return Volatility ◽  
Chinese Stock Market ◽  
Stock Return Volatility ◽  
News Release ◽  
Volatility Persistence ◽  
Google Search ◽  
The Impact

This paper examines the impact of firms’ sustainability engagement on their stock returns and volatility by employing the EGARCH and FIGARCH models using data from the major financial firms listed in the Chinese stock market. We find evidence of a positive association between sustainability engagement and stock returns, suggesting firms’ sustainability news release in favour of the market. Although volatility persistence can largely be explained by news flows, the results show that sustainability news release has the significant and largest drop in volatility persistence, followed by popularity in Google search engine and the general news. Sustainability news release is found to affect positively stock return volatility. We also find evidence that market expectation can be driven by the dominant social paradigm when sustainability is included. These findings have important implications for market efficiency and effective portfolio management decisions.

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.

Capital Gains Taxes and Stock Return Volatility

2013 ◽  
Vol 35 (2) ◽  
pp. 1-31 ◽  
Author(s):  
Zhonglan Dai ◽  
Douglas A. Shackelford ◽  
Harold H. Zhang
Keyword(s):  
Stock Returns ◽  
Stock Return ◽  
Cash Flows ◽  
Capital Gains ◽  
Return Volatility ◽  
Capital Gains Tax ◽  
Tax Rate ◽  
Stock Return Volatility ◽  
Capital Gains Taxes ◽  
The Impact

ABSTRACT This paper presents an empirical investigation of the impact of capital gains taxes on stock return volatility. We predict that the more stock returns are subject to capital gains taxation, the greater the increase in return volatility following a capital gains tax rate cut due to reduced risk-sharing in firms' cash flows between shareholders and the government. Consistent with this prediction, we find larger increases in the return volatility for more appreciated stocks than for less appreciated stocks and for non-dividend-paying stocks than for dividend-paying stocks after both 1978 and 1997 capital gains tax rate reductions. The findings imply that capital gains taxes convey a heretofore overlooked benefit of lower stock return volatility.

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