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Research about volatility shock persistence is very important, since it could reflect the risks that can be used to estimate the fluctuations of stock returns in the future. This paper investigates a comparison of the volatility shock persistence sectoral indexes between the consumer goods (CONS) and property-real estate (PROP) sectors, using a sin...
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... the stationary data test was conducted in order to determine whether there was autocorrelation in the data return tested. Table 2, it was found that the JKSE, CONS, and PROP indexes had an ADF absolute value greater than the critical absolute value (5%). Hence, it could be stated that the return data of each index was already stationary. ...
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... The value of a stock can be seen from the stock price. The share price is the nominal value in the proof of ownership of the capital share for a company or limited liability company (Christianti, 2018;Jalari & Marimin, 2020). The stock price is essential to measure the company's performance and as a basis for determining the return and risk in the future. ...
Purpose - This study aims to examine the capital market's reaction to the merger of BUMN Syariah Banks, which is seen as abnormal returns at PT Bank BRI Syariah Tbk.Method - The data for this study were taken ten days before and ten days after announcing the BUMN Sharia Bank merger. The data was processed by paired sample t-test using SPSS.Result - Based on the analysis and discussion results, it shows that there is no market reaction to the announcement of the signing of the BUMN Islamic bank merger on BRIS shares as seen from the abnormal returns before and after the signing of the merger, which there is no significant difference.Implication - This can happen because the world is currently facing the COVID-19 pandemic, which causes market uncertainty. In addition, abnormal returns are not the only indicator to measure the wealth created by an event. Another factor that causes no significant difference in abnormal returns is that the data used in the event window research is daily and short enough to have no visible reaction. Furthermore, the issue of a merger has also been circulating before the announcement of the signingOriginality- This article examines abnormal returns before and after the announcement of the merger of State-Owned Sharia Banks
... The GARCH (1,1)-type models was applied by [20] to Indonesian commodity market, [28] to Indonesian foreign exchange market, [5] to Indonesian stock market, and [15] to Indonesian capital market. [20] examined the predictability of five GARCH-type models, namely ARCH, GARCH, GARCH-M, EGARCH, and TGARCH, for seven primary agricultural commodities in Indonesian export and found that the predictability of the considered models is different for each commodity. ...
... The results show that GARCH (1,1) model provides evidence of volatility clustering for returns from the prices of Indonesian stocks. [15] compared the volatility shock persistence sectoral indexes between the sectors of consumer goods (CONS) and property-real estate (PROP) for the period from January 2010 to December 2015. Due to the volatility shock of both indices moves back to normal stability quite quickly, [15] recommended to the investors who avoid the risk to invest in both sectors. ...
... [15] compared the volatility shock persistence sectoral indexes between the sectors of consumer goods (CONS) and property-real estate (PROP) for the period from January 2010 to December 2015. Due to the volatility shock of both indices moves back to normal stability quite quickly, [15] recommended to the investors who avoid the risk to invest in both sectors. ...
This study proposed two new classes of GARCH(1,1) model by applying the Tukeytransformations to the returns and to the lagged variance. The behavior of return volatility was investigated on the basis of models with normal and Student-t distributions for return error. The competing models were estimated by using the Excel Solver and Matlab tools. The empirical analysis is based on simulated data, daily exchange rates of the IDR/USD, and daily stock indices of FTSE100 and TOPIX. This study recommends the use of Excel Solver for finance academics and practitioners working on volatility using GARCH(1,1) models. Our empirical findings conclude that GARCH(1,1) models under Tukey transformations should be considered in risk management decisions since the models are more appropriate than standard for describing returns and volatility of financial time series and its stylized facts including fat tails and mean reverting. The Tukey transformed returns imply a shorter volatility half-life, and thus this study suggests that investors should invest the observed assets in a shorter time period to obtain higher returns.
