2019
DOI: 10.1016/j.resourpol.2019.02.013
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Can alternative hedging assets add value to Islamic-conventional portfolio mix: Evidence from MGARCH models

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Cited by 38 publications
(15 citation statements)
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“…Previous studies apply a variety of methods that mostly involve generalized autoregressive conditional heteroskedasticity (GARCH)-based models and conditional correlation (e.g. Basher and Sadorsky, 2016; Raza et al, 2019) while considering the aggregate level of equity indices. However, the use of aggregate equity indices masks the relationship at the sectoral level and thus potential heterogeneity in hedging inferences.…”
Section: Related Studiesmentioning
confidence: 99%
“…Previous studies apply a variety of methods that mostly involve generalized autoregressive conditional heteroskedasticity (GARCH)-based models and conditional correlation (e.g. Basher and Sadorsky, 2016; Raza et al, 2019) while considering the aggregate level of equity indices. However, the use of aggregate equity indices masks the relationship at the sectoral level and thus potential heterogeneity in hedging inferences.…”
Section: Related Studiesmentioning
confidence: 99%
“…The ADCC-GARCH method allows asymmetric effects in conditional variants and conditional correlations to increase over time as well as lower diversification during volatile conditions (Gjika & Horváth, 2013). Raza et al (2019) show that the ADCC-GARCH analysis technique with alternative gold assets can provide a better diversification effect and return. Thus, this research also aims to compare the performance formed between the DCC-GARCH and ADCC-GARCH analysis techniques, because the ADCC-GARCH analysis technique is considered better.…”
Section: H1b: Portfolios Formed By the Adcc-garch Analysis Technique ...mentioning
confidence: 92%
“…Therefore, gold can be included in the formation of a dynamic portfolio which is still rarely studied in Indonesia. In addition, portfolios using asset classes with different values can produce better returns (Raza et al 2019).…”
Section: Introductionmentioning
confidence: 99%
“…FFR influence can be reflected by the US 3-month T-bill rate (Yang & Hamori 2014). Several studies show that the Islamic stock market volatility increases during a crisis due to various macroeconomic factors, such as the instability of the US 10-year T-bond yield (Shahzad et al 2020, Haddad et al 2020, US Uncertainty Index (UCT) (Nazlioglu et al 2015), and the fluctuation of the Chicago Board Options Exchange Volatility Index (CBOE VIX) (Raza et al 2019).…”
mentioning
confidence: 99%
“…Another macroeconomic factor is the Chicago Board Options Exchange Volatility Index (CBOE VIX), an indicator of market volatility and investors' risk-aversion level. CBOE VIX is known to have a negative correlation and low spillover effect on the Asia-Pacific Islamic stock market (Raza et al 2019).…”
mentioning
confidence: 99%