伊斯兰债券和伊斯兰股票的最佳对冲比率:一种新方法

Q2 Economics, Econometrics and Finance
Bayu Adi Nugroho, Dewi Fiscalina Kusumawardhani
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引用次数: 0

摘要

本文提出了一种计算套期保值比率的新模型。具体而言,该模型修正了指数加权移动平均法的波动率预测,以考虑收益的肥尾分布。这个简单的模型旨在克服复杂GARCH模型众所周知的缺点,即需要较长的日回报周期来确保模型的收敛性。这些数据是伊斯兰交易所交易基金:SP基金道琼斯全球伊斯兰债券ETF, Wahed富时美国伊斯兰教法ETF和iShares MSCI新兴市场伊斯兰UCITS ETF。在动荡时期,伊斯兰债券起到了分散投资的作用,因为它们与伊斯兰股票呈正相关,而且它们的波动性小于伊斯兰股票。这项工作还实现了广泛使用的方法,如动态等相关garch, GO-GARCH,不对称DCC-GARCH, naïve方法和线性回归。采用两种形式的数据分割和滚动窗口分析来减少数据挖掘的偏差。所有模型都能提前一步预测对冲比率。利用小波变换的收益和包含第三阶矩和第四阶矩的效用分析,所提出的模型比竞争模型具有更好的性能。不管不同的对冲工具(贵金属)和资产类别,结果都是一样的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
OPTIMAL HEDGE RATIO OF SUKUK AND ISLAMIC EQUITY: A NOVEL APPROACH
This research applies a novel model to compute a hedge ratio. Specifically, the model modifies volatility forecasts of an exponentially weighted moving average method to account for the fat-tailed distribution of returns. This simpler model aims to overcome the widely-known drawback of the complex GARCH models that a long daily return period is required to ensure the model’s convergence. The data are Islamic exchange-traded funds: SP Funds Dow Jones Global Sukuk ETF, Wahed FTSE USA Shariah ETF, and iShares MSCI EM Islamic UCITS ETF. Sukuk act as a diversifier over the turmoil period since they are positively correlated with Islamic equity and their volatility is less than that of Islamic equity. This work also implements widely-used methods such as Dynamic Equicorrelation-GARCH, GO-GARCH, asymmetric DCC-GARCH, naïve approach, and linear regression. Two forms of data splitting and a rolling-window analysis are carried out to reduce data mining bias. All models generate one-step ahead forecasts of hedge ratios. Applying wavelet-transformed returns and utility analysis incorporating third and fourth moments, the proposed models produce better performance than the competing models. The results remain the same irrespective of different hedging instruments (precious metals) and asset classes.
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来源期刊
CiteScore
1.90
自引率
0.00%
发文量
19
审稿时长
24 weeks
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