经济
计量经济学
波动性(金融)
库存(枪支)
金融经济学
社会联系
ARCH模型
心理学
机械工程
工程类
心理治疗师
作者
Karel Janda,Ladislav Krištoufek,Binyi Zhang
标识
DOI:10.1016/j.eneco.2022.105911
摘要
This paper aims to empirically investigate the dynamic connectedness between oil prices and stock returns of clean energy-related and technology companies in China and U.S. financial markets. We apply three multivariate GARCH model specifications (CCC, DCC and ADCC) to investigate the return and volatility spillovers among price and return series. We use rolling window analysis to forecast out-of-sample one-step-ahead dynamic conditional correlations and time-varying optimal hedge ratios. Our results suggest that Invesco China Technology ETF (CQQQ) is the best asset to hedge Chinese clean energy stocks followed by WTI, ECO, and PSE. Our results are reasonably robust to the choice of different model refits and forecast length of rolling window analysis. Our empirical findings provide investors and policymakers with the systematic understanding of return and volatility connectedness between China and U.S. clean energy stock markets.
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