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Normal and extreme interactions among nonferrous metal futures: A new quantile-frequency connectedness approach
Finance Research Letters ; 47:102855, 2022.
Article in English | ScienceDirect | ID: covidwho-1778129
ABSTRACT
Nonferrous metal markets are wildly discussed for their ultimate importance in industry production. However, the interactions among major international nonferrous metal futures, especially their extreme connectedness at different time frequencies (horizons), are rarely recognized. This paper investigates the normal and extreme interactions at various time frequencies among twelve major international nonferrous metal futures traded in LME and SHFE by proposing a new quantile-frequency connectedness measurement, which combines the quantile connectedness approach of Ando et al. (2018) and frequency connectedness method of Barunik and Krehlik (2018). The main empirical results show that, firstly, these major nonferrous metal futures maintain very tight total connectedness no matter in normal or extreme conditions, and the extreme left- and right-tail connectedness measures are larger than the one at normal case. Secondly, there is no clear difference between the extreme downside (left-tail) and upside (right-tail) total connectedness in both time and frequency domains. Thirdly, the total and net connectedness effects of these nonferrous metal futures are mainly centered in short-term frequency at both normal and extreme quantiles. Fourthly, the dynamic analysis indicates that the total connectedness among these futures are very stable throughout the data sample, even during the recent COVID-19 pandemic. Finally, these nonferrous metal futures play quite different roles in net connectedness effects across various quantiles and time frequencies.
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Full text: Available Collection: Databases of international organizations Database: ScienceDirect Language: English Journal: Finance Research Letters Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: ScienceDirect Language: English Journal: Finance Research Letters Year: 2022 Document Type: Article