Time-frequency higher-order moment Co-movement and connectedness between Chinese stock and commodity markets

Huiming Zhu, Xiling Xia, Liya Hau, Tian Zeng and Xi Deng

International Review of Economics & Finance, 2024, vol. 96, issue PA

Abstract: This study examines the higher-order moment co-movement and connectedness between China's stock and commodity markets across time and frequency domains. We propose wavelet decomposition to develop a multiscale time-varying parameter vector autoregression (TVP-VAR) approach for measuring higher-order moment connectedness. Our empirical findings are as follows: First, the co-movement of stock-commodity varies over time and across different frequencies, exhibiting heterogeneity at different moments. Stocks demonstrate robust co-movement with commodities over the medium- and long-term periods. Second, higher-order moment connectedness is stronger than return connectedness, whereas weaker than volatility connectedness. Finally, higher-order moment connectedness is highly event-dependent, peaking at COVID-19 onset. And long-run factors have the greatest effect on dynamic moment connectedness.

Keywords: Time-frequency co-movement; Connectedness; Higher-order moment; Stock-commodity; China (search for similar items in EconPapers)
JEL-codes: C22 C58 G15 (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1059056024005720
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:reveco:v:96:y:2024:i:pa:s1059056024005720

DOI: 10.1016/j.iref.2024.103580

Access Statistics for this article

International Review of Economics & Finance is currently edited by H. Beladi and C. Chen

More articles in International Review of Economics & Finance from Elsevier
Bibliographic data for series maintained by Catherine Liu ().