Interrelationship and Volatility Dynamics Among the Seven Main NYSE Mineral ETFs

Pedro Augusto Streck, Marcelo De Oliveira Passos, Mathias Schneid Tessmann (), Alfrânio Rodrigo Trescher, Daniel De Abreu Pereira Uhr and Maria Laura Marques
Additional contact information
Pedro Augusto Streck: Organizations and Markets Graduate Program, Federal University of Pelotas, Pelotas 96055-630, RS, Brazil
Marcelo De Oliveira Passos: Organizations and Markets Graduate Program, Federal University of Pelotas, Pelotas 96055-630, RS, Brazil
Mathias Schneid Tessmann: Economics and Management School, Brazilian Institute of Education Development and Research (IDP), Brasília 70830-401, DF, Brazil
Alfrânio Rodrigo Trescher: Economics and Management School, Brazilian Institute of Education Development and Research (IDP), Brasília 70830-401, DF, Brazil
Daniel De Abreu Pereira Uhr: Organizations and Markets Graduate Program, Federal University of Pelotas, Pelotas 96055-630, RS, Brazil
Maria Laura Marques: Organizations and Markets Graduate Program, Federal University of Pelotas, Pelotas 96055-630, RS, Brazil

Economies, 2024, vol. 12, issue 12, 1-14

Abstract: This paper aims to investigate the main mineral exchange-traded funds (ETFs) in terms of trading volumes on the New York Stock Exchange by measuring the volatility transmission among them and the connectivity of this market. Daily closing ETF data from 2019 to 2023 for platinum, silver, copper, lead, nickel, gold, and a diversified set of precious metals are considered to estimate a spillover index and apply complex network metrics that identify and cluster the intensity of these relationships. The results indicate that the ETFs that transmit and receive the most volatility in the modeled complex network, in ascending order, are precious metals: gold, silver, and platinum. They are described by the cluster analysis of the modularity optimization process as the group most used for hedging purposes in critical periods. These findings are helpful for the scientific literature about derivatives by bringing empirical evidence from metals markets, supply chain agents, and investors.

Keywords: minerals commodities; ETFs; volatility transmission; complex networks; spillover index (search for similar items in EconPapers)
JEL-codes: E F I J O Q (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7099/12/12/322/pdf (application/pdf)
https://www.mdpi.com/2227-7099/12/12/322/ (text/html)

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:gam:jecomi:v:12:y:2024:i:12:p:322-:d:1530842

Access Statistics for this article

Economies is currently edited by Ms. Hongyan Zhang

More articles in Economies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().