Asymmetric and time-frequency spillovers among commodities using high-frequency data

Massimiliano Caporin, Muhammad Abubakr Naeem, Muhammad Arif, Mudassar Hasan, Xuan Vinh Vo, Syed Jawad Hussain Shahzad

Research output: Contribution to journalArticlepeer-review

52 Citations (Scopus)

Abstract

In this study, we examine the asymmetric short- and long-run spillover among commodities using realized variances and realized semivariances calculated through 5-min trading data of commodity futures. In doing so, we apply time and frequency domain generalized error variance decomposition approaches and build a network of commodity connectedness. Our findings indicate low inter-group connectedness, distinct group clustering, and high intragroup network-based connectedness in realized volatilities of sample commodities. We find more pronounced inter- and intra-group volatility connectedness for negative realized volatilities than positive ones. Besides, we show that volatility connectedness is a long-run phenomenon. Additionally, the time-varying net directional spillover connectedness reveals that the bad volatility connectedness dictates the good volatility connectedness for the total sample as well as for various frequency domains, both in terms of magnitude and length of time. The implications for investors and policymakers are discussed.

Original languageEnglish
Article number101958
JournalResources Policy
Volume70
DOIs
Publication statusPublished - Mar 2021
Externally publishedYes

Keywords

  • Asymmetric volatility
  • Commodity connectedness
  • High-frequency data
  • Time-frequency domain

ASJC Scopus subject areas

  • Sociology and Political Science
  • Economics and Econometrics
  • Management, Monitoring, Policy and Law
  • Law

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