2018
DOI: 10.1016/j.qref.2018.05.001
|View full text |Cite
|
Sign up to set email alerts
|

Volatility spillovers across global asset classes: Evidence from time and frequency domains

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

16
66
1
4

Year Published

2018
2018
2024
2024

Publication Types

Select...
9
1

Relationship

3
7

Authors

Journals

citations
Cited by 132 publications
(87 citation statements)
references
References 45 publications
16
66
1
4
Order By: Relevance
“…Liu et al [31] examine the spillovers of return and volatility from fossil fuel energies (crude oil, coal, natural gas) to electricity spot and three electricity futures in Europe using the same time-frequency domain frameworks. Tiwari et al [32] examine the volatility spillovers among four global assets, including currency, credit default swaps, sovereign bonds, and stocks, using the Diebold-Yilmaz approach and Barunik and Krehlik method.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Liu et al [31] examine the spillovers of return and volatility from fossil fuel energies (crude oil, coal, natural gas) to electricity spot and three electricity futures in Europe using the same time-frequency domain frameworks. Tiwari et al [32] examine the volatility spillovers among four global assets, including currency, credit default swaps, sovereign bonds, and stocks, using the Diebold-Yilmaz approach and Barunik and Krehlik method.…”
Section: Literature Reviewmentioning
confidence: 99%
“…For corresponding studies on co-movements in gold and oil returns, see References [14][15][16][17], and references cited therein. A literature review on return and volatility spillovers across asset classes can be found in Reference [18].…”
Section: Introductionmentioning
confidence: 99%
“…are used. SeeCreal et al (2013) for details.5 Before moving into our discussion of the findings, it must be highlighted that the outlined spillover estimation framework is due toBarunik & Krehlik (2018) and seems to be gaining popularity in relevant literature (see e.g.,Corbet et al, 2018;Lau et al, 2017;Tiwari et al, 2018). Spillover estimation byBarunik & Krehlik (2018) is closely related to the framework ofDiebold & Yilmaz (2012) and can be regarded as an extension of the latter.…”
mentioning
confidence: 99%