Evidence map›Paper›PMID 37262027›Full record

ArticlePloS one2023

Volatility spillovers across sectors and their magnitude: A sector-based analysis for Australia.

Duc Hong Vo

Abstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Duc Hong VoResearch Centre in Business, Economics & Resources, Ho Chi Minh City Open University, Ho Chi Minh City, Vietnam.ORCID 0000-0001-7823-0349

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

While spillover across equity markets has been extensively investigated, volatility spillover across sectors has largely been under-examined in the current literature. This paper estimates the sectoral volatility using the ARMA-GARCH model and its spillover across Australian sectors on the VAR framework during the 2010-2021 period. We then identify breakpoints in market volatility during the Covid-19 pandemic using a wavelet methodology. We find that volatility spillover across Australian sectors is very significant at 60 per cent from 2010 to 2019, reaching 90 per cent during the Covid-19 pandemic in 2020. The spillover then reverts to its pre-pandemic level in 2021. Consumer Staples and Industrials are the significant risk transmitters, whereas Financials and Real estates are the most significant risk absorbers. Our findings also indicate that Real Estate, Health Care, and Financials record the most significant increase in volatility of more than 300 per cent. Policy implications regarding risk management across Australian sectors have emerged, particularly during extreme events such as the pandemic.

Indexed as

COVID-19AustraliaHealth FacilitiesHumansIndustryPandemics

Identifiers

PMID37262027
PMCPMC10234523

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.