Evidence map›Paper›PMID 40163455›Full record

ArticlePloS one2025

Asymmetric spillover connectedness between clean energy markets and industrial stock markets: How uncertainties affect it.

Ailing Li, Bingmao Zhong

Abstract read
In one paragraph

Article in PloS one, 2025. 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

2 authors.

Ailing LiSchool of Finance, Harbin University of Commerce, Harbin, China.ORCID 0009-0007-3973-3876
Bingmao ZhongSchool of Finance, Harbin University of Commerce, Harbin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As the global climate crisis intensifies, clean energy is becoming increasingly important, and the intrinsic link between industry and energy highlights the connectedness between the industrial stock market and the clean energy market, and examining this connectedness can reveal risk spillovers between these markets. We categorise the clean energy market into hydro, wind and solar markets, and the industrial stock market into low-carbon portfolios, high-carbon portfolios and ordinary portfolios, and use the network connectedness methodology to investigate the connectedness of returns between the clean energy submarkets and the industrial stock submarkets in the time and frequency domains. The returns are categorised into positive and negative returns in order to investigate the asymmetry in the connectedness of the markets. Finally, we explore the effects of EPU, GPU, and CPU in terms of network connectedness. It is revealed that clean energy submarkets are net receivers of risk, industrial stock submarkets are risk transmitters. The hydropower market is the main risk receiver, while the low-carbon portfolio is the main risk transmitter. Risk spillovers are mainly driven by short-term spillovers and do not have persistent spillover transmission. Bad news has a greater impact on network connectedness, leading to higher levels of connectedness between markets. EPU and CPU have significant effects on network connectedness. Our findings are informative for both investors and policymakers.

Indexed as

CommerceIndustryInvestmentsUncertainty

Identifiers

PMID40163455
PMCPMC11957356

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.