Evidence map›Paper›PMID 37192900›Full record

ArticleFinancial innovation2023

Tail spillover effects between cryptocurrencies and uncertainty in the gold, oil, and stock markets.

Walid Mensi, Mariya Gubareva, Hee-Un Ko, Xuan Vinh Vo, Sang Hoon Kang

Abstract read
In one paragraph

Article in Financial innovation, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

5 authors.

Walid MensiDepartment of Economics and Finance, College of Economics and Political Science, Sultan Qaboos University, Muscat, Oman.
Mariya GubarevaUniversidade de Lisboa, Lisbon School of Economics and Management (ISEG), Research Centre in Economic and Organisational Sociology (SOCIUS) / Research in Social Sciences and Management (CSG), Rua Miguel Lupi 20, 1249-078 Lisbon, Portugal.
Hee-Un KoKorea Housing and Urban Guarantee Corporation, Busan, Korea.
Xuan Vinh VoInstitute of Business Research and CFVG, University of Economics Ho Chi Minh City, Ho Chi Minh City, Vietnam.
Sang Hoon KangPNU Business School, Pusan National University, Busan, Republic of Korea.ORCID 0000-0002-1236-136X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study investigates tail dependence among five major cryptocurrencies, namely Bitcoin, Ethereum, Litecoin, Ripple, and Bitcoin Cash, and uncertainties in the gold, oil, and equity markets. Using the cross-quantilogram method and quantile connectedness approach, we identify cross-quantile interdependence between the analyzed variables. Our results show that the spillover between cryptocurrencies and volatility indices for the major traditional markets varies substantially across quantiles, implying that diversification benefits for these assets may differ widely across normal and extreme market conditions. Under normal market conditions, the total connectedness index is moderate and falls below the elevated values observed under bearish and bullish market conditions. Moreover, we show that under all market conditions, cryptocurrencies have a leadership influence over the volatility indices. Our results have important policy implications for enhancing financial stability and deliver valuable insights for deploying volatility-based financial instruments that can potentially provide cryptocurrency investors with suitable hedges, as we show that cryptocurrency and volatility markets are insignificantly (weakly) connected under normal (extreme) market conditions.

Indexed as

Cross-quantilogramCryptocurrencyQuantile spilloverUncertainty indices

Identifiers

PMID37192900
PMCPMC10154763

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.