Evidence map›Paper›PMID 39687181›Full record

ArticleHeliyon2024

AI companies' strategies with traditional vs. digital assets amid geopolitical and banking crises.

Wael Dammak, Mohamed Fakhfekh, Hind Alnafisah, Ahmed Jeribi

Abstract read
In one paragraph

Article in Heliyon, 2024. 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

4 authors.

Wael DammakEslsca Business School-CERFIM, Paris, France.
Mohamed FakhfekhHigher Institute of Business Administration of Sfax, Tunisia.
Hind AlnafisahDepartment of Economics, College of Business Administration, Princess Nourah bint Abdulrahman University, P.O.Box 84428, Riyadh, 11671, Saudi Arabia.
Ahmed JeribiFaculty of Economics and Management of Mahdia, Tunisia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The financial industry evolves rapidly, offering numerous opportunities but also introducing inherent risks that require careful navigation by institutions. This paper explores the performance of traditional and digital assets as tools for hedging, diversification, and safe-haven strategies during the Russian-Ukrainian crisis and the Silicon Valley Bank (SVB) collapse. Utilizing daily data from April 30, 2021, to September 15, 2023, and employing the Asymmetric Dynamic Conditional Correlation (ADCC) model, which combines four Generalized Autoregressive Conditional Heteroskedasticity (GARCH) family models and two residual distributions, we conduct a comprehensive analysis. The results indicate that Bitcoin's role as a safe haven is limited during the geopolitical crisis, impacting specific stocks, while gold's effectiveness varies. Digix Gold (DGX) demonstrates robust safe-haven properties, and Paxos Gold (PAXG) proves notably effective for certain stocks. Before the SVB crisis, gold primarily acts as a diversifier but later emerges as a significant safe haven during the banking crisis. These findings provide valuable insights to portfolio managers, emphasizing the importance of adaptive asset allocation in addressing financial uncertainties.

Indexed as

CrisesDigital assetsHedgingIntelligence artificial companiesSafe havenTraditional assets

Identifiers

PMID39687181
PMCPMC11647844

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.