COVID-19 and China commodity price jump behavior: An information spillover and wavelet coherency analysis.

Xingyu Dai, Matthew C Li, Ling Xiao, Qunwei Wang

Open access · greenAbstract read

In one paragraph

Article in Resources policy, 2022. 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

4.9field-weighted citation impact, top 5% of its field

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, 21 citations in OpenAlex.

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 at 2 institutions in 2 countries.

Xingyu DaiCollege of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, China.

Matthew C LiRoyal Holloway University of London, Egham, TW20 0EX, United Kingdom.

Ling XiaoRoyal Holloway University of London, Egham, TW20 0EX, United Kingdom.

Qunwei WangCollege of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, China.

Nanjing University of Aeronautics and Astronautics · CNRoyal Holloway University of London · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Jumps in commodity prices can make asset risk management challenging. This study explores the influence feature of the COVID-19 epidemic on China's commodity price jumps, using 5-min intraday high-frequency futures data of three China's commodity markets (energy, chemical, and metal) from January 23, 2020 to June 10, 2022. We find that firstly the information spillover from the COVID-19 spread situation to China's energy price jumps is relatively weak, and the COVID-19 epidemic shows the most substantial jump information spillover pattern to China's chemical price. The information spillover pattern is time-varying across the COVID-19 spread situation phase. Secondly, there are co-movement patterns between China's commodity price and China/global COVID-19 confirmed cases. This co-movement feature mainly occurs at the medium- or long-run time scales, and varies across commodities. Thirdly, the demand elasticity for China's commodities and its dependence on imports and exports are the main factors influencing the sensitivity of its price jumps to the COVID-19 outbreak.

Indexed as

Commodity market pricesCOVID-19High-frequency dataInformation spilloverPrice jumpsWavelet coherency

Identifiers

PMID36249416

DOI10.1016/j.resourpol.2022.103055

PMCPMC9550664

OpenAlexW4304172673

What OpenQuestion holds

Textmetadata

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.