Cross-correlations between economic policy uncertainty and precious and industrial metals: A multifractal cross-correlation analysis

Aslam, Faheem; Zil-e-huma,; Bibi, Rabia; Ferreira, Paulo

doi:10.1016/j.resourpol.2021.102473

Cited by 28 publications

(10 citation statements)

References 79 publications

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“…Herding behavior may play a substantial role in explaining the movement of commodity prices, according to some researchers. As an instance, Fasanya et al (2021) discover that 24 Chinese commodities exhibit positive response business, noisy business, and a steer mentality; on the other hand, Aslam et al (2022) show that steering behavior varies between markets and it is asymmetric. The bottom line is that, in earlier studies, commodities were shown to interact significantly with other asset classes and to be a fence and safe-like haven for other asset categories under certain conditions.…”

Section: Commodity Markets and Effect Of Covid-19mentioning

confidence: 99%

RETRACTED ARTICLE: Economic policy uncertainty and commodity market volatility: implications for economic recovery

Xiao

Ayub

2022

Environ Sci Pollut Res

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As a consequence of the COVID-19 pandemic outbreak, most commodities experienced significant price drops, which were expected to continue well into 2020. As a result, the Markov switching model is used to study the influence of policy uncertainty and the COVID-19 pandemic on commodity prices in the USA. Commodity markets are stimulated by economic policy uncertainty, according to results from a two-state Markov switching model. In both high and low regimes, economic policy uncertainty (EPU) influences the commodity market, according to the study's findings. However, in the high regime, EPU has a greater influence on the energy and metal sectors. EPU has different influences on commodity markets in highand low-volatility regimes, according to this study. There is a wide range of correlations between COVID-19 outcomes and EPU and how the prices of natural gas, oil, corn, silver, soybean, copper, gold, and steel respond to these tremors, in both high-and low-volatility tenure. Oil and natural gas, on the other hand, are unaffected by shifts in COVID-19 death rates under either regime. Results show that in both high-and low-volatility regimes, the demand and supply for most commodities are responsive to historical prices.

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Section: Commodity Markets and Effect Of Covid-19mentioning

confidence: 99%

RETRACTED ARTICLE: Economic policy uncertainty and commodity market volatility: implications for economic recovery

Xiao

Ayub

2022

Environ Sci Pollut Res

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“…Furthermore, stock return may explain copper price return and vice versa, generating another endogeneity problem. There is also evidence that confirm that EPU and copper markets are interlinked (Aslam et al, 2022). There is a need to solve these problems since ignoring them will lead to biased and inefficient estimates (Wintoki et al, 2012).…”

Section: Methodsmentioning

confidence: 99%

How does China economic policy uncertainty (EPU) impact copper-firms stock returns and copper prices returns?

Maquieira

Flores

Espinosa

2023

ARLA

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PurposeThis study focuses on how China EPU may impact copper-firms stock returns and also how China EPU mediates between stock returns and copper prices returns.Design/methodology/approachThe sample consists of 44 copper firms from January 2011 to March 2022. The study also considers a subsample of 29 net-exporters countries. Panel data methodology is used, allowing to control for unobservable heterogeneity and endogeneity problems. The equations are estimated through a dynamic panel using the generalized methods of moments (GMM).FindingsChina EPU has a negative and statistically significant relationship with stock returns. Copper price returns are positively associated with stock returns. This research also considers two scenarios: high and low levels of China EPU. For high levels of China EPU states it is reported a negative relationship between stock returns and China EPU and copper price returns show a positive relationship with stock returns.Research limitations/implicationsThere is need to explore other metals for what China exhibits a high demand and observe if China EPU and Global EPU have similar impacts on stock returns. It will be useful to identify main firm's consumers of copper and these other metals to explore the relationship between EPU and stock returns.Originality/valueTo the best of the authors’ knowledge, this is the first paper that analyzes China EPU index and its impact on both copper-firms stocks returns and on changes in copper prices. This is done using all public copper firms worldwide.

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“…Several nonlinearly interacting factors make up the complex systems of physical quantities, such as biological, ecological, technological, financial, as well as social, and they all have been shown to exhibit long-range correlations. Recent research aimed to shed light on the internal dynamics of these cross-correlations that occur in numerous simultaneously recorded time series (Aslam et al 2022;Podobnik et al 2009;Y. Shi et al 2020a, b;Waţorek et al 2019;Xiong et al 2018;Zhao and Cui 2021).…”

Section: Multifractal Detrended Analysis Methodsmentioning

confidence: 99%

“…Since the development of multifractal detrended crosscorrelation analysis (MF-DCCA, or called MF-DXA) by Zhou (2008) reveal the multifractal features of two cross-correlated signals, DCCA and MF-DCCA have been widely discussed and used (Aslam et al 2022;Jafari et al 2007;Jiang and Zhou 2011;Kristoufek 2011;Zou and Zhang 2020).…”

Section: Multifractal Detrended Analysis Methodsmentioning

confidence: 99%

On the inner dynamics between Fossil fuels and the carbon market: a combination of seasonal-trend decomposition and multifractal cross-correlation analysis

Aslam

Ali

Amjad

et al. 2022

Environ Sci Pollut Res

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This study examines the inner dynamics of multifractality between the carbon market (EU ETS) and four major fossil fuel energy markets: Brent Crude Oil (BRN), Richards Bay Coal (RBC), UK Natural Gas (NGH2), and FTSE350 electricity index (FTSE350) from January 04, 2016, to March 04, 2022. First, we decompose the daily price changes by applying seasonal and trend decomposition using loess (STL). Then, we examine the inner dynamics of multifractality and cross-correlation by employing multifractal detrended fluctuation analysis (MFDFA) and multifractal detrended cross-correlation analysis (MFDCCA) using the remaining components of the return series. Our findings reveal that all series and the cross-correlations of carbon and fossil fuels markets have multifractal characteristics. We find crude oil to be the most efficient market (lowest multifractal), while coal is the least efficient (highest multifractal). Only coal shows persistent, whereas the other markets exhibit antipersistent behavior. Interestingly, the coal and EU ETS pair demonstrates a higher degree of multifractal patterns. In contrast, the pair of natural gas and EU ETS exhibits the lowest multifractal characteristics among the energy markets. Only the crude oil market shows persistent cross-correlations in the multifractality. These findings have important academic and managerial implications for investors and policymakers.

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Cross-correlations between economic policy uncertainty and precious and industrial metals: A multifractal cross-correlation analysis

Cited by 28 publications

References 79 publications

RETRACTED ARTICLE: Economic policy uncertainty and commodity market volatility: implications for economic recovery

RETRACTED ARTICLE: Economic policy uncertainty and commodity market volatility: implications for economic recovery

How does China economic policy uncertainty (EPU) impact copper-firms stock returns and copper prices returns?

On the inner dynamics between Fossil fuels and the carbon market: a combination of seasonal-trend decomposition and multifractal cross-correlation analysis

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