Do commodity markets catch a cold from stock markets? Modelling uncertainty spillovers using Google search trends and wavelet coherence

Szczygielski, Jan; Charteris, Ailie; Obojska, Lidia

doi:10.1016/j.irfa.2022.102304

Cited by 10 publications

(2 citation statements)

References 105 publications

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“…In contrast, wavelet techniques can extract information across a spectrum of frequencies while preserving the temporal dimension (Kumar and Ajaz 2019). The wavelet coherence model holds significant prominence among researchers for its extensive utilization in examining the intricate dynamics of contagion between markets (Aloui and Hkiri 2014;Kirikkaleli and Güngör, 2021;Özdemir 2022;Pal and Mitra 2019;Szczygielski et al 2023;Xie et al 2023). Employing this model, we generated heatmaps to monitor contagion dynamics among Bitcoin, gold, and the stock markets of Japan, the USA, the UK, China, Germany, and France over a specific period.…”

Section: Additional Analysis Using Wavelet Coherence Modelmentioning

confidence: 99%

Volatility contagion between cryptocurrencies, gold and stock markets pre-and-during COVID-19: evidence using DCC-GARCH and cascade-correlation network

Ibrahim,

Elamer,

Alasker

et al. 2024

Financ Innov

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The rapid rise of Bitcoin and its increasing global adoption has raised concerns about its impact on traditional markets, particularly in periods of economic turmoil and uncertainty such as the COVID-19 pandemic. This study examines the extent of the volatility contagion from the Bitcoin market to traditional markets, focusing on gold and six major stock markets (Japan, USA, UK, China, Germany, and France) using daily data from January 2, 2011, to June 2, 2022, with 2958 daily observations. We employ DCC-GARCH, wavelet coherence, and cascade-correlation network models to analyze the relationship between Bitcoin and those markets. Our results indicate long-term volatility contagion between Bitcoin and gold and short-term contagion during periods of market turmoil and uncertainty. We also find evidence of long-term contagion between Bitcoin and the six stock markets, with short-term contagion observed in Chinese and Japanese markets during COVID-19. These results suggest a risk of uncontrollable threats from Bitcoin volatility and highlight the need for measures to prevent infection transmission to local stock markets. Hedge funds, mutual funds, and individual and institutional investors can benefit from using our findings in their risk management strategies. Our research confirms the utility of the cascade-correlation network model as an innovative method to investigate intermarket contagion across diverse conditions. It holds significant implications for stock market investors and policymakers, providing evidence for potentially using cryptocurrencies for hedging, for diversification, or as a safe haven.

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Section: Additional Analysis Using Wavelet Coherence Modelmentioning

confidence: 99%

Volatility contagion between cryptocurrencies, gold and stock markets pre-and-during COVID-19: evidence using DCC-GARCH and cascade-correlation network

Ibrahim,

Elamer,

Alasker

et al. 2024

Financ Innov

View full text Add to dashboard Cite

show abstract

“…1 Volatility in the commodity market can be transmitted to other global investment portfolios (bonds, stocks, currencies, cash and cash equivalents) (Szczygielski et al, 2023). This study makes two main contributions to the existing body of knowledge.…”

Section: Introductionmentioning

confidence: 96%

Modelling Volatility in the Commodity Market Amidst Russia- Ukraine War

Imandojemu,

Sule

2024

Energy RESEARCH LETTERS

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We pursue two noteworthy effects of the Russia-Ukraine war on commodity market volatility. First, we construct a Russia-Ukraine war index while modelling commodity market volatility. Second, we explore the relationship between the Russia-Ukraine war and commodity market volatility using various estimators. We find consistent patterns in the volatility models of the selected estimators. Our results show that the Russia-Ukraine war triggered commodity market volatility.

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Interconnectedness between electricity and artificial intelligence-based markets during the crisis periods: Evidence from the TVP-VAR approach

Yousaf,

Ohikhuare,

et al. 2024

Energy Economics

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Do commodity markets catch a cold from stock markets? Modelling uncertainty spillovers using Google search trends and wavelet coherence

Cited by 10 publications

References 105 publications

Volatility contagion between cryptocurrencies, gold and stock markets pre-and-during COVID-19: evidence using DCC-GARCH and cascade-correlation network

Volatility contagion between cryptocurrencies, gold and stock markets pre-and-during COVID-19: evidence using DCC-GARCH and cascade-correlation network

Modelling Volatility in the Commodity Market Amidst Russia- Ukraine War

Interconnectedness between electricity and artificial intelligence-based markets during the crisis periods: Evidence from the TVP-VAR approach

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