On the relationship between Bitcoin and other assets during the outbreak of coronavirus: Evidence from fractional cointegration analysis

Béjaoui, Azza; Mgadmi, Nidhal; Moussa, Wajdi

doi:10.1016/j.resourpol.2022.102682

Cited by 7 publications

(3 citation statements)

References 23 publications

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“…According to Yin et al ( 2021 ), the long-term volatility of cryptocurrency markets has a considerable impact on the oil market. Bejaoui et al ( 2022 ) also discover a strong correlation between Bitcoin and commodity assets such as crude oil and natural gas. Hassan et al ( 2022 ) recently examined the relationship between the cryptocurrency environmental attention index (ICEA) and three asset classes, including commodity markets, and found that the commodity assets, such as soybeans, had a positive correlation with it.…”

Section: Introductionmentioning

confidence: 98%

Do commodity assets hedge uncertainties? What we learn from the recent turbulence period?

et al. 2022

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This study analyses the impact of different uncertainties on commodity markets to assess commodity markets' hedging or safe-haven properties. Using time-varying dynamic conditional correlation and wavelet-based Quantile-on-Quantile regression models, our findings show that, both before and during the COVID-19 crisis, soybeans and clean energy stocks offer strong safe-haven opportunities against cryptocurrency price uncertainty and geopolitical risks (GPR). Soybean markets weakly hedge cryptocurrency policy uncertainty, US economic policy uncertainty, and crude oil volatility. In addition, GSCI commodity and crude oil also offer a weak safe-haven property against cryptocurrency uncertainties and GPR. Consistent with earlier studies, our findings indicate that safe-haven traits can alter across frequencies and quantiles. Our findings have significant implications for investors and regulators in hedging and making proper decisions, respectively, under diverse uncertain circumstances.

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Section: Introductionmentioning

confidence: 98%

Do commodity assets hedge uncertainties? What we learn from the recent turbulence period?

et al. 2022

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“…Furthermore, we examined the correlation between Bitcoin and other assets (namely, crude oil, S&P500 and natural gas) amid the onset of the Covid-19 pandemic using fractional cointegration analysis [35]. Our findings revealed the presence of fractional integration within the residual series, suggesting the existence of this type of relationship.…”

Section: Literature Reviewmentioning

confidence: 88%

“…The S&P500, Bitcoin, and Brent crude oil are all financial assets, but they are influenced by distinct underlying factors that drive their prices [33], [34]. While there can be some correlations between these assets (as in Figure 1), they are affected by a variety of factors over time, and the connections between them may not always be evident [35], [36]. Nonetheless, random events such as Covid-19 and conflicts (Ukraine, Gaza) have consistently influenced the relationships among stock markets, commodities and cryptocurrencies.…”

Section: Introductionmentioning

confidence: 99%

Exploring the Dynamics of Brent Crude Oil, S&P500 and Bitcoin Prices Amid Economic Instability

Bâra,

Georgescu,

Oprea

et al. 2024

IEEE Access

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In this paper, we mainly investigate three variables from the price volatility point of view: Brent crude oil, S&P500 and Bitcoin (BTCUSD), aiming to underline the impact of price volatility. Brent crude oil accounts for two-thirds of the oil market. Its price volatility has a significant impact on environmental, transportation, mobility, economic and social aspects that affect sustainability. This paper conducts an extensive examination of the forecasting capabilities of various GARCH (Generalized Autoregressive Conditional Heteroskedasticity) models, identifying the most suitable GARCH model for estimating Value at Risk (VaR) for Brent crude oil price. The assessment of VaR for different GARCH models is carried out using Kupiec's Probability of Failure (POF) test and Christoffersen's test. This study leverages Brent crude oil data spanning from 2019 to 2023. Additionally, to prove the robustness of the GARCH models, we further consider the West Texas Intermediate (WTI) and Dubai oil prices that are the dominant in the U.S and Asian market. The investigation identifies the TGARCH(1,1) Skewed Student model as the optimal choice among 9 models considered for VaR estimation. The results show that TGARCH Skewed Student model surpasses the other models in the study, proving its superiority in forecasting Brent crude oil price volatility and facilitating VaR estimation. A VaR of 0.044 with a 95% confidence level means that there is a 95% chance that the portfolio will not lose more than 4.4% of its value. By incorporating skewness in addition to volatility asymmetry, the Skewed GARCH-type models provide a more realistic representation of the underlying return distribution. Furthermore, the most appropriate GARCH-type model for WTI crude oil is EGARCH(1,1) Skewed Student, with a VaR coverage of 0.39. The most appropriate GARCH-type model for Dubai crude oil is TGARCH(1,1) Skewed Student, with a VaR coverage of 0.17. Both WTI oil and Dubai crude oil have a coverage that exceeds 5%, implying a more conservative approach to estimating potential losses. Furthermore, the unidirectional causalities BTCUSD→BRENT and BTCUSD→S&P500 are identified. The results of the current research have practical implications for both importing and exporting countries, policy makers and investors. For companies in the oil sector, VaR informs operational decisions, such as production levels, capital expenditure and inventory management, by providing insights into market risk. Moreover, understanding the risks associated with oil aids in long-term strategic planning.INDEX TERMS backtesting, Bitcoin, Brent crude oil, GARCH model, price volatility, S&P500

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Spillover Connectedness Between Cryptocurrency and Energy Sector: An Empirical Investigation Under Asymmetric Exogenous Shocks of Health and Geopolitical Crisis and Uncertainties

Gherghina,

Armeanu,

Andrei

et al. 2024

J Knowl Econ

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On the relationship between Bitcoin and other assets during the outbreak of coronavirus: Evidence from fractional cointegration analysis

Cited by 7 publications

References 23 publications

Do commodity assets hedge uncertainties? What we learn from the recent turbulence period?

Do commodity assets hedge uncertainties? What we learn from the recent turbulence period?

Exploring the Dynamics of Brent Crude Oil, S&P500 and Bitcoin Prices Amid Economic Instability

Spillover Connectedness Between Cryptocurrency and Energy Sector: An Empirical Investigation Under Asymmetric Exogenous Shocks of Health and Geopolitical Crisis and Uncertainties

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