This study addresses whether gold exhibits the function of a hedge or safe haven as often referred to in academia.It contributes to the existing literature by(i)revisiting this question for the principal stock markets...This study addresses whether gold exhibits the function of a hedge or safe haven as often referred to in academia.It contributes to the existing literature by(i)revisiting this question for the principal stock markets in the Middle East and North Africa(MENA)region and(ii)using the copula-quantile-on-quantile and conditional value at risk methods to detail the risks facing market participants provided with accurate information about various gold and stock market scenarios(i.e.,bear,normal,bull).The results provide strong evidence of quantile dependence between gold and stock returns.Positive correlations are found between MENA gold and stock markets when both are bullish.Conversely,when stock returns are bearish,gold markets show negative correlations with MENA stock markets.The risk spillover from gold to stock markets intensified during the global financial and European crises.Given the risk spillover between gold and stock markets,investors in MENA markets should be careful when considering gold as a safe haven because its effectiveness as a hedge is not the same in all MENA stock markets.Investors and portfolio managers should rebalance their portfolio compositions under various gold and stock market conditions.Overall,such precise insights about the heterogeneous linkages and spillovers between gold and MENA stock returns provide potential input for developing effective hedging strategies and optimal portfolio allocations.展开更多
This study investigates tail dependence among five major cryptocurrencies,namely Bitcoin,Ethereum,Litecoin,Ripple,and Bitcoin Cash,and uncertainties in the gold,oil,and equity markets.Using the cross-quantilogram meth...This study investigates tail dependence among five major cryptocurrencies,namely Bitcoin,Ethereum,Litecoin,Ripple,and Bitcoin Cash,and uncertainties in the gold,oil,and equity markets.Using the cross-quantilogram method and quantile connectedness approach,we identify cross-quantile interdependence between the analyzed variables.Our results show that the spillover between cryptocurrencies and volatility indices for the major traditional markets varies substantially across quantiles,implying that diversification benefits for these assets may differ widely across normal and extreme market conditions.Under normal market conditions,the total connectedness index is moderate and falls below the elevated values observed under bearish and bullish market conditions.Moreover,we show that under all market conditions,cryptocurrencies have a leadership influence over the volatility indices.Our results have important policy implications for enhancing financial stability and deliver valuable insights for deploying volatility-based financial instruments that can potentially provide cryptocurrency investors with suitable hedges,as we show that cryptocurrency and volatility markets are insignificantly(weakly)connected under normal(extreme)market conditions.展开更多
This paper examines the high frequency multiscale relationships and nonlinear multiscale causality between Bitcoin,Ethereum,Monero,Dash,Ripple,and Litecoin.We apply nonlinear Granger causality and rolling window wavel...This paper examines the high frequency multiscale relationships and nonlinear multiscale causality between Bitcoin,Ethereum,Monero,Dash,Ripple,and Litecoin.We apply nonlinear Granger causality and rolling window wavelet correlation(RWCC)to 15 min-data.Empirical RWCC results indicate mostly positive co-movements and long-term memory between the cryptocurrencies,especially between Bitcoin,Ethereum,and Monero.The nonlinear Granger causality tests reveal dual causation between most of the cryptocurrency pairs.We advance evidence to improve portfolio risk assessment,and hedging strategies.展开更多
Correction to:Financ Innov 7:75(2021)https://doi.org/10.1186/s40854-021-00290-w Following publication of this article(Mensi et al.2021),the corresponding author reported that his 2nd affiliation was missing.So the cor...Correction to:Financ Innov 7:75(2021)https://doi.org/10.1186/s40854-021-00290-w Following publication of this article(Mensi et al.2021),the corresponding author reported that his 2nd affiliation was missing.So the corresponding author’s affiliations are:1Department of Economics and Finance,College of Economics and Political Science,Sultan Qaboos University,Muscat,Oman 2South Ural State University,76,Lenin Prospekt,Chelyabinsk,Russian Federation The affiliations have been updated in this Correction and in the original article.展开更多
文摘This study addresses whether gold exhibits the function of a hedge or safe haven as often referred to in academia.It contributes to the existing literature by(i)revisiting this question for the principal stock markets in the Middle East and North Africa(MENA)region and(ii)using the copula-quantile-on-quantile and conditional value at risk methods to detail the risks facing market participants provided with accurate information about various gold and stock market scenarios(i.e.,bear,normal,bull).The results provide strong evidence of quantile dependence between gold and stock returns.Positive correlations are found between MENA gold and stock markets when both are bullish.Conversely,when stock returns are bearish,gold markets show negative correlations with MENA stock markets.The risk spillover from gold to stock markets intensified during the global financial and European crises.Given the risk spillover between gold and stock markets,investors in MENA markets should be careful when considering gold as a safe haven because its effectiveness as a hedge is not the same in all MENA stock markets.Investors and portfolio managers should rebalance their portfolio compositions under various gold and stock market conditions.Overall,such precise insights about the heterogeneous linkages and spillovers between gold and MENA stock returns provide potential input for developing effective hedging strategies and optimal portfolio allocations.
基金supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea(2022S1A5A2A01038422).
文摘This study investigates tail dependence among five major cryptocurrencies,namely Bitcoin,Ethereum,Litecoin,Ripple,and Bitcoin Cash,and uncertainties in the gold,oil,and equity markets.Using the cross-quantilogram method and quantile connectedness approach,we identify cross-quantile interdependence between the analyzed variables.Our results show that the spillover between cryptocurrencies and volatility indices for the major traditional markets varies substantially across quantiles,implying that diversification benefits for these assets may differ widely across normal and extreme market conditions.Under normal market conditions,the total connectedness index is moderate and falls below the elevated values observed under bearish and bullish market conditions.Moreover,we show that under all market conditions,cryptocurrencies have a leadership influence over the volatility indices.Our results have important policy implications for enhancing financial stability and deliver valuable insights for deploying volatility-based financial instruments that can potentially provide cryptocurrency investors with suitable hedges,as we show that cryptocurrency and volatility markets are insignificantly(weakly)connected under normal(extreme)market conditions.
文摘This paper examines the high frequency multiscale relationships and nonlinear multiscale causality between Bitcoin,Ethereum,Monero,Dash,Ripple,and Litecoin.We apply nonlinear Granger causality and rolling window wavelet correlation(RWCC)to 15 min-data.Empirical RWCC results indicate mostly positive co-movements and long-term memory between the cryptocurrencies,especially between Bitcoin,Ethereum,and Monero.The nonlinear Granger causality tests reveal dual causation between most of the cryptocurrency pairs.We advance evidence to improve portfolio risk assessment,and hedging strategies.
文摘Correction to:Financ Innov 7:75(2021)https://doi.org/10.1186/s40854-021-00290-w Following publication of this article(Mensi et al.2021),the corresponding author reported that his 2nd affiliation was missing.So the corresponding author’s affiliations are:1Department of Economics and Finance,College of Economics and Political Science,Sultan Qaboos University,Muscat,Oman 2South Ural State University,76,Lenin Prospekt,Chelyabinsk,Russian Federation The affiliations have been updated in this Correction and in the original article.
