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.

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.

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.

This study aims to examine the tail connectedness between the Chinese and Association of Southeast Asian Nations (ASEAN) stock markets. More specifically, the authors measure the return spillovers at three quantile levels: median (t = 0.5), lower extreme (t = 0.05) and upper extreme (t = 0.95). The connectedness at extreme upper and lower quantiles provides insightful information to investors regarding tail risk propagation, which ultimately suggests that investors adjust their portfolios according to the extreme bullish and bearish market conditions. The authors employ the quantile connectedness approach of Ando et al. (2022) to examine the quantile transmission mechanism among the ASEAN and Chinese stock markets. The results show significant evidence of a higher level of connectedness between Chinese and ASEAN stock markets at extreme upper and lower quantiles compared to the median quantiles, which suggests the use of a quantile-based connectedness approach instead of an average-measure-based one. Furthermore, the time-varying connectedness analysis shows that the total spillovers reach the highest peaks during the global financial crisis, the Chinese stock market crash and the COVID-19 pandemic at the upper, lower and median quantiles. Finally, the static and dynamic pairwise spillovers between the Chinese and ASEAN markets vary over quantiles as well. This study is the first attempt to examine quantile vector autoregression (VAR)-based return spillovers between China and ASEAN stock markets during different market statuses. Besides, the COVID-19 has intensified the uncertainty in Asian countries, mainly China and ASEAN economies.

Purpose: This paper examines asymmetric multifractality (A-MF) in the leading Middle East and North Africa (MENA) stock markets under different turbulent periods (global financial crisis [GFC] and European sovereign debt crisis [ESDC], oil price crash and COVID-19 pandemic).Design/methodology/approach: This study applies the asymmetric multifractal detrended fluctuation analysis (A-MF-DFA) method of Cao et al. (2013) to identify A-MF and MENA stock market efficiency during the COVID-19 pandemic.Findings: The results show strong evidence of different patterns of MF during upward and downward trends. Inefficiency is higher during upward trends than during downward trends in most of the stock markets in the whole sample period, and the opposite is true during financial crises. The Turkish stock market is the least inefficient during upward and downward trends. A-MF intensifies with an increase in scales. The evolution of excessive A-MF for MENA stock returns is heterogeneous. Most of the stock markets are more inefficient during a pandemic crisis than during an oil crash and other financial crises. However, the inefficiency of the Saudi Arabia and Qatar stock markets is highly sensitive to oil price crashes. Overall, the level of inefficiency varies across market trends, scales and stock markets and over time. The findings of this study provide investors and policymakers with valuable insights into efficient investment strategies, risk management and financial stability.Originality/value: This paper first explores A-MF in the MENA emerging stock markets. The A-MF analysis provides useful information to investors regarding asset allocation, portfolio risk management and investment strategies during bullish and bearish market states. In addition, this paper examines A-MF under different turbulent periods, such as the GFC, the ESDC, the 2014–2016 oil crash and the COVID-19 pandemic.