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We study price-switching spillovers between real estate investment trusts (REITs), oil, and gold markets by considering high- and low-volatility regimes as described by Markov-switching vector autoregression. Empirical results for different REIT markets indicate that gold (oil) has a lower (higher) impact on REITs in a high-volatility regime than in a low-volatility regime. Furthermore, in a low-volatility regime, gold and oil are net spillover contributors to REITs, while in a high-volatility regime, REITs are net spillover contributors. Price spillovers are time-varying, and climb during the early COVID-19 pandemic period and in early 2022.

This paper examines the quantile-dependent short- and long-run impact of the FFR, VIX index and crude oil prices on the credit risk of the U.S. banking, financial services and insurance sectors. Using the quantile autoregressive distributed lag model, we find that the federal funds rate and the equity volatility mainly increase the credit risk of the financial sector when the credit risk is on a rising trend. However, oil prices, and to a lesser extent, decrease the credit risk. The short- and long-run impacts of the considered risk factors are time-varying and heterogeneous across the different credit market states.

This study explores the impacts of structural breaks (SB) on the dual long memory levels of Bitcoin and Ethereum price returns. We identify dual long memory and structural changes on cryptocurrency markets using four different generalized autoregressive conditional heteroskedasticity models (e.g., GARCH, FIGARCH, FIAPARCH, and HYGARCH). Furthermore, the persistence level of both returns and volatility decreases after accounting for long memory and switching states. Finally, the FIGARCH model with SB variables provides a comparatively superior forecasting accuracy performance. These findings have significant implications for both cryptocurrency allocations and portfolio management.

This study assesses the efficiency of Bitcoin market compared to gold, stock and foreign exchange markets. By applying a MF-DFA approach, the study found that the long-memory feature and multifractality of the Bitcoin market was stronger and Bitcoin was therefore more inefficient than the gold, stock and currency markets.

This paper investigates the volatility spillover and connectedness among global and regional stock markets and those of Greece, Ireland, Portugal, Spain, and Italy (GIPSI). For this investigation, we perform a static and rolling-window analysis to measure volatility spillovers using the Diebold and Yilmaz (2012, 2014) methodology. We also examine the network connectedness at different stages of recent crises. Our finding indicates that recent crises intensify volatility spillovers, supporting the financial contagion effects. Furthermore, the GIPSI (except Spain and Greece markets), global and regional U.S. markets are net transmitter of shocks while the rest stock markets are net receiver of shocks.

This paper investigates the upward and downward multifractality and time-varying efficiency of green bonds (GBs) using the asymmetric MF-DFA method and Hurst exponents. The results reveal significant asymmetrical multifractality for all GB markets, which increased as the scale increased. Moreover, GB markets are inefficient and vary across market trends and scales. The MSCI Global, Green Building, Industrial, Utility, and Baa GB markets are more inefficient under upward trends whereas the remaining GB markets are more inefficient under downward trends. Citi Macro Risk, both US and Eurozone financial conditions, treasury bills, and COVID-19 are the drivers of GB dynamic inefficiency.

This study examines the dynamic correlations and portfolio diversification between the major developed and BRICS stock markets. The results reveal a significant variability in the time-varying conditional correlations between these markets during upturn and downturn periods. We underline the importance of overweighting the optimal portfolios with stocks from the developed countries over those from the BRICS. Finally, we demonstrate the usefulness of using developed market stocks in the BRICS stock portfolio risk management.

This paper examines the impacts of COVID-19 outbreak on the spillover between ten US and Chinese equity sectors. We use Copula and Conditional Value at Risk approaches. The results show evidence of asymmetric tail dependence during the COVID-19 outbreak with the exception of the Utilities sector, where a symmetric tail dependence is found. Moreover, we find time-varying bidirectional asymmetric risk spillovers from the US to China and vice versa. The risk spillover is higher from the US to China before COVID-19 and from China to the US during COVD-19 spread, which is significantly intensified between March 2020 and April 2020.