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Through the application of the VAR-AGARCH model to intra-day data for three cryp-tocurrencies (Bitcoin, Ethereum, and Litecoin), this study examines the return and volatility spillover between these cryptocurrencies during the pre-COVID-19 period and the COVID-19 period. We also estimate the optimal weights, hedge ratios, and hedging effectiveness during both sample periods. We find that the return spillovers vary across the two periods for the Bitcoin-Ethereum, Bitcoin-Litecoin, and Ethereum-Litecoin pairs. However, the volatility transmissions are found to be different during the two sample periods for the Bitcoin-Ethereum and Bitcoin-Litecoin pairs. The constant conditional correlations between all pairs of cryptocurrencies are observed to be higher during the COVID-19 period compared to the pre-COVID-19 period. Based on optimal weights, investors are advised to decrease their investments (a) in Bitcoin for the portfolios of Bitcoin/Ethereum and Bitcoin/Litecoin and (b) in Ethereum for the portfolios of Ethereum/Litecoin during the COVID-19 period. All hedge ratios are found to be higher during the COVID-19 period, implying a higher hedging cost compared to the pre-COVID-19 period. Last, the hedging effectiveness is higher during the COVID-19 period compared to the pre-COVID-19 period. Overall, these findings provide useful information to portfolio managers and policymakers regarding portfolio diversification, hedging, forecasting, and risk management.

PurposeThis study aims to analyze the moderating role of capital on the relationship between loan growth and credit risk for Islamic banks in the post-crisis era.Design/methodology/approachThe study used annual data of 217 Islamic banks from 38 countries and ranges from 2010–2019. The study applies a two-step system GMM method for hypotheses testing about the moderating role of bank capital on the relationship between loan growth and credit risk in Islamic banks.FindingsThe findings showed that an increase in loan growth increases the credit risk of Islamic banks, as evidenced by loan loss provisions, loan loss reserves and nonperforming loans. The results indicate that capital positively moderates the relationship between loan growth and credit risk in Islamic banking. The positive relationship between bank capital and risk-taking is in line with the “regulatory hypothesis” in banking. The findings predict lower impacts of capital on the relationship between loan growth and credit risk in the South Asian region than MENA, Africa, South, East and Central Asia regions. However, the impact of capital is higher for larger Islamic banks than medium and smaller ones.Practical implicationsThe findings of the study add value to the current debate on the role of bank capital to reduce risk-taking in Islamic banks. The study's findings have implications for policymakers, managers, especially in Islamic banking, for improving the Islamic financial system by managing the role of capital, loan growth and credit risk.Originality/valueThis is the first study to explore the moderating role of bank capital on the relationship between loan growth and credit risk in the post-crisis era, especially in Islamic banking. This is the first study in the Islamic banking context, which is providing empirical evidence for the impact of loan growth on the back looking and forward-looking proxies of credit risk under the moderating role of bank capitalization in the post-crisis era. This is the first study, which providing findings based on regions and size to compare the differences in Islamic banks for the impact of loan growth on credit risk under the moderating role of capitalization.

Purpose The purpose of this study is to investigate safe-haven properties of environmental, social and governance (ESG) stocks in global and emerging ESG stock markets during the times of COVID-19 so that portfolio managers and equity market investors could decide to use ESG stocks in their portfolio hedging strategies during times of health and market crisis similar to COVID-19 pandemic. Design/methodology/approach The study uses a wavelet coherence framework on four major ESG stock indices from global and emerging stock markets, and two proxies of COVID-19 fear over the period from 5 February 2020 to 18 March 2021. Findings The results of the study show a positive co-movement of the global COVID-19 fear index (GFI) with ESG stock indices on the frequency band of 32 to 64 days, which confirms hedging and safe-haven properties of ESG stocks using the health fear proxy of COVID-19. However, the relationship between all indices and GFI is mixed and inconclusive on a frequency of 0–8 days. Further, the findings do not support the safe-haven characteristics of ESG indices using the market fear proxy (IDEMV index) of COVID-19. The robustness analysis using the CBOE VIX as a proxy of market fear supports that ESG indices do not possess safe-haven properties. The results of the study conclude that the safe-haven properties of ESG indices during the ongoing COVID-19 pandemic is contingent upon the proxy of COVID-19 fear. Practical implications The findings have important implications for the equity investors and assetty managers to improve their portfolio performance by including ESG stocks in their portfolio choice during the COVID-19 pandemic and similar health crisis. However, their investment decisions could be affected by the choice of COVID-19 proxy. Originality/value The authors believe in the originality of the paper due to following reasons. First, to the best of the knowledge, this is the first study investigating the safe-haven properties of ESG stocks. Second, the authors use both health fear (GFI) and market fear (IDEMV index) proxies of COVID-19 to compare whether safe-haven properties are characterized by health fear or market fear due to COVID-19. Finally, the authors use the wavelet coherency framework, which not only takes both time and frequency dimensions of the data into account but also remains unaffected by data stationarity and size issues.

PurposeThis study aims to understand how quickly Japanese banks readjust their capital ratios (leverage, regulatory capital, tier-I capital and common equity) following an economic shock.Design/methodology/approachThis study uses a two-step system GMM framework to test the study's hypotheses using the annual data of Japanese commercial and cooperative banks ranging from 2005 to 2020.FindingsThe findings show that banks adjust their leverage ratio faster than regulatory capital, tier-I capital and common equity ratios. In addition to that, the results reveal that the speed of capital adjustment is higher for commercial banks than for cooperative banks, suggesting higher economic costs and implications for commercial banks. Furthermore, it is worth noting that well-capitalised (under-capitalised) banks tend to prioritise the adjustments to common equity (leverage) before considering the adjustments to leverage (common equity). According to the results, high-liquid (low-liquid) banks alter their regulatory capital and tier-I capital ratios (leverage) more quickly (more slowly) than low-liquid (high-liquid) banks.Practical implicationsThe findings suggest that when formulating and implementing new banking regulations, particularly in assessing and adjusting specific capital requirements under Pillar II of Basel III, management (including bankers, regulators and policymakers) should consider the heterogeneity observed in the rate of capital adjustment across various bank characteristics. Additionally, bank managers should also consider the speed of adjustment when determining optimal half-life and target capital structures.Originality/valueTo the author's knowledge, this study represents a pioneering investigation into the rate of adjustment of capital ratios (leverage, regulatory, tier-I and common equity) within Japan's banking sector. The study employs a comprehensive dataset encompassing both commercial and cooperative banks to facilitate this analysis. A notable contribution to the existing body of literature, this study offers a detailed analysis and emphasises the varying degrees of adjustment in capital ratios. The study also highlights the heterogeneous nature of the adjustment rate in these ratios by categorising the data into well-capitalised, under-capitalised, highly liquid and low-liquid banks.

This study uses hourly data to analyse the return and volatility transmission of oil-gold and oil-Bitcoin pairs during the pre-COVID-19 and COVID-19 periods. The results show that the return transmissions vary across the two periods for both pairs. There is a unidirectional volatility spill-over from gold to oil in the pre-COVID-19 period, and from oil to gold during the COVID-19 period. There is a significant volatility spill-over from Bitcoin to oil during the pre-COVID-19 period, whereas no evidence of volatility spill-over between oil and Bitcoin is shown during the COVID-19 period. Based on optimal weights, investors should increase their investments in, (a) gold for a portfolio of oil-gold, and (b) Bitcoin for a portfolio of oil-Bitcoin during the COVID-19 period. All hedge ratios are higher during the COVID-19 period, implying a higher hedging cost compared to the pre-COVID-19 period. The results of hedging effectiveness reveal that the risk-adjusted returns can be improved by constructing a portfolio of oil-gold and oil-Bitcoin during both sample periods. Further results reveal that gold is a strong safe haven and a hedge for the oil market, while Bitcoin serves as a diversifier for the oil market during the COVID-19 period.

Climate change may cause severe hydrological droughts, leading to water shortages which will require to be assessed using high-resolution data. Gravity Recovery and Climate Experiment (GRACE) satellite Terrestrial Water Storage (TWSA) estimates offer a promising solution to monitor hydrological drought, but its coarse resolution (1°) limits its applications to small regions of the Indus Basin Irrigation System (IBIS). Here we employed machine learning models such as Extreme Gradient Boosting (XGBoost) and Artificial Neural Network (ANN) to downscale GRACE TWSA from 1° to 0.25°. The findings revealed that the XGBoost model outperformed the ANN model with Nash Sutcliff Efficiency (NSE) (0.99), Pearson correlation (R) (0.99), Root Mean Square Error (RMSE) (5.22 mm), and Mean Absolute Error (MAE) (2.75 mm) between the predicted and GRACE-derived TWSA. Further, Water Storage Deficit Index (WSDI) and WSD (Water Storage Deficit) were used to determine the severity and episodes of droughts, respectively. The results of WSDI exhibited a strong agreement when compared with the Standardized Precipitation Evapotranspiration Index (SPEI) at different time scales (1-, 3-, and 6-months) and self-calibrated Palmer Drought Severity Index (sc-PDSI). Moreover, the IBIS had experienced increasing drought episodes, e.g., eight drought episodes were detected within the years 2010 and 2016 with WSDI of −1.20 and −1.28 and total WSD of −496.99 mm and −734.01 mm, respectively. The Partial Least Square Regression (PLSR) model between WSDI and climatic variables indicated that potential evaporation had the largest influence on drought after precipitation. The findings of this study will be helpful for drought-related decision-making in IBIS.

Groundwater has a significant contribution to water storage and is considered to be one of the sources for agricultural irrigation; industrial; and domestic water use. The Gravity Recovery and Climate Experiment (GRACE) satellite provides a unique opportunity to evaluate terrestrial water storage (TWS) and groundwater storage (GWS) at a large spatial scale. However; the coarse resolution of GRACE limits its ability to investigate the water storage change at a small scale. It is; therefore; needed to improve the resolution of GRACE data at a spatial scale applicable for regional-level studies. In this study; a machine-learning-based downscaling random forest model (RFM) and artificial neural network (ANN) model were developed to downscale GRACE data (TWS and GWS) from 1° to a higher resolution (0.25°). The spatial maps of downscaled TWS and GWS were generated over the Indus basin irrigation system (IBIS). Variations in TWS of GRACE in combination with geospatial variables; including digital elevation model (DEM), slope; aspect; and hydrological variables; including soil moisture; evapotranspiration; rainfall; surface runoff; canopy water; and temperature; were used. The geospatial and hydrological variables could potentially contribute to; or correlate with; GRACE TWS. The RFM outperformed the ANN model and results show Pearson correlation coefficient (R) (0.97), root mean square error (RMSE) (11.83 mm), mean absolute error (MAE) (7.71 mm), and Nash–Sutcliffe efficiency (NSE) (0.94) while comparing with the training dataset from 2003 to 2016. These results indicate the suitability of RFM to downscale GRACE data at a regional scale. The downscaled GWS data were analyzed; and we observed that the region has lost GWS of about −9.54 ± 1.27 km3 at the rate of −0.68 ± 0.09 km3/year from 2003 to 2016. The validation results showed that R between downscaled GWS and observational wells GWS are 0.67 and 0.77 at seasonal and annual scales with a confidence level of 95%, respectively. It can; therefore; be concluded that the RFM has the potential to downscale GRACE data at a spatial scale suitable to predict GWS at regional scales.

Purpose This study aims to examine the hedge, diversifier and safe-haven properties of bonds against infectious disease-related equity market volatility (IDEMV), like COVID-19.Design/methodology/approach The authors apply wavelet coherence methodology on the daily data of IDEMV and bond market (US, UK, Japan, Switzerland, Canada, Australia, Sweden, China and Europe) indices from 1 January 2000 to 14 February 2021.Findings The results show no significant co-movement between these bond indices and IDEMV, thus confirming that they serve as a hedge against IDEMV. However, during the turbulent period like COVID-19, the authors find that the US, UK, Japan, Switzerland, Canada, Australia, Sweden, China and European bond markets act as safe-haven against IDEMV, whereas the UK, US, Japan and Canadian bond markets demonstrate an in-phase and positive co-movement with IDEMV during COVID-19, suggesting their role as a diversifier.Research limitations/implications The study findings are important for investors and portfolio managers regarding risk management, portfolio diversification and investment strategies.Originality/value The authors contribute to the fast growing body of work on the financial impacts of COVID-19 as well as to ongoing consideration of whether a bond is a safe-haven investment.

This study aims to investigate the impact of banking-sector concentration on the banks' liquidity creation in GCC countries over the period from 2012 to 2018 by using a dynamic GMM panel procedure. The results suggest that increased bank competition reduces banks' liquidity creation across the GCC countries. The study's findings are in line with the 'financial fragility hypothesis\" according to which banks to reduce their lending activities when competition is high in the market. The evidence suggests that the banking industry is different from others, and pro-competitive policies in the banking industry can reduce liquidity provision by banks. In the context of policy implications, a concentrated banking system discourages capital provision to firms; hence, regulators have to take appropriate measures to resolve the problem of a reduced supply of capital. Government must regulate the banking sector by keeping in view their long-run goal as competition is a double-edged sword in banking.

This study examines the safe-haven and hedging roles of gold against thirteen Asian stock markets during the COVID-19 outbreak. During the COVID-19 sub-period, gold is shown to be a strong hedge (diversifier) for the majority (minority) of Asian stock markets; it exhibits the property of a strong safe-haven in China, Indonesia, Singapore, and Vietnam, and a weak safe-haven in Pakistan and Thailand. The optimal weights of all stock-gold portfolios are lower during the COVID-19 sub-period than the pre COVID-19 sub-period, suggesting that portfolio investors should increase their investment in gold during the COVID-19 sub-period. The hedging effectiveness for most Asian stock markets is higher during the COVID-19 sub-period. Further analyses show that the hedge portfolio returns in many cases are mostly driven by gold implied volatility and inflation expectations in both sub-periods. Our findings have useful implications for market participants holding investments in Asian stocks during stressful periods.