Search results

This study aims to explore the impact of cryptocurrencies (Bitcoin, Ethereum, Monero and Ripple) on the gold, WTI, VIX index, G7 and the BRICS index before and during COVID-19.

This research analyzes the impact of cryptocurrencies (Bitcoin, Ethereum, Monero and Ripple) on the gold, WTI, VIX index, G7 and the BRICS index before and during COVID-19, using the quantile regression approach for the 2016–2020 period. In addition, to catch long- and short-run asymmetries of cryptocurrencies on aforementioned dependent variables, an asymmetric nonlinear co-integration (nonlinear autoregressive distributed lag [NARDL]) approach is applied.

The result of the quantile regression shows that in a high market, which corresponds to the 90th quantile, the FTSE MIB, CAC40, SSE, BSE 30, and BVSP stock market showed a statistically insignificant negative coefficient, on the Bitcoin price. In a middle and low markets, which correspond to the 0.2, 0.3 and 0.5th quantiles, the BVSP, FTSE MIB, S&P/TSX, SSE and Nikkei stock markets show statistically significant and positive on Bitcoin. Evidence from the NARDL shows a statistically significant positive impact of cryptocurrencies on the gold, WTI, VIX index, G7 and BRICS indices before and during COVID-19 pandemic.

These results can provide investors with valuable analysis and information and help them make the best decisions and adopt the best strategies. Therefore, future investigations may concentrate and examine the monetary and governmental policies to be adapted to face the COVID-19 pandemic’s dangerous effects on both the society and the economy. For this reason, investors should take this into account when making their asset allocation decisions. Moreover, the portfolio managers, such as index funds, may consider few eligible cryptocurrencies for their inclusion into the portfolio. However, the speculators present in both stock and crypto markets may opt for a spread strategy to improve their portfolio returns.

The purpose of this study is to examine whether the relationship between asset quality and profitability is linear or nonlinear, using a global dataset containing 2,943 banks from advanced and emerging economies.

The authors use the U-shape test to investigate the existence of a nonlinear relationship between asset quality and profitability. In addition, the dynamic panel generalised method of moments (GMM) and quantile regression are used to examine the nonlinear effect of profitability on nonperforming loans (NPLs).

After controlling for macroeconomic and bank internal factors, the authors find empirical evidence supporting the existence of a nonlinear relationship in the form of a U-shape. This is also confirmed through the three-stage U test procedure. After distinguishing between advanced and emerging economies, the authors also find that, in advanced markets, the credit policy responds more rapidly to changes in credit market conditions than in emerging markets, providing insights into credit market dynamics.

Further research can check the robustness of this study’s findings in different markets and investigate the existence of nonlinearity in other bank variables.

In a nutshell, the results demonstrate potential implications for policymakers who need to carefully monitor banks' lending behaviour to ensure that banks do not lower lending standards. In addition, banking regulators and supervisors should consider the possible nonlinear relationship in their risk assessments and macrostress tests. Further, these results are important for bank managers, who should monitor the performance of their loan portfolios to ensure that their credit officers do not lower credit standards. Likewise, for banks located in an emerging economy, investing in human capital and advanced technologies can enable them to respond more effectively to changes in the credit market.

To the best of the authors' knowledge, this study is considered the first to provide empirical evidence for the nonlinear relationship between asset quality and profitability.