Pharmacokinetic interaction between verapamil and ritonavir-boosted nirmatrelvir: implications for the management of COVID-19 in patients with hypertension.

A woman in her 80s was brought to the emergency department for acute onset of generalised weakness, lethargy and altered mental state. The emergency medical service found her to have symptomatic bradycardia, and transcutaneous pacing was done. Medical history was notable for hypertension, hyperlipidaemia, type 2 diabetes, and a recently diagnosed SARS-CoV-2 (COVID-19) infection for which she was prescribed ritonavir-boosted nirmatrelvir (Paxlovid) two days before the presentation. On arrival at the hospital, she was found to have marked bradycardia with widened QRS, hyperglycaemia and metabolic acidosis. Transvenous pacing along with pressor support and insulin were initiated, and she was admitted to the intensive care unit. Drug interaction between ritonavir-boosted nirmatrelvir and verapamil leading to verapamil toxicity was suspected of causing her symptoms, and both drugs were withheld. She reverted to sinus rhythm on the fourth day, and the pacemaker was discontinued.

Examining the asymmetries between equity and commodity ETFs during COVID-19

Previous studies have neither examined the volatility co-movements across stock and commodity markets in terms of both time and frequency nor differentiated between bad and good volatility and the potential asymmetric effect. To address this gap, we computed 5-min price data, the positive and negative semivariances on five leading Exchange Traded Funds (ETFs) covering the US equity market, crude oil, natural gas, gold, and silver markets from January 2, 2019 to May 29, 2020, and then draw on the wavelet coherency methodology and the time-varying wavelet coherence measure. The results showed that the negative realized volatility co-movements are stronger during the COVID-19 outbreak, especially at short and medium frequencies. The US stock market leads energy and precious metals in the short-run frequency. However, over the long-run, the lead-lag pattern mostly alternates over time for all cases. Notably, the realized volatilities of US equities and precious metals are shaped by the COVID-19 outbreak, reflecting the quest of investors for protection from the market volatilities by investing in gold and silver. This latest finding is confirmed by the wavelet coherence measure. Further results showed asymmetric co-movements emanating especially from realized negative semivariance of equities and energy markets around the pandemic outbreak across short time horizons. We also noticed that the COVID-19 outbreak increased the procyclical movement of all ETFs in the short term. The effect is more pronounced among the US equity and precious metals markets, whereas no significant countercyclical connectedness is observed among these markets. Our findings supported previous evidence that gold and silver can serve as safe-haven assets due to their low coherence with other assets.

Measuring systemic risk in the global banking sector: A cross-quantilogram network approach

We propose a new systemic risk index based on the interdependence of extreme downside movements of stock returns using the cross-quantilogram and network analysis approach. While quantile dependence allows for sensitivity in times of market downturn, the topological network properties allow for capturing the interconnectedness of the banking system and identification of the specific contribution of each individual bank. Using this design, the proposed systemic risk index is not only easy to calculate and interpret but identifies the banking system's significant transmitters and receivers of extreme downside risk. For the empirical evaluation of the proposed risk index, we use a sample of 83 large banks during the 2003–2020 period, spanning multiple recent crises affecting the banking market. The proposed index is found to be robust in comparison to major alternative systemic risk measures.

Dependence dynamics of Islamic and conventional equity sectors: What do we learn from the decoupling hypothesis and COVID-19 pandemic?

The recent COVID-19 pandemic intensification generates a different set of challenges for global financial markets and portfolio management strategies. This paper uses network analysis to investigate the static and dynamic dependence within Islamic and conventional equity sectors. The study focuses on the decoupling hypothesis and how the dependence among sectors changes during COVID19. Empirical findings indicate a higher degree of spillover during the COVID19 sub-period. Islamic and conventional equities behave differently in terms of industry-level dependence during normal and crisis times, thus decoupling. Further, the dependence effect between conventional equity returns is stronger than Islamic equity returns during the COVID-19 pandemic. The finding of this paper has several significant implications for portfolio selection and risk management. Portfolios consisting of Islamic equity sectors including industrials, basic materials, consumer services, and technologies highlight low-diversification benefits across the entire sample period. Also, investment exposure to less connected Islamic and conventional equity sectors provides a good diversification strategy.

A chain mediation model on COVID-19 symptoms and mental health outcomes in Americans, Asians and Europeans.

The novel Coronavirus-2019 (COVID-19) was declared a pandemic by the World Health Organization (WHO) in March 2020, impacting the lifestyles, economy, physical and mental health of individuals globally. This study aimed to test the model triggered by physical symptoms resembling COVID-19 infection, in which the need for health information and perceived impact of the pandemic mediated the path sequentially, leading to adverse mental health outcomes. A cross-sectional research design with chain mediation model involving 4612 participants from participating 8 countries selected via a respondent-driven sampling strategy was used. Participants completed online questionnaires on physical symptoms, the need for health information, the Impact of Event Scale-Revised (IES-R) questionnaire and Depression, Anxiety and Stress Scale (DASS-21). The results showed that Poland and the Philippines were the two countries with the highest levels of anxiety, depression and stress; conversely, Vietnam had the lowest mean scores in these areas. Chain mediation model showed the need for health information, and the perceived impact of the pandemic were sequential mediators between physical symptoms resembling COVID-19 infection (predictor) and consequent mental health status (outcome). Excessive and contradictory health information might increase the perceived impact of the pandemic. Rapid COVID-19 testing should be implemented to minimize the psychological burden associated with physical symptoms, whilst public mental health interventions could target adverse mental outcomes associated with the pandemic.

Comparison of optimization algorithms for selecting the fractional frequency in Fourier form unit root tests

We compare the performance of unit root tests which include flexible Fourier trends in their testing processes. The algorithms considered are those of Broyden, Fletcher, Goldfarb and Shanno (BFGS), Berndt, Hall, Hall and Hausman (BHHH), Simplex, Genetic and grid search (GS). The simulation results indicate that derivative-free methods, such as Genetic and Simplex, have advantages over hill-climbing methods, such as BFGS and BHHH in providing accurate fractional frequencies for fractional frequency flexible Fourier form (FFFFF) unit root test. When the parameters are estimated under the alternative hypothesis of the FFFFF type of unit root test, the grid search and derivative-free methods provide unbiased and efficient estimations. We also provide the asymptotic distribution of the FFFFF unit root test. We extend the FFFFF unit root test to a panel version in order to increase the power of the test. Finally, the empirical analyses of Covid19 unit root test show that derivative-free methods, are better than other methods. However, for big data and accurate estimation of the frequency parameters, the Simplex methodology using the bootstrap process is preferred.

Spillovers and diversification potential of bank equity returns from developed and emerging America

We examine the network spillovers, portfolio allocation characteristics and diversification potential of bank returns from developed and emerging America. We draw our results by applying a directional spillover index, the tail-event driven network (TENET) and nonlinear portfolio optimization methods on bank returns. We find that the spillovers and connectedness among banks from emerging America are noticeably smaller than those among banks from developed America. The largest emerging market spillover transmitters and receivers are the banks from Brazil, followed by the banks from Chile. The largest developed market spillover transmitter is JP Morgan Chase. The connectedness among banks from developed America is dominated by the banks from the USA, relative to those from Canada. The total connectedness of the emerging market banks is more intensified than that of the banks from developed America due to the effect of the COVID-19 pandemic. The portfolio optimization shows that in developed America, the largest banks from the USA are the largest risk contributors to total portfolio risk, whereas the banks from Canada contribute the least risk. In emerging America, the banks from Brazil contribute the most risk to total portfolio risk while the banks from Peru and one bank from Colombia contribute the least risk. The portfolio of banks from emerging America offers greater diversification potential and lower total portfolio allocation risk.