Shift contagion and minimum causal intensity portfolio during the COVID-19 and the ongoing Russia-Ukraine conflict

Using the TYDL causality test, this paper attempts (i) to investigate the existence of shift contagion among a large spectrum of financial markets during recent stress and stress-free periods and (ii) to propose a new approach of portfolio management based on the minimization of the causal intensity. During the COVID-19 crisis period, the shift contagion analysis not only reveal a tripling of the causal links between the markets studied, but also a change in the causal structure. Beyond the initial impact of the COVID-19 crisis on financial markets, policy interventions seem to have helped in reassuring market participants that the further spread of financial stress would be mitigated. However, the Russian-Ukrainian conflict, and the high degree of uncertainty it entailed, has again exacerbated the interdependencies between financial markets. In terms of portfolio analysis, our minimum-causal-intensity approach records a lower (respectively higher) reward-to-volatility ratio than the Markowitz (1952 & 1959) minimum-variance traditional approach during the pre-COVID-19 (respectively pre-war) period. On the other hand, both approaches, the one we propose in this paper and the minimum-variance approach, record negative reward-to-volatility ratios during crisis periods.

Predictive modeling and analysis of air quality - Visualizing before and during COVID-19 scenarios

Quality air to breathe is the basic necessity for an individual and in recent times, emission from various sources caused by human activities has resulted in substantial degradation in the air quality. This work focuses to study the inadvertent effect of COVID-19 lockdown on air pollution. Pollutants' concentration before- and during- COVID-19 lockdown is captured to understand the variation in air quality. Firstly, multi-pollutant profiling using hierarchical cluster analysis of pollutants' concentration is performed that highlights the differences in the cluster compositions between before- and during-lockdown time periods. Results show that the particulate matter (PM₁₀ and PM_2.5) in air that formed the primary cluster before lock-down, came down to close similarity with other clusters during lockdown. Secondly, predicting air quality index (AQI) based on the forecasts of pollutants' concentration is performed using neural networks, support vector machine, decision tree, random forest, and boosting algorithms. The best-fitted models representing AQI is identified separately for before- and during-lockdown time periods based on its predictive power. While deterministic method reactively evaluates present AQI when current pollutants' concentration at a particular time and place are known, this study uses the best fitted data-driven model to determine future AQIs based on the forecasts of pollutant's concentration accurately (overall RMSE<0.1 for before lockdown scenario and <0.3 for during lockdown scenario). The study contributes to visualize the variation in pollutants' concentrations between the two scenarios. The results show that the reduced economic activities during lockdown period had led to the drop in concentration of PM₁₀ and PM_2.5 by 27% and 50% on an average. The findings of this study have practical and societal implications and serve as a reference mechanism for policymakers and governing bodies to revise their actions plans for regulating individual air pollutants in the atmospheric air.

The Impact of COVID-19 pandemic on Islamic and conventional financial markets: International empirical evidence

The current global COVID-19 pandemic is adversely affecting financial markets, including commodities, conventional stocks, and Islamic stocks. This paper empirically investigates the extent to which COVID-19 effects may drive interdependence in markets. We fit copulas to pairs of returns before and during the ongoing epidemic shock, analyze the observed changes in the dependence structure, and discuss asymmetries on the propagation of crisis. We also use the findings to construct portfolios possessing desirable expected behavior. We find that the dependence structure changes significantly during the global pandemic providing valuable information on how the COVID-19 crisis affects inter-dependencies. The selected portfolio, including gold and Islamic return indices, has the best performance outside the COVID-19 crisis, and slightly more performing during the bear markets validating gold's intrinsic characteristic to be a safe haven. However, the portfolio performances, when combining the Brent with Islamic or conventional indices, have the same trend for the whole period. Our findings contribute to help investors better adjust their investment strategies.

Emerging and advanced economies markets behaviour during the COVID‐19 crisis era

This article examines the consequences of the COVID‐19 crisis on the interdependencies between emerging and advanced economies. Using daily market index data from 22 developed and emerging markets, we develop a combination of statistical methods based on Diebold and Yilmaz spillover index and Toda–Yamamoto and Dolado and Lütkepohl causality approach. The results substantiate an increase in the interdependence between emerging and advances economies, which suggests an increase in the transmission of the stress and uncertainty between financial markets during the pandemic period. Our findings show that the emerging countries are affected by the financial markets of advanced economies during the COVID‐19 crisis and, in particular, by European markets, which appear to be the primary driver of contagion and transmission of stress and uncertainty to all other regional markets.

The unprecedented reaction of equity and commodity markets to COVID-19

Using a drifting spillover index approach (Diebold and Yilmaz, 2012) and a continuous time-frequency tool (Torrence and Webster, 1999), this paper attempts an empirical investigation of the spillovers and co-movements among commodity and stock prices in the major oil-producing and consuming countries. While our results point to the existence of a significant interdependence among the markets considered, Chinese and Saudi Arabian stock markets seem to be weakly integrated into the world market. Moreover, the spillovers are time-varying and reached their highest levels during the COVID-19 medical shock.

Economic growth and environment in the United Kingdom: robust evidence using more than 250 years data

Using a long span of data (from 1751 to 2016), this paper empirically investigates the relationship between carbon dioxide (CO₂) emissions and economic growth (real GDP per capita) in the United Kingdom. The empirical results provide strong support for the existence of an Environmental Kuznets Curve (EKC) in the UK, i.e., an inverted U-shaped relationship between CO₂ emissions and economic growth, with turning point estimated around the mid-twentieth century. This turning point corresponds with the introduction of changes in environmental standards and policies, which reflects the regulatory efforts to limit pollution by reducing the discharge of grit into the atmosphere, as well as the decline in the use of coal as source of energy, which reflects the country willingness to ensure the energy transition necessary for sustainable development.

Temporary restorative materials: properties and uses

Various materials used for temporary restorations are reviewed, with reference to their chemical and physical properties. Research and standard specifications should be instituted in order to standardize and improve the many products now available to the profession. Knowledge of the materials and their properties will enable the dentist to arrive at correct selection of the material for each case, thus promoting more successful clinical procedures.