Visibility graph analysis of crude oil futures markets: Insights from the COVID-19 pandemic and Russia-Ukraine conflict (preprint)

Drawing inspiration from the significant impact of the ongoing Russia-Ukraine conflict and the recent COVID-19 pandemic on global financial markets, this study conducts a thorough analysis of three key crude oil futures markets: WTI, Brent, and Shanghai (SC). Employing the visibility graph (VG) methodology, we examine both static and dynamic characteristics using daily and high-frequency data. We identified a clear power-law decay in most VG degree distributions and highlighted the pronounced clustering tendencies within crude oil futures VGs. Our results also confirm an inverse correlation between clustering coefficient and node degree and further reveal that all VGs not only adhere to the small-world property but also exhibit intricate assortative mixing. Through the time-varying characteristics of VGs, we found that WTI and Brent demonstrate aligned behavior, while the SC market, with its unique trading mechanics, deviates. The 5-minute VGs' assortativity coefficient provides a deeper understanding of these markets' reactions to the pandemic and geopolitical events. Furthermore, the differential responses during the COVID-19 and Russia-Ukraine conflict underline the unique sensitivities of each market to global disruptions. Overall, this research offers profound insights into the structure, dynamics, and adaptability of these essential commodities markets in the face of worldwide challenges.

New insights into price drivers of crude oil futures markets: Evidence from quantile ARDL approach (preprint)

This paper investigates the cointegration between possible determinants of crude oil futures prices during the COVID-19 pandemic period. We perform comparative analysis of WTI and newly-launched Shanghai crude oil futures (SC) via the Autoregressive Distributed Lag (ARDL) model and Quantile Autoregressive Distributed Lag (QARDL) model. The empirical results confirm that economic policy uncertainty, stock markets, interest rates and coronavirus panic are important drivers of WTI futures prices. Our findings also suggest that the US and China's stock markets play vital roles in movements of SC futures prices. Meanwhile, CSI300 stock index has a significant positive short-run impact on SC futures prices while S\&P500 prices possess a positive nexus with SC futures prices both in long-run and short-run. Overall, these empirical evidences provide practical implications for investors and policymakers.

Air quality in Nanjing during COVID-19 lockdown period

In order to investigate the impact of COVID-19 lockdown on air quality in Nanjing, the air pollutants observed from January 25 to February 10, in 2020（COVID-19 lockdown period） in Nanjing and its surrounding cities was analyzed. During the lockdown period with poor atmospheric diffusion conditions, the concentrations of PM2.5, PM10, NO2, SO2, and CO decreased obviously, with the value of 36, 44, 5, 22μg/m3 and 1.1 mg/m3, whereasO3 increased by 4%. The net effectiveness of the emission reduction measures was calculated through comparisons of concentrations of air pollutants between and before COVID in the similar meteorological conditions. Concentrations of PM2.5, PM10, SO2, NO2 and CO decreased by 41.7%, 45.3%, 14.3%, 43.5% and 18.2%, respectively, whereasO3 increased by 4.8%. Compared to capital cities of the Yangtze River Delta in the same period, the largest decline of SO2 and the medium decline of the other pollutions were appeared in Nanjing. The diurnal variation concentration of PM2.5 and PM10 changed from double peak to single peak, due to the disappearance of nighttime sub-peak of particle. The concentration ofO3 increased significantly at night, which was resulted from that sharp reduction of traffic sources weaken the titration reaction of NO toO3. The peak ofO3 during the daytime depended on the variation of the ratio of VOCs to NOx due to the emission control.