ABSTRACT
This paper presents a unique time-varying parameter vector autoregression (TVP-VAR) based extended joint connectedness approach to quantify the connectedness and transmission mechanism of shocks of nine commodities futures returns (namely;Gold and Silver from the category of precious metals;Copper, Lead, Zinc, Nickel and Aluminium from the category of base or industry metals;Natural Gas and Brent Crude Oil from energy sector) obtained from Multi Commodity Exchange of India Limited (MCX) from January 1, 2018 to December 31, 2021. This paper employs Balcilar et al. (2021)'s TVP-VAR extended joint connectedness approach, which combines the TVP-VAR connectedness approach of Antonakakis et al. (2020) with the joint spillover approach of Lastrapes and Wiesen (2021), to investigate the dynamic connectedness among the select commodity futures of interest. Our findings show that system-wide dynamic connectedness varies over time and is driven by economic events. The pandemic shocks appear to have an impact on system-wide dynamic connectedness, which peaks during the COVID-19 pandemic. Crude oil and zinc are the primary net shock transmitters, whereas gold and silver are the primary net shock receivers. We also discovered that the role of aluminum in shock transmitters and shock receivers changed during the course of the investigation. Pairwise connectivity, on the other hand, shows that Zinc, Copper, Nickel, and Crude oil are the key drivers of gold price changes, explaining the network's high degree of interconnectivity. During the study period, it was also discovered that silver has a significant influence on gold. Furthermore, in comparison to natural gas, gold's spillover activity is still relatively modest (on a scale), indicating that gold is less sensitive to market innovations. © 2023 Elsevier Ltd
ABSTRACT
The Covid-19 pandemic has caused a lot of stress and anxiety. This study aims to observe the impact of the demographic variables of age, gender, educational level and area of residence on the anxiety and depression levels due to the pandemic. Data was obtained using a questionnaire to record demographic variables such as Age, Gender, educational level and area of residence. Data was also obtained using a questionnaire that measured questions related to depression and anxiety. Results indicated that age recorded a significant impact of chances for depression. This means that individuals between the age group of <30years had a 3 times greater chance of developing depression due to the pandemic compared to the 30-59 years and >60-year-old age groups. On the other hand, males recorded an increased level of anxiety which was 2.5 times higher than females. © 2022 IEEE.
ABSTRACT
COVID 19, a furious virus, exploded across the globe in 2020. Treatment, tracing and testing are the only way to retain a normal life. But the biggest obstacle is the shortage of proper testing kits which makes life horrendous. As a consequence it demands time to ramp up the development of a suitable test kit. In this scenario we propose a kit that is made up of a two-dimensional (2-D) Si-based photonic crystal structure (PCS) that could distinguish the novel coronaviruses (n-CoV) from ordinary coronaviruses. The principle of identification relies on the reflectance, absorbance and transmittance characteristics at the signal of 412 nm wavelength obtained from a laser diode (LD);moreover, the operational mechanism deals with the manipulation of the signal with the proposed PCS structure which contains the virus solution. Finally, the output transmitted energy differentiates the viruses pertaining to their nature;for example, an output with visible light energy gives an indication of normal flu;on the other hand, output energy within the infrared (IR) range confirms the case of novel coronavirus infection.