Non-Gaussian score-driven conditionally heteroskedastic models with a macroeconomic application

We contribute to the literature on empirical macroeconomic models with time-varying conditional moments, by introducing a heteroskedastic score-driven model with Student's t-distributed innovations, named the heteroskedastic score-driven -QVAR (quasi-vector autoregressive) model. The -QVAR model is a robust nonlinear extension of the VARMA (VAR moving average) model. As an illustration, we apply the heteroskedastic -QVAR model to a dynamic stochastic general equilibrium model, for which we estimate Gaussian-ABCD and -ABCD representations. We use data on economic output, inflation, interest rate, government spending, aggregate productivity, and consumption of the USA for the period of 1954 Q3 to 2022 Q1. Due to the robustness of the heteroskedastic -QVAR model, even including the period of the coronavirus disease of 2019 (COVID-19) pandemic and the start of the Russian invasion of Ukraine, we find a superior statistical performance, lower policy-relevant dynamic effects, and a higher estimation precision of the impulse response function for US gross domestic product growth and US inflation rate, for the heteroskedastic score-driven -ABCD representation rather than for the homoskedastic Gaussian-ABCD representation. © The Author(s), 2023. Published by Cambridge University Press.

Connectedness between the COVID-19 related media coverage and Islamic equities: The role of economic policy uncertainty

This paper examines the static and dynamic return and volatility connectedness among Islamic equity indices and a Coronavirus coverage index over the ongoing COVID-19 pandemic crisis. We employ ten major sectoral equity indices covering main economic sectors and the Coronavirus media coverage index (MCI) and apply the time-varying parameter vector autoregressive methodology (TVP-VAR). The results show a high degree of connectedness between the return and volatility series of the different sectoral indices. Moreover, the information transmission between these indices and the media coverage index shows that Islamic equities are net receivers of shocks from the coronavirus MCI. Additionally, we investigate the causality between the different connectedness measures and the Economic Policy Uncertainty (EPU). Our results indicate that EPU has predictive power on the net connectedness between the Islamic sectoral equities and the Coronavirus MCI. © 2022 Elsevier B.V.

Analysis of the dynamic return and volatility connectedness for non-ferrous industrial metals during the COVID-19 pandemic crisis

Purpose: This paper aims to examine the dynamic return and volatility connectedness for six major industrial metals (tin, lead, nickel, zinc, copper and aluminium) and the coronavirus media coverage index (MCI). Design/methodology/approach: To that purpose, this study applies the fresh time-varying parameter vector autoregression methodology (TVP–VAR model) during the sample period between 2 January, 2020, and 16 April, 2021, that is, covering the three waves of the COVID-19 pandemic crisis. Findings: This study’s results show interesting findings. First, dynamic total return and volatility connectedness changes over time, highlighting a significant increase during the third wave of the pandemic. Second, the MCI index is a leading net transmitter in terms of return and volatility at the introduction of the SARS-CoV-2 coronavirus crisis. Third, this study clearly distinguishes two profiles among industrial metals: copper and tin/zinc as net transmitters and lead and aluminium as net receivers. Finally, the most relevant differences between them are concentrated not only at the beginning of the COVID-19 pandemic (first wave) but also during the second and third waves of the coronavirus outbreak. Originality/value: To the best of the authors’ knowledge, this is the first research that explores the dynamic return and volatility connectedness in the industrial metal market, applying the TVP–VAR methodology during the first waves of the COVID-19 pandemic crisis. © 2022, Emerald Publishing Limited.

Oil price shocks and the return and volatility spillover between industrial and precious metals star

This study explores the dynamic return and volatility connectedness for some dominant industrial (Aluminium, Copper, Lead, Nickel, Tin, and Zinc) and precious metals (Gold, Palladium, Platinum, Silver) to crude oil shocks (risk, demand, and supply) during the sample period between January 2, 2009 and July 17, 2020. Our findings indicate that, demand shocks and risk shocks are the dominant receiver (transmitter) of shocks from (to) for metal returns. Second, we document the time-varying nature of both total return and volatility connectedness. Third, both net directional return and volatility connectedness show that some metals such as Tin, Gold and, even, Nickel, Lead and Aluminium appear as net transmitters, at least in some intervals of the sample period analysed. On the other hand, other industrial and precious metal markets show a net receiver profile, such as Copper, Zinc and Platinum, among others. Lastly, we find more differences between the net dynamic connectedness of the metal markets analysed in terms of return than volatility. The net directional volatility connectedness increases sizably during the global crisis due to the spread of the SARS-CoV-2 coronavirus. (c) 2021 Elsevier B.V. All rights reserved.