ABSTRACT
PurposeThis 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/approachTo 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.FindingsThis 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/valueTo 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.
ABSTRACT
This study aims to examine the impact of the different waves of the COVID-19 pandemic on the connectedness of the BRICS (Brazil, Russia, India, China, and South Africa) term structure of interest rates and its components (level, slope and curvature). For that purpose, this research applies the time-varying parameter vector autoregression (TVP-VAR) approach in order to assess the direction of spillovers among countries and factors and measure their contribution to the connectedness system. Our results show that the total connectedness measure changes over time, and the level and curvature components show connectedness that persists longer than the slope component, both in the first wave of the COVID-19 pandemic. Brazil and South Africa would appear as net transmitters of shocks, whereas China and India are net receivers. Finally, the most significant differences in the net dynamic connectedness between transmitters and receivers were focused on before and during the first wave of the COVID-19 pandemic crisis. Some additional impacts were observed during the last waves of the coronavirus pandemic. To our best knowledge, this is the first study on the connectedness between the yield curves of the BRICS economies and the COVID-19 crisis uncertainty according to the coronavirus MCI, by decomposing the yield curve into its factors (level, slope, and curvature).
ABSTRACT
This study aims to examine the impact of the different waves of the COVID-19 pandemic on the connectedness of the BRICS (Brazil, Russia, India, China, and South Africa) term structure of interest rates and its components (level, slope and curvature). For that purpose, this research applies the time-varying parameter vector autoregression (TVP-VAR) approach in order to assess the direction of spillovers among countries and factors and measure their contribution to the connectedness system. Our results show that the total connectedness measure changes over time, and the level and curvature components show connectedness that persists longer than the slope component, both in the first wave of the COVID-19 pandemic. Brazil and South Africa would appear as net transmitters of shocks, whereas China and India are net receivers. Finally, the most significant differences in the net dynamic connectedness between transmitters and receivers were focused on before and during the first wave of the COVID-19 pandemic crisis. Some additional impacts were observed during the last waves of the coronavirus pandemic. To our best knowledge, this is the first study on the connectedness between the yield curves of the BRICS economies and the COVID-19 crisis uncertainty according to the coronavirus MCI, by decomposing the yield curve into its factors (level, slope, and curvature).
ABSTRACT
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.
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We investigate the joint and bivariate return and volatility interdependence between various agricultural commodities and oil price shocks. As an alternative of the Diebold and Yilmaz (2012 and 2014) spillover methodology, this paper proposes the application of the fresh time-varying parameter vector autoregression (TVP-VAR) methodology by Antonakakis and Gabauer (2017) during the sample period between January 7, 2000 and September 17, 2020. In addition, this paper pays special attention to the most relevant periods of economic turbulence among the last 20 years: dotcom bubble, Global Financial Crisis (GFC) and COVID-19 pandemic crisis. About the main results, the directional return and volatility connectedness of oil risk shocks is higher than oil demand shocks and, in turn, higher than oil supply shocks. In addition, the dynamic total return and volatility connectedness changes over time, rising during periods of economic crisis. In general, the net return connectedness considerably increases during the three most important crises. Thus, the differences between transmitters' (Canola and Corn) and receivers’ (Orange Juice, Lean Hog, Sugar and Rubber) agricultural commodity markets are emphasized during the GFC and the COVID-19 pandemic crisis. Finally, the net volatility connectedness measure would not show evidence as clear as the net return connectedness measure.
ABSTRACT
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.