Modeling Oil shocks–Green Investments Nexus: A Global Evidence Based on Wavelet Coherence Technique

This study investigates the interdependence between oil shocks and green investments over time and frequency domains. Using the wavelet coherence approach, our results show evidence of bidirectional causality between all the variants of oil shocks and green investments around the global financial crisis and the 2014-2016 oil crisis. Economic activity shocks significantly Granger-cause green investments during the COVID-19 pandemic. © 2023, Asia-Pacific Applied Economics Association. All rights reserved.

Oil price shocks and inflation: A cross-national examination in the ASEAN5+3 countries

We test interaction between the oil price shocks and inflation in the ASEAN5+3 countries utilizing 35 years of monthly data beginning in 1987–2022. We show that when the COVID-19 pandemic is factored into our sample, oil-specific demand shocks and aggregate demand shocks had a significant impact on inflation in these countries. These findings hint that the COVID-19 pandemic is likely the fundamental cause of the inflationary impact of these shocks. The impact of rising inflation sparked by shocks emanating from oil-specific demand and aggregate demand is evident in Malaysia, Singapore, Thailand, the Philippines, and Japan. We discover evidence that inflation responds asymmetrically to oil price shocks, depending on whether the shocks are positive or negative. Our empirical findings have significant policy implications for policymakers as they provide a reasonable explanation for the ASEAN5+3 countries' inflationary responses to various oil price shocks. © 2023 Elsevier Ltd

The bubble contagion effect between crude oil and oil-exporting stock markets: the case of GCC countries

Purpose: This study aims to investigate the existence of bubbles and their contagion effect in crude oil and stock markets of oil-exporting countries Gulf Cooperation Council (GCC) from 2016 to 2021. Design/methodology/approach: The authors use Generalized Sup augmented Dickey–Fuller (GSADF) and Backward Sup augmented Dickey–Fuller (BSADF) to significantly identify multiple bubbles stock and oil markets with precise dates. Furthermore, the authors check the contagion effect of bubbles between crude oil and GCC stock markets based on the time-varying Granger causality test. Findings: First, the authors find empirical evidence of downwards bubbles in crude oil prices and in all GCC stock indexes (except the Saudi stock index) during the corona virus disease 2019 (COVID-19) outbreak. Second, the authors do not detect empirical evidence of bubble transmission between crude oil markets and GCC stock markets (except with the Dubai Financial Market index). Practical implications: The findings of this study would illuminate policymakers not to limit the factors of systematic financial crises in oil-exporting countries to crude oil and to consider factors such as monetary policy and economic diversification measures. This study has also crucial implications for investors. In fact, investors should not ignore the responses of the stock markets to oil price shocks that are heterogeneous across countries when looking for investment opportunities in the GCC region. Originality/value: The study justifies the changing nature of the bubble contagion effect through the novel implementation of the time-varying Granger causality test to detect whether bubble contagion exists between oil and GCC stock markets and if that does, in which direction. © 2023, Emerald Publishing Limited.

Do oil shocks affect the green bond market?

This study examines the predictive power of oil shocks for the green bond markets. In line with this aim, we investigated the extent to which oil shocks could be used to accurately make in- and out-of-sample forecasts for green bond returns. Three striking findings emanated from our results: First, the three types of oil shock are reliable predictors for green bond indices. Second, the performances of the predictive models were consistent across the different forecasting horizons (i.e. H = 1 to H = 24). Third, our findings were sensitive to classifying the dataset into pre-COVID and COVID eras. For instance, the results confirmed that the predictive power of oil shocks declined during the crisis period. We also discuss some policy implications of this study's findings. © 2022 The Author(s)

Multilayer information spillover networks between oil shocks and banking sectors: Evidence from oil-rich countries

There is no doubt that oil price shocks significantly affect oil-producing countries' macroeconomic fundamentals and financial stability, mainly in crisis times. The recent oil price shocks, coupled with the COVID-19 pandemic, motivated us to investigate the connectedness and risk transmission among oil shocks and banking sectors in the Gulf Cooperation Council (GCC) economies from June 30, 2006, to September 9, 2021. Thus, we construct multilayer information spillover networks between oil price shocks and GCC banking sectors. The empirical results show that the Bahrain banking sector depicts the highest connectedness and risk transmission with oil price shocks on the extreme risk spillover layer. In addition, Kuwait and the United Arab Emirates are highly connected to oil demand shocks. Furthermore, we find a substantial increase in extreme risk spillover and volatility spillover layers during the COVID-19 period. The results of this paper have some important implications for regional portfolio risk management, alleviating systemic risk, and developing hedging and investment strategies.

Do oil shocks affect the green bond market?

This study examines the predictive power of oil shocks for the green bond markets. In line with this aim, we investigated the extent to which oil shocks could be used to accurately make in- and out-of-sample forecasts for green bond returns. Three striking findings emanated from our results: First, the three types of oil shock are reliable predictors for green bond indices. Second, the performances of the predictive models were consistent across the different forecasting horizons (i.e. H = 1 to H = 24). Third, our findings were sensitive to classifying the dataset into pre-COVID and COVID eras. For instance, the results confirmed that the predictive power of oil shocks declined during the crisis period. We also discuss some policy implications of this study's findings.

Network Topology of Dynamic Credit Default Swap Curves of Energy Firms and the Role of Oil Shocks

Using network analysis on the connectedness of default factors in a credit default swap (CDS) dataset of U.S. and European energy firms, we provide the first evidence of differences in the shape and dynamics of the interconnectedness of the level, slope, and curvature, representing long-, short-and middle-term default factors, respectively. The interconnectedness of the three default factors increases during the European sovereign debt crisis (ESDC), whereas only the interconnect-edness of the level factor increases during the oil price crash, and the interconnect-edness of both level and slope factors spikes during COVID19. European firms contribute more to the transmission of long-term and short-term default risk from early 2011 till the beginning of the 2014–2105 oil price crash;afterwards, U.S. firms are major default transmitters despite some periods of parity with European firms. The impacts of oil demand and supply shocks on the various interconnect-edness are quantile-dependent and more pronounced in the long term for the credit risk of the energy firms. © 2022 by the IAEE. All rights reserved.

Nexus between oil shocks and agriculture commodities: Evidence from time and frequency domain

Oil shocks demonstrate an effective economic event in the face of several unprecedented financial challenges. The current study endeavors to investigate the nexus between oil shocks and agriculture commodities with portfolio implications. Building on the novel techniques of time- and frequency spillovers and portfolio analysis, we unlocked the potential connectedness networks as well as diversification and trading strategies for investors and portfolio managers. Our findings document strong intra and weaker inter-connectedness between oil shocks and agriculture commodities with greater time-varying spillovers in the short- and long-run. We framed valuable intuitions for policymakers, macro-prudential authorities, investors, and portfolio managers.

Connectedness and directional spillovers in energy sectors: international evidence

This paper provides a comparative analysis of how the energy-sector stocks of 20 regional blocs (Americas, Australasia, BRIC, Southeast Asia, Scandinavia, Southern Europe, Far East, Europe, European Union, Emerging Europe, Asia, G7, G12, Economic and Monetary Union (EMU), CCARBNS, Latin America, North America, PIIGS, Asia-Pacific and NORCS) are connected from 5 July 1994 to 21 April 2020. It uses various techniques: Diebold and Yilmaz (2014)(DY 2014, hereafter) spillover indices and TVP-VAR, LASSO-VAR. Our main results are as follows: First, the DY approach results show that the biggest net contributor of volatility is the CCARBNS region, followed by the G12 and G7 regions, while the biggest receiver of volatility is the Southeast Asia region. Second, the TVP-VAR and LASSO-VAR results reveal that Scandinavia, Far East, and America's regions are net receivers of energy shocks, with net transmitters being CCARBNS, G7, G12 and Emerging European regions. Third, during the 2007-2008 financial crisis and recent COVID-19 outbreak, energy stock market spillovers have reached unprecedented high levels. Fourth, the world policy uncertainty greatly influenced the magnitude of volatility spillovers across regional energy stock markets.

Emerging markets sovereign CDS spreads during COVID-19: Economics versus epidemiology news.

Can bad news about COVID-19 induce negative expectations on sovereign credit risks? We investigate the factors driving credit default swap (CDS) spreads of emerging market sovereigns around the outbreak of COVID-19. Using 2014-2019 data, we estimate a two-factor model of global and regional risks and then extrapolate the model-implied spreads for the period July 2019-June 2020. Intriguingly, the model initially predicts the realized spreads well but loses predictive accuracy during the COVID-19 pandemic. Fiscal space and oil-revenue dependence primarily drive the differences between the realized and predicted sovereign spreads. Our augmented-factor model indicates that the cumulative COVID-19 mortality rate growth is positively associated with the CDS spreads. The evidence suggests that the epidemiological deterioration can lower confidence in the sovereign credit markets due to the prospects of prolonged lockdowns and a slower GDP growth recovery. Our results also hold for a single regression of daily spread changes during 2014-2020.