Time-frequency volatility transmission among energy commodities and financial markets during the COVID-19 pandemic: A Novel TVP-VAR frequency connectedness approach

Huang, Jionghao; Chen, Baifan; Xu, Yushi; Xia, Xiaohua

doi:10.1016/j.frl.2023.103634

Cited by 25 publications

(9 citation statements)

References 36 publications

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“…Similarly, a long-term volatility transmission related to cryptocurrency consumption is predominantly involved. These findings align with previous studies conducted by Chen, Xu, and Peng (2022) and Huang et al (2023), which also documented a long-term pattern of volatility transmission. These results suggest that the global pandemic and geopolitical tensions may have caused a fundamental change in investor expectations, leading to an increase in long-term uncertainty and systemic risk.…”

Section: Total Average Dynamic Connectednesssupporting

confidence: 92%

“…For a better understanding of the influence of the Russia-Ukraine conflict on these interconnections across the network of markets, we lead a more dynamic analytical framework that considers the changing nature of the TACI over time (depicted with black color) and reflects how the roles of the studied markets within the network evolve illustrated in Figure 3. The dominance of low-frequency response to shocks primarily drives the total volatility spillover, which aligns with the findings of Huang et al (2023). In addition, we noticed a sharp increase in TACI in late December 2019, coinciding with the COVID-19 epidemic spreading rapidly worldwide, causing turmoil in the global financial market.…”

Section: Total Dynamic Connectednesssupporting

confidence: 87%

“…The considerable level of volatility transmission observed during the geopolitical tensions caused by the recent Russia-Ukraine conflict aligns with the findings of Ha and Nham (2022), Huang et al (2023) and Le (2023). These studies gave evidence of a considerable transmission of volatility between fuel and renewable energy markets.…”

Section: Total Average Dynamic Connectednesssupporting

confidence: 80%

“…Using the novel time-varying parameter vector autoregression (TVP-VAR) frequency connectedness approach, we can conduct a more informative analysis of spillovers under different market states, including bear, normal and bull market conditions. This methodology improves the prediction accuracy of the time-series models (Huang, Chen, Xu, & Xia, 2023).…”

Section: Agjsrmentioning

confidence: 97%

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Reconceptualizing the interplay between geopolitical index, green financial assets and renewable energy markets: evidence from the machine learning approach

Jarboui,

Mnif,

Zghidi

et al. 2024

AGJSR

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PurposeIn an era marked by heightened geopolitical uncertainties, such as international conflicts and economic instability, the dynamics of energy markets assume paramount importance. Our study delves into this complex backdrop, focusing on the intricate interplay the between traditional and emerging energy sectors.Design/methodology/approachThis study analyzes the interconnections among green financial assets, renewable energy markets, the geopolitical risk index and cryptocurrency carbon emissions from December 19, 2017 to February 15, 2023. We investigate these relationships using a novel time-frequency connectedness approach and machine learning methodology.FindingsOur findings reveal that green energy stocks, except the PBW, exhibit the highest net transmission of volatility, followed by COAL. In contrast, CARBON emerges as the primary net recipient of volatility, followed by fuel energy assets. The frequency decomposition results also indicate that the long-term components serve as the primary source of directional volatility spillover, suggesting that volatility transmission among green stocks and energy assets tends to occur over a more extended period. The SHapley additive exPlanations (SHAP) results show that the green and fuel energy markets are negatively connected with geopolitical risks (GPRs). The results obtained through the SHAP analysis confirm the novel time-varying parameter vector autoregressive (TVP-VAR) frequency connectedness findings. The CARBON and PBW markets consistently experience spillover shocks from other markets in short and long-term horizons. The role of crude oil as a receiver or transmitter of shocks varies over time.Originality/valueGreen financial assets and clean energy play significant roles in the financial markets and reduce geopolitical risk. Our study employs a time-frequency connectedness approach to assess the interconnections among four markets' families: fuel, renewable energy, green stocks and carbon markets. We utilize the novel TVP-VAR approach, which allows for flexibility and enables us to measure net pairwise connectedness in both short and long-term horizons.

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Section: Total Average Dynamic Connectednesssupporting

confidence: 92%

Section: Total Dynamic Connectednesssupporting

confidence: 87%

Section: Total Average Dynamic Connectednesssupporting

confidence: 80%

Section: Agjsrmentioning

confidence: 97%

See 2 more Smart Citations

Reconceptualizing the interplay between geopolitical index, green financial assets and renewable energy markets: evidence from the machine learning approach

Jarboui,

Mnif,

Zghidi

et al. 2024

AGJSR

View full text Add to dashboard Cite

show abstract

“…Although each commodity market responds to specific shocks (Baffes and Nagle 2022), the financialization of commodities (Cheng and Xiong 2014) has been accompanied by stronger cross-market linkages and, thus, an increase in volatility spillovers among commodity markets (Mandacı et al 2020;Bouri et al 2021a, b;Shahzad et al 2021). According to existing literature, the global crisis triggered an increase in the connectedness between commodity prices (Sari et al 2010;Zhang and Wei 2010;Ahmadi et al 2016;Kang et al 2017;Luo and Ji 2018;Umar et al 2019Umar et al , 2021Zhang and Broadstock 2020;Jebabli et al 2021;Farid et al 2021;Lin and Su 2021;Hung 2021;Balcilar et al 2021;Apergis et al 2022;Huang et al 2023;Zhang et al 2023;Cunado et al 2023), implying a reduction in diversification opportunities for investors. We pay particular attention to the volatility spillovers between energy and metal commodities before and after the Coronavirus disease of 2019 (COVID-19) pandemic, as this pandemic is one of the most important sources of uncertainty.…”

Section: Introductionmentioning

confidence: 99%

Realized volatility spillovers between energy and metal markets: a time-varying connectedness approach

Cunado,

Gabauer,

Gupta

2024

Financ Innov

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This paper analyzes the degree of dynamic connectedness between energy and metal commodity prices in the pre and post-COVID-19 era, using the time-varying parameter vector autoregressive connectedness approach of Antonakakis et al. (J Risk Financ Manag 13(4):84, 2020). The results suggest that market interconnectedness increased slightly following the outbreak of COVID-19, although this increase was lower and less persistent than that observed after the Global Financial Crisis of 2008. Furthermore, we find that crude oil was the main net transmitter of shocks before COVID-19 while heating oil, gold, and silver were the main net transmitters of shocks during the COVID-19 pandemic. In contrast, natural gas and palladium were the main net receivers of shocks during the entire sample period, making these two commodities attractive hedging and safe haven options for investors during the pandemic. Overall, our results suggest that hedging and diversification opportunities decrease during crises. Furthermore, they indicate that accurate forecasts of the volatility of several commodities, such as natural gas and different metals, can be obtained by exploiting the information content of crude oil. However, they also reveal that crude oil lost its leading position as a net shock transmitter during the COVID-19 pandemic.

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Volatility Transmission Role of Indian Equity and Commodity Markets

Kaur,

Chaudhary

2024

Deep Learning Tools for Predicting Stock Market Movements

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Time-frequency volatility transmission among energy commodities and financial markets during the COVID-19 pandemic: A Novel TVP-VAR frequency connectedness approach

Cited by 25 publications

References 36 publications

Reconceptualizing the interplay between geopolitical index, green financial assets and renewable energy markets: evidence from the machine learning approach

Reconceptualizing the interplay between geopolitical index, green financial assets and renewable energy markets: evidence from the machine learning approach

Realized volatility spillovers between energy and metal markets: a time-varying connectedness approach

Volatility Transmission Role of Indian Equity and Commodity Markets

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