Time-frequency connectedness of crude oil, economic policy uncertainty and Chinese commodity markets: Evidence from rolling window analysis

Zhu, Huiming; Chen, Weiyan; Hau, Liya; Chen, Qitong

doi:10.1016/j.najef.2021.101447

Cited by 51 publications

(16 citation statements)

References 48 publications

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“…Considering the spillover may be sensitive to the size of the rolling window ( Zhu et al, 2021 ), we change the size of the rolling window (50 days, 100 days, 150 days) for robustness testing. Table 10 exhibits that total connectedness is larger in the short-run than in the long-run.…”

Section: Robustness Testmentioning

confidence: 99%

The time-frequency connectedness among metal, energy and carbon markets pre and during COVID-19 outbreak

Jiang

Chen

2022

Resources Policy

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Section: Robustness Testmentioning

confidence: 99%

The time-frequency connectedness among metal, energy and carbon markets pre and during COVID-19 outbreak

Jiang

Chen

2022

Resources Policy

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“…Qiao et al (2022) found that there is an interaction between economic policy uncertainty (EPU) and high-risk assets using time-varying parameter vector autoregression. According to Zhu et al (2021), the interconnection among EPU, crude oil, and commodities futures increases as the scale expands but decreases in the ultralong horizon.…”

Section: Introductionmentioning

confidence: 99%

Exploring the Asymmetric Effects of Economic Policy Uncertainty and Implied Volatilities on Energy Futures Returns: Novel Insights From Quantile-on-Quantile Regression

Bossman

Gherghina

Asafo−Adjei

et al. 2022

Journal of Business Economics and Management

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This study examined the asymmetric effects of major uncertainty and volatility indices (economic policy uncertainty, Chicago Board Options Exchange crude oil volatility, CBOE volatility index, CBOE VIX volatility, and NASDAQ 100 volatility target) on the returns of global energy and its constituents (global energy index, Brent, heating oil, natural gas, and petroleum). The causalityin-quantiles test and the quantile-on-quantile regression technique were employed on daily data covering the period between April 2012 and March 2022. The findings evidenced asymmetries and heterogeneity in the causal effects of global uncertainty and market volatilities on energy markets. For all uncertainty and volatility measures, we found strong negative relationships with energy commodities at stressed conditions, signalling some hedging benefits for market participants. The current research is among the first investigations to explore the asymmetric relationships between major uncertainty and volatility indices, as well as global energy and its constituents. Essential portfolio implications of our findings are discussed.

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“…Second, EPU brings greater operational risk to trading markets, including but not limited to green technology markets and carbon trading markets (Wang et al 2022). In addition, EPU can also affect energy markets (Qin et al 2020, Zhu et al 2021 and carbon trading markets (Adekoya et al 2021, by exacerbating market volatility and increasing the risk. Volatility in such markets may in turn increase EPU, creating a vicious cycle (Su et al 2021).…”

Section: Environmental Impact Of Epumentioning

confidence: 99%

Prediction of Post-COVID-19 economic and environmental policy and recovery based on recurrent neural network and long short-term memory network

Xiong²,

Chen³

et al. 2022

Environ. Res. Commun.

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COVID-19 has brought significant impacts on the global economy and environment. The Global Economic-and-environmental Policy Uncertainty (GEPU) index is a critical indicator to measure the uncertainty of global economic policies. Its prediction provides evidence for the good prospect of global economic and environmental policy and recovery. This is the first study using the monthly data of GEPU from January 1997 to January 2022 to predict the GEPU index after the COVID-19 pandemic. Both Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) models have been adopted to predict the GEPU. In general, the RNN outperforms the LSTM networks, and most results suggest that the GEPU index will remain stable or decline in the coming year. A few results point to the possibility of a short-term increase in GEPU, but still far from its two peaks during the first year of the COVID-19 pandemic. This forecast confirms that the impact of the epidemic on global economic and environmental policy will continue to wane. Lower economic and environmental policy uncertainty facilitates global economic and environmental recovery. Economic recovery brings more opportunities and a stable macroeconomic environment, which is a positive sign for both investors and businesses. Meanwhile, for the ecological environment, the declining GEPU index marks a gradual reduction in the direct impact of policy uncertainty on sustainable development, but the indirect environmental impact of uncertainty may remain in the long run. Our prediction also provides a reference for subsequent policy formulation and related research.

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Time-frequency connectedness of crude oil, economic policy uncertainty and Chinese commodity markets: Evidence from rolling window analysis

Cited by 51 publications

References 48 publications

The time-frequency connectedness among metal, energy and carbon markets pre and during COVID-19 outbreak

The time-frequency connectedness among metal, energy and carbon markets pre and during COVID-19 outbreak

Exploring the Asymmetric Effects of Economic Policy Uncertainty and Implied Volatilities on Energy Futures Returns: Novel Insights From Quantile-on-Quantile Regression

Prediction of Post-COVID-19 economic and environmental policy and recovery based on recurrent neural network and long short-term memory network

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