Network diffusion of international oil volatility risk in China's stock market: Quantile interconnectedness modelling and shock decomposition analysis

Huang, Jionghao; Li, Ziruo; Xia, Xiaohua

doi:10.1016/j.iref.2021.04.034

Cited by 8 publications

(2 citation statements)

References 106 publications

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“… Goodell, 2020 , Huang et al, 2021 , Le et al, 2021 , Maghyereh and Abdoh, 2022 , Ashfaq et al, 2020 , Shah and Dar, 2021 , Zhang and Hamori, 2021 …”

Section: Uncited Referencesmentioning

confidence: 99%

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

Huang

Chen

et al. 2023

Finance Research Letters

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“… Goodell, 2020 , Huang et al, 2021 , Le et al, 2021 , Maghyereh and Abdoh, 2022 , Ashfaq et al, 2020 , Shah and Dar, 2021 , Zhang and Hamori, 2021 …”

Section: Uncited Referencesmentioning

confidence: 99%

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

Huang

Chen

et al. 2023

Finance Research Letters

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“…Ahmed and Huo (2021) consider the volatility dynamic relationship between the Chinese stock market, commodity markets and global oil prices through a trivariate VAR-BEKK-GARCH model, and display a bidirectional spillover between oil and stock markets. Huang et al (2021) indicate a significant network volatility spillover between the stock market and oil volatility risk using a quantile model. Hernandez et al (2022) utilize a nonlinear Granger causality test to show spillover effects between stock market volatility and oil market volatility.…”

Section: Literature Reviewmentioning

confidence: 98%

Uncertainty‐driven oil volatility risk premium and international stock market volatility forecasting

Tong

Miao

et al. 2022

Journal of Forecasting

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Forecasting international stock market volatility using the oil volatility risk premium (OVRP) is important for asset allocation and financial risk management. In previous literature, the issue of biased OVRP has not been well addressed. The OVRP is defined as the difference between the ex ante risk‐neutral expectation of oil return variation and the oil realized variance. This is a biased estimator as argued by previous studies. In this paper, we propose a new measure of OVRP, namely, the uncertainty‐driven OVRP (UOVRP), in which the expected realized variation is the conditional variance of oil futures returns estimated by a typical GARCH‐MIDAS model, and the long‐term volatility component of conditional variance is directly determined by several uncertainty indices. Using heterogeneous autoregressive models (HAR), we find that UOVRPs significantly and positively predict most of the international stock market volatility in‐sample. Furthermore, it significantly outperforms the realized volatility, the “model‐free” OVRP, and recently proposed volatility predictors for most American, European, and Pacific markets out‐of‐sample. On average, UOVRPs driven by the world uncertainty index and the U.S. economic policy uncertainty perform the best among all UOVRPs. The predictive ability of UOVRPs is robust across a series of checks.

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Extreme risk contagion between international crude oil and China's energy-intensive sectors: New evidence from quantile Granger causality and spillover methods

Chen,

Sun

2023

Energy

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Network diffusion of international oil volatility risk in China's stock market: Quantile interconnectedness modelling and shock decomposition analysis

Cited by 8 publications

References 106 publications

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

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

Uncertainty‐driven oil volatility risk premium and international stock market volatility forecasting

Extreme risk contagion between international crude oil and China's energy-intensive sectors: New evidence from quantile Granger causality and spillover methods

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