Oil prices, US stock return, and the dependence between their quantiles

By Nicholas Sim, Hongtao Zhou. 2015

1,276 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Renewable Energy, Sustainability and the Environment

View Paper: https://www.semanticscholar.org/paper/08ae8f99198b84462e59b3f74df8acc1666bc642

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. Muhammad Shahbaz
2. Elie Bouri
3. Rangan Gupta
4. Syed Jawad Hussain Shahzad
5. Arshian Sharif
6. Avik Sinha
7. David Roubaud
8. Aviral Kumar Tiwari

In Renewable Energy, Sustainability and the Environment

1. Muhammad Shahbaz
2. Avik Sinha
3. Syed Jawad Hussain Shahzad
4. Mantu Kumar Mahalik
5. Arshian Sharif
6. David Roubaud
7. Gazi Salah Uddin
8. Aviral Kumar Tiwari

Citations in the corpus

• Does Bitcoin hedge global uncertainty? Evidence from wavelet-based quantile-in-quantile regressions (2016, methodology): “Hence, rather than using the QRA approach, we follow Sim and Zhou (2015) who propose a QQ approach.”
• Asymmetric Impact of Oil Price Shock on Stock Market in China: A Combination Analysis Based on SVAR Model and NARDL Model (2017, methodology): “Sim and Zhou (2015) have employed the quantile regression technique to analyze the effect of the oil market-specific demand shock on the return of the stock market, and the asymmetry of the effect are discussed. As described above, the nonlinear effect of crude oil price on the stock market has been”
• The marginal impacts of energy prices on carbon price variations: Evidence from a quantile-on-quantile approach (2021, positive): “As briefly mentioned in Section 1, we use the recently developed quantile-on-quantile (QQ) approach (Sim and Zhou, 2015) to investigate the impact of crude oil, natural gas, and coal futures markets on the carbon futures market.”
• The energy consumption and economic growth nexus in top ten energy-consuming countries: Fresh evidence from using the quantile-on-quantile approach (2018, methodology): “In this section, the key features of the model specification of the quantile-on-quantile (QQ) approach recently suggested by Sim and Zhou (2015) are used to study the relationship between energy consumption and economic growth in the top ten energy-consuming countries of the world.”
• Renewable energy, oil prices, and economic activity: A Granger-causality in quantiles analysis (2018, methodology): “To test for Granger-causality in quantiles between conomic variables, some studies applied the Sup-Wald test proposed by Koenker and Machado (1999) on the coefficients of a quantile regression model (see e.g., Chuang et al., 2009; Bastianin et al., 2014; Sim and Zhou, 2015).”
• Oil price shocks, economic policy uncertainty and industry stock returns in China: Asymmetric effects with quantile regression (2017, methodology): “Sim and Zhou (2015) also indicate that oil shocks affect US stock returns depending on market circumstances by using the quantile-on-quantile approach.”