scholarly journals Research on Time-Varying Two-Way Spillover Effects Between Carbon and Energy Markets: Empirical Evidence From China

2021 ◽  
Vol 9 ◽  
Author(s):  
Sen Qiao ◽  
Chen Xi Zhao ◽  
Kai Quan Zhang ◽  
Zheng Yu Ren
Keyword(s):  
Crude Oil ◽  
Spillover Effect ◽  
Energy Markets ◽  
Carbon Market ◽  
Energy Market ◽  
Time Varying ◽  
Carbon Markets ◽  
Oil Futures ◽  
New Energy ◽  
Crude Oil Futures

With the improvement of China’s carbon emission trading system, the spillover effect between carbon and energy markets is becoming more and more prominent. This paper selects four representative pilot carbon markets, including Beijing (BEA), Guangdong (GDEA), Hubei (HBEA) and Shanghai (SHEA). And three representative energy markets, including Crude Oil Futures (SC), power index (L11655) and China Securities new energy index (NEI). Combining the rolling window technology with DY spillover index, set a 50-weeks rolling window to measure the spillover index, and deeply analyze the time-varying two-way spillover effect between China’s carbon and energy markets. The results show that the spillover effect between China’s carbon and energy markets has significant time variability and two-way asymmetry. The time-varying spillover effect of different carbon pilot markets on the energy market has regional heterogeneity. The volatility spillover effect of Beijing and Shanghai carbon markets mainly comes from the crude oil futures market, Guangdong carbon market mainly comes from the new energy market, and Hubei carbon market mainly comes from crude oil and electricity market. The above research results contribute to the prevention of potential risk spillover between carbon and energy markets, which can promote the establishment of China’s unified carbon market and the prevention of systemic financial risks in energy market.

scholarly journals Volatility Spillover Effect of International Crude Oil Futures and China-Russia Stock Market: A Multivariate BEKK-GARCH Model Based on Wavelet Multiresolution Analysis

2019 ◽  
Vol 11 (1) ◽  
pp. 183
Author(s):  
Maoguo Wu ◽  
Daimin Lu
Keyword(s):  
Stock Market ◽  
Crude Oil ◽  
Explanatory Power ◽  
Composite Index ◽  
Spillover Effect ◽  
Stock Index ◽  
Oil Futures ◽  
Crude Oil Futures ◽  
Futures Price ◽  
Volatility Spillover Effect

The increasingly prominent strategic position of crude oil determines its high impact on macro-economy. The value of crude oil is reflected in the price of crude oil futures. Stock market is the barometer of macro economy. To what extent does international crude oil futures price affect stock market? China and Russia are the biggest importer and exporter of crude oil, respectively. Crude oil is of strategic value to both countries. This study empirically investigates the volatility spillover effect of international crude oil futures and China-Russia stock market from April 24th, 2015 to April 20th, 2018, based on the data of international crude oil futures prices, China-Russia stock market composite index, and industry stock index. The empirical results show that there is a short-term relationship between China-Russia stock market composite index and international crude oil futures price. The international crude oil futures price has a greater explanatory power to Russian RTS index, but a smaller explanatory power to Shanghai composite index. All industry stock indices are cointegrated with international crude oil futures prices. Except for China industry and Russia energy, the adjustment coefficient of international crude oil futures price on stock index volatility of other industries is insignificant. This study mainly studies the relationship between international crude oil futures price and the comprehensive stock index and industry stock index of China and Russia, and compares the impact of international crude oil futures price on the stock market of the largest importer and the largest exporter of crude oil to explore the linkage between crude oil futures price and stock market, and puts forward policy implications based on the empirical results.

Unbiasedness and time varying risk premia in the crude oil futures market

1994 ◽  
Vol 16 (2) ◽  
pp. 99-105 ◽  
Author(s):  
Imad A. Moosa ◽  
Nabeel E. Al-Loughani
Keyword(s):  
Crude Oil ◽  
Futures Market ◽  
Risk Premia ◽  
Time Varying ◽  
Oil Futures ◽  
Crude Oil Futures

scholarly journals The Volatility Spillover Effect Between the International Crude Oil Futures Price and China’s Stock Market - Multivariate BEKK-GARCH Model Based on Wavelet Multiresolution

2019 ◽  
Vol 10 (4) ◽  
pp. 84
Author(s):  
Maoguo Wu ◽  
Zhehao Zhu
Keyword(s):  
Stock Market ◽  
Crude Oil ◽  
Spillover Effect ◽  
Garch Model ◽  
Futures Market ◽  
Volatility Spillover ◽  
Oil Futures ◽  
Model Based ◽  
Crude Oil Futures ◽  
Volatility Spillover Effect

This study aims to analyze the volatility spillover effect between the international crude oil futures market and China’s stock market. Using West Texas Intermediate (WTI) and the Shanghai Composite Index (SSEC) to represent the international crude oil futures market and China’s stock market respectively, this study selects data of WTI and the SSEC from August 10, 2007 to August 10, 2017. It processes these data via wavelet multiresolution to decompose them into different levels and then builds the data model based on the BEKK-GARCH model. By testing the parameters through the Wald test, it further explores whether the volatility spillover effect exists between WTI and the SSEC. Empirical evidence finds that the volatility spillover effect between WTI and the SSEC is significant in the short run, while, however, such a volatility spillover effect does not exist in the medium and long term.

scholarly journals Time-Varying Optimal Hedge Ratio for Brent Oil Market

2015 ◽  
Vol 56 ◽  
pp. 103-106
Author(s):  
Mohsen Mehrara ◽  
Monire Hamldar
Keyword(s):  
Crude Oil ◽  
Garch Model ◽  
Time Varying ◽  
Oil Futures ◽  
Hedge Ratio ◽  
Oil Market ◽  
Hedging Ratio ◽  
Daily Data ◽  
Crude Oil Futures ◽  
Optimal Hedge

This paper examines the optimal hedging ratio (OHR) for the Brent Crude Oil Futures using daily data over the period 1990/17/8-2014/11/3. To estimate OHR, we employ multivariate BEKK MV-GARCH model. At last, the efficiency of this approach are compared with the constant OHR captured from OLS through Edrington's index.

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