Time varying correlation structure of Chinese stock market of crude oil related companies greatly influenced by external factors

2019 ◽  
Vol 530 ◽  
pp. 121086 ◽  
Author(s):  
Leyang Xue ◽  
Feier Chen ◽  
Siqing Guo ◽  
Guiyuan Fu ◽  
Tingyi Li ◽  
...  
Keyword(s):  
Stock Market ◽  
Crude Oil ◽  
External Factors ◽  
Correlation Structure ◽  
Time Varying ◽  
Chinese Stock Market

The optimal thermal causal path analysis on the relationship between international crude oil price and stock market

Kybernetes ◽  
2018 ◽  
Vol 47 (6) ◽  
pp. 1242-1261 ◽  
Author(s):  
Can Zhong Yao ◽  
Peng Cheng Kuang ◽  
Ji Nan Lin
Keyword(s):  
Stock Market ◽  
Crude Oil ◽  
Stock Markets ◽  
Oil Prices ◽  
Oil Price ◽  
Chinese Stock Market ◽  
Crude Oil Price ◽  
Content Type ◽  
Crude Oil Prices ◽  
Causal Path

Purpose The purpose of this study is to reveal the lead–lag structure between international crude oil price and stock markets. Design/methodology/approach The methods used for this study are as follows: empirical mode decomposition; shift-window-based Pearson coefficient and thermal causal path method. Findings The fluctuation characteristic of Chinese stock market before 2010 is very similar to international crude oil prices. After 2010, their fluctuation patterns are significantly different from each other. The two stock markets significantly led international crude oil prices, revealing varying lead–lag orders among stock markets. During 2000 and 2004, the stock markets significantly led international crude oil prices but they are less distinct from the lead–lag orders. After 2004, the effects changed so that the leading effect of Shanghai composite index remains no longer significant, and after 2012, S&P index just significantly lagged behind the international crude oil prices. Originality/value China and the US stock markets develop different pattens to handle the crude oil prices fluctuation after finance crisis in 1998.

TIME-VARYING LONG MEMORIES OF THE CHINESE CURRENCY AND STOCK MARKETS BASED ON THE HURST EXPONENT

2014 ◽  
Vol 13 (01) ◽  
pp. 1450007 ◽  
Author(s):  
CAO GUANGXI ◽  
HAN YAN ◽  
CUI WEIJUN
Keyword(s):  
Exchange Rate ◽  
Stock Market ◽  
Stock Markets ◽  
Hurst Exponent ◽  
Composite Index ◽  
Fluctuation Analysis ◽  
Time Varying ◽  
Chinese Stock Market ◽  
Currency Market ◽  
Cointegration Tests

Based on the daily return and volatility series of the Chinese yuan (RMB)/US dollar (USD) exchange rate and the Shanghai Stock Composite Index, the time-varying long memories of the Chinese currency and stock markets are investigated by comprehensively using the rescaled range (R/S), the modified R/S, and the detrended fluctuation analysis methods. According to the results drawn: (1) the efficiency of the Chinese currency market has not improved significantly, whereas the efficiency of the Chinese stock market has improved steadily, (2) volatility series presents longer memory than return series either in the Chinese currency or stock market and (3) the time-varying Hurst exponent of the Chinese currency market is sensitive to the reform that enhances the flexibility of the RMB exchange rate. Moreover, we find that short-term bidirectional Granger causal relationship exists, but no long-run equilibrium relationship between the time-varying Hurst exponents of the Chinese currency and stock markets was found based on the Granger causality and cointegration tests, respectively.

New results on the predictive value of crude oil for US stock returns

2018 ◽  
Vol 35 (1) ◽  
pp. 97-108 ◽  
Author(s):  
Matt Brigida
Keyword(s):  
Stock Market ◽  
Crude Oil ◽  
State Space ◽  
Risk Premia ◽  
Time Varying ◽  
Content Type ◽  
Varying Coefficients ◽  
The Us ◽  
The Relationship ◽  
Predictive Relationship

Purpose The purpose of this study is to clarify the nature of the predictive relationship between crude oil and the US stock market, with particular attention to whether this relationship is driven by time-varying risk premia. Design/methodology/approach The authors formulate the predictive regression as a state-space model and estimate the time-varying coefficients via the Kalman filter and prediction-error decomposition. Findings The authors find that the nature of the predictive relationship between crude oil and the US stock market changed in the latter half of 2008. After mid-2008, the predictive relationship switched signs and exhibited characteristics which make it much more likely that the predictive relationship is due to time-varying risk premia rather than a market inefficiency. Originality/value The authors apply a state-space approach to modeling the predictive relationship. This allows one to watch the evolution of the predictive relationship over time. In particular, the authors identify a dramatic shift in the relationship around August 2008. Prior research has not been able to identify shifts in the relationship.

scholarly journals Half-day trading and spillovers

2021 ◽  
Vol 15 (1) ◽  
Author(s):  
Yifan Chen ◽  
Limin Yu ◽  
Jianhua Gang
Keyword(s):  
Stock Market ◽  
Spillover Effects ◽  
The United States ◽  
Time Varying ◽  
Chinese Stock Market ◽  
Conditional Correlation ◽  
Day Trading ◽  
Market Impacts ◽  
Positive Spillover ◽  
The U.S

AbstractThis paper investigates the linkage of returns and volatilities between the United States and Chinese stock markets from January 2010 to March 2020. We use the dynamic conditional correlation (DCC) and asymmetric Baba–Engle–Kraft–Kroner (BEKK) GARCH models to calculate the time-varying correlations of these two markets and examine the return and volatility spillover effects between these two markets. The empirical results show that there are only unidirectional return spillovers from the U.S. stock market to the Chinese stock market. The U.S. stock market has a consistently positive spillover to China’s next day’s morning trading, but its impact on China’s next day’s afternoon trading appears to be insignificant. This finding implies that information in the U.S. stock market impacts the performance of the Chinese stock market differently in distinct semi-day trading. Moreover, with respect to the volatility, there are significant bidirectional spillover effects between these two markets.

Spillover effects between energies, gold, and stock: the United States versus China

2020 ◽  
Vol 31 (8) ◽  
pp. 1416-1447 ◽  
Author(s):  
Xie He ◽  
Tetsuya Takiguchi ◽  
Tadahiro Nakajima ◽  
Shigeyuki Hamori
Keyword(s):  
United States ◽  
Stock Market ◽  
Crude Oil ◽  
Spillover Effect ◽  
The United States ◽  
Commodity Markets ◽  
Volatility Spillover ◽  
Chinese Stock Market ◽  
The Us ◽  
Volatility Spillover Effect

This study investigates the time–frequency dynamics of return and volatility spillovers between the stock market and three commodity markets: natural gas, crude oil, and gold via a comparative analysis between the United States and China is conducted with the help of new empirical methods. Our findings are as follows. First, in terms of time, return spillovers between crude oil and the stock market are strongest in two of the three commodity markets. Crude oil emits a net negative return spillover to the US stock market, and a net positive return spillover to the Chinese stock market. By contrast, the strongest volatility spillover effect is transmitted to the stock markets of both countries through gold. However, gold has a net positive volatility spillover effect on the US stock market and a net negative effect on the Chinese stock market. In the frequency domain, most of the return spillover is produced in the short term, and most of the volatility spillover occurs in the long term. In addition, the moving-window method reveals the dynamic nature of the spillover effect. Some extreme events can have a dramatic effect on the spillover index. Conversely, the spillover effect differs significantly between the two countries and is characterized by time variation and frequency dependence.

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