Copula model dependency between oil prices and stock markets: Evidence from China and Vietnam

By Cuong C. Nguyen, M. Bhatti. 2012

186 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/b879028883b1f3b4d9e2d4135c00d921eed3b620

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Citations in the corpus

Energy markets and CO2 emissions: Analysis by stochastic copula autoregressive model (2015, unknown): “To the best of our knowledge, copulas have been used in commodities markets by Zohrabyan (2014)[14], Kharoubi and German(2008)[15], Reboredo (2011)[16], Nguyen and Bhatti (2012)[17], Hammoudeh et al (2013)[18] and Syed et al(2014)[19].”
Oil Prices and Stock Markets: A Review of the Theory and Empirical Evidence (2018, background): “Although this strand has received some attention recently (see for instance, Jammazi and Reboredo, 2016; Khalfaoui et al., 2015; Nguyen and Bhatti, 2012), results are by no means conclusive.”
Fighting terrorism in Africa: Benchmarking policy harmonization (2018, methodology): “The employment of Dynamic Conditional Correlation (Chiang et al., 2007; Al Rahahleh & Bhatti, 2017) and Copula (Ahsnaullah & Bhatti, 2010; Bhatti & Nguyen, 2012; Nguyen & Bhatti, 2012; Jong-Min & Jung, 2016) methodologies that are designed to analyze data into some extreme events are recommendable.”
Extreme risk spillovers between crude oil and stock markets (2015, background): “2 e.g., Geman and Kharoubi (2008), Aloui et al. (2013), Nguyen and Bhatti (2012), Wen et al. (2012), and Zhu et al. (2014). the crude oil market was increasing extremely, and vice versa; Wen et al. (2012) find significantly increasing tail dependence between crude oil and the U.S. stock market…”
Time-varying correlation between oil and stock market volatilities: Evidence from oil-importing and oil-exporting countries (2016, background): “Broadstock et al. (2012) and Nguyen and Bhatti (2012) also claim that the Chinese stock market index does not receive a significant impact oil prices, especially until the global financial crisis.”
The Structure and Degree of Dependence - A Quantile Regression Approach (2012, unknown): “Specific applications of copulas to risk management and diversification of financial risks can be found in Chollete, de la Peña Lu (2011), Kole, Koedijk and Verbeek (2007) and Nguyen and Bhatti (2012).”
Oil Price Uncertainty and Sectoral Stock Returns in China: A Time-Varying Approach (2015, background): “For example, Nguyen and Bhatti (2012) did not find any tail dependence in the relationship between global oil price changes and the Chinese stock market.”
Asymmetric spillover and network connectedness between crude oil, gold, and Chinese sector stock markets (2021, background): “A third stand of literature examines the dependence structure (upper and lower tail dependence) between crude oil and stock markets (Sukcharoen et al., 2014; Li and Wei, 2018; Nguyen and Bahtti, 2018; Ji et al., 2020).”
Oil price shocks and stock market returns: New evidence from the United States and China (2014, background): “This latter finding is also in line with Nguyen and Bhatti (2012) who report that the Chinese stock market is not affected by oil prices during the period 2000-2009.”
Modelling dynamic dependence between crude oil prices and Asia-Pacific stock market returns (2014, background): “Nguyen and Bhatti (2012) find no tail dependence in the relationship between international oil price changes and Chinese stock returns.”
Dependences and volatility spillovers between the oil and stock markets: New evidence from the copula and VAR-BEKK-GARCH models (2020, background): “…investigating multi-market dependence relationships have not considered structural breaks and regime changes, which may have stimulated rapid and continually changing volatilities in markets over an extended period of time (e.g., Nguyen, 2012; Sukcharoen et al., 2014; Ji et al., 2018; Zhang, 2017).”