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Risk dependence of CoVaR and structural change between oil prices and exchange rates: A time-varying copula model. (2019). Fan, Ying ; Liu, Bing-Yue ; Ji, Qiang.
In: Energy Economics.
RePEc:eee:eneeco:v:77:y:2019:i:c:p:80-92.

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  2. Probability equivalent level for CoVaR and VaR. (2024). Suarez-Llorens, Alfonso ; Sordo, Miguel A ; Pellerey, Franco ; Ortega-Jimenez, Patricia.
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  3. Quantile time-frequency connectedness analysis between crude oil, gold, financial markets, and macroeconomic indicators: Evidence from the US and EU. (2024). Hamori, Shigeyuki ; Shang, Jin.
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  22. Wavelet Coherence and Continuous Wavelet Transform - Implementation and Application to the Relationship between Exchange Rate and Oil Price for Importing and Exporting Countries. (2023). Aladwani, Jassim.
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  23. Tail dependence structure and extreme risk spillover effects between the international agricultural futures and spot markets. (2023). Zhou, Wei-Xing ; Dai, Peng-Fei.
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  24. The relationship between oil prices and exchange rates in South Africa. (2022). Hlongwane, Nyiko Worship.
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  28. Time-frequency volatility spillovers across the international crude oil market and Chinese major energy futures markets: Evidence from COVID-19. (2022). Xie, Qiwei ; Yao, Yanzhen ; Liu, Ranran.
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  33. The growth of oil futures in China: Evidence of market maturity through global crises. (2022). Corbet, Shaen ; Oxley, Les ; Hu, Yang ; Hou, Yang.
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  36. Extreme risk spillover of the oil, exchange rate to Chinese stock market: Evidence from implied volatility indexes. (2022). Zhao, Lili ; Yin, Hua ; Li, Wanyang ; Wen, Fenghua ; Chen, Lin.
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  37. Crude oil price and exchange rate: Evidence from the period before and after the launch of Chinas crude oil futures. (2022). Sun, Chuanwang ; Cai, Weiyi ; Peng, Yiqi ; Zhan, Yanhong.
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  38. How does investor attention matter for crude oil prices and returns? Evidence from time-frequency quantile causality analysis. (2022). Hau, Liya ; Yu, Dongwei ; Zhu, Huiming ; Chen, Qitong.
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  45. Multidimensional risk spillovers among crude oil, the US and Chinese stock markets: Evidence during the COVID-19 epidemic. (2021). Lu, Tuantuan ; Wei, YU ; Tang, Yong ; Zhu, Pengfei.
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  47. Dynamic and frequency-domain risk spillovers among oil, gold, and foreign exchange markets: Evidence from implied volatility. (2021). Chen, Jinyu ; Huang, Jianbai ; Ding, Qian.
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  67. Dynamic complexity and causality of crude oil and major stock markets. (2020). Wang, Jun ; Xiao, DI.
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  68. Copula stochastic volatility in oil returns: Approximate Bayesian computation with volatility prediction. (2020). Galeano, Pedro ; Ausin, Concepcion M ; Virbickait, Audron.
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  69. Multi-scale dependence structure and risk contagion between oil, gold, and US exchange rate: A wavelet-based vine-copula approach. (2020). Zhou, Dequn ; Zha, Donglan ; Wang, Qunwei ; Dai, Xingyu.
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  70. How do dynamic responses of exchange rates to oil price shocks co-move? From a time-varying perspective. (2020). lucey, brian ; Huang, Shupei.
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  71. Asymmetric risk spillovers between Shanghai and Hong Kong stock markets under China’s capital account liberalization. (2020). He, Jianmin ; Li, Shouwei ; Wei, YU ; Yang, Kun.
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  72. Predicting tail events in a RIA-EVT-Copula framework. (2020). Zhou, Wei-Xing ; Wang, Gang-Jin ; Jiang, Zhi-Qiang ; Zhai, Jin-Rui ; Li, Wei-Zhen.
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  73. Conditional Dependence between Oil Prices and Exchange Rates in BRICS Countries: An Application of the Copula-GARCH Model. (2019). Hamori, Shigeyuki ; He, Yijin.
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  74. Oil price-inflation pass-through in the United States over 1871 to 2018: A wavelet coherency analysis. (2019). Tiwari, Aviral ; Hatemi-J, Abdulnasser ; GUPTA, RANGAN ; Cunado, Juncal.
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  50. A Composite Indicator of Systemic Stress (CISS) for Colombia. (2014). Rojas Bohórquez, Juan Sebastián ; Morales Mosquera, Miguel ; Hurtado, Jorge ; Cabrera, Wilmar .
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