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Risk dependence of CoVaR and structural change between oil prices and exchange rates: A time-varying copula model

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  • Ji, Qiang
  • Liu, Bing-Yue
  • Fan, Ying

Abstract

This paper analyses the dynamic dependence between WTI crude oil and the exchange rates of the United States and China, taking structural changes of dependence into account by using six time-varying copula models. Upside and downside conditional values at risk (CoVaRs) are introduced specifically to measure the upward and downward risk dependences between oil prices and exchange rates. The findings indicate a structural break point of dependence exists between daily or weekly crude oil and the US dollar index. The dependence between crude oil and the RMB exchange rate is faintly positive with lower tail dependence, while the dependence between crude oil and the US dollar index is significantly negative with lower-upper and upper-lower tail dependence. Finally, the CoVaRs results show that there is significant risk spillover from crude oil to Chinese and the US exchange rate markets. Furthermore, the spillover effect is significantly asymmetry in Chinese exchange rate market in response to rising and falling oil returns, while the asymmetry of spillover effect for the US dollar index is not significant.

Suggested Citation

  • Ji, Qiang & Liu, Bing-Yue & Fan, Ying, 2019. "Risk dependence of CoVaR and structural change between oil prices and exchange rates: A time-varying copula model," Energy Economics, Elsevier, vol. 77(C), pages 80-92.
  • Handle: RePEc:eee:eneeco:v:77:y:2019:i:c:p:80-92
    DOI: 10.1016/j.eneco.2018.07.012
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    2. Yi, Yongsheng & Ma, Feng & Zhang, Yaojie & Huang, Dengshi, 2019. "Forecasting stock returns with cycle-decomposed predictors," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 250-261.
    3. Wei-Zhen Li & Jin-Rui Zhai & Zhi-Qiang Jiang & Gang-Jin Wang & Wei-Xing Zhou, 2020. "Predicting tail events in a RIA-EVT-Copula framework," Papers 2004.03190, arXiv.org, revised Apr 2020.
    4. Huang, Shupei & An, Haizhong & Lucey, Brian, 2020. "How do dynamic responses of exchange rates to oil price shocks co-move? From a time-varying perspective," Energy Economics, Elsevier, vol. 86(C).
    5. Tiwari, Aviral Kumar & Cunado, Juncal & Hatemi-J, Abdulnasser & Gupta, Rangan, 2019. "Oil price-inflation pass-through in the United States over 1871 to 2018: A wavelet coherency analysis," Structural Change and Economic Dynamics, Elsevier, vol. 50(C), pages 51-55.
    6. Liu, Xiang-dong & Pan, Fei & Cai, Wen-li & Peng, Rui, 2020. "Correlation and risk measurement modeling: A Markov-switching mixed Clayton copula approach," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
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    9. Ngo Thai HUNG, 2020. "Conditional dependence between oil prices and CEE stock markets: a copula-GARCH approach Abstract: This study investigates both the constant and time-varying conditional dependency between crude oil a," Eastern Journal of European Studies, Centre for European Studies, Alexandru Ioan Cuza University, vol. 11, pages 62-86, June.
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    More about this item

    Keywords

    Dynamic dependence; CoVaR; Time-varying copula; Structural change; Oil price; Exchange rate;

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

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