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Systemic risk in European financial and energy sectors: Dynamic factor copula approach

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  • Nevrla, Matěj

Abstract

We perform an analysis of systemic risk in financial and energy sectors in Europe using daily time series of CDS spreads. We employ the factor copula model with GAS dynamics from Oh and Patton (2018) for the purpose of estimating dependency structures between market participants. Based on the estimated models, we perform Monte Carlo simulations to obtain future values of CDS spreads, and then measure the probability of systemic events at given time points. We conclude that substantially higher systemic risk is present in the financial sector compared to the energy sector. We also find that the most systemically vulnerable financial and energy companies come from Spain.

Suggested Citation

  • Nevrla, Matěj, 2020. "Systemic risk in European financial and energy sectors: Dynamic factor copula approach," Economic Systems, Elsevier, vol. 44(4).
    • Handle: RePEc:eee:ecosys:v:44:y:2020:i:4:s0939362518304904
    DOI: 10.1016/j.ecosys.2020.100820
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    References listed on IDEAS

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    2. Xie, Qichang & Luo, Chao & Cong, Xiaoping & Wang, Xu, 2024. "Volatility connectedness and its determinants of global energy stock markets," Economic Systems, Elsevier, vol. 48(2).
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    More about this item

    Keywords

    Credit default swap; Energy sector; Factor copula; Financial sector; Generalized autoregressive score model; Systemic risk;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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