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Short Communications

Discussion of ‘On studying extreme values and systematic risks with nonlinear time series models and tail dependence measures’

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Pages 38-40 | Received 24 Dec 2020, Accepted 24 Dec 2020, Published online: 22 Jan 2021

References

  • Bader, B., Yan, J., & Zhang, X. (2018). Automated threshold selection for extreme value analysis via ordered goodness-of-fit tests with adjustment for false discovery rate. The Annals of Applied Statistics, 12(1), 310–329. https://doi.org/10.1214/17-AOAS1092
  • Das, B., & Resnick, S. I. (2015). Models with hidden regular variation: Generation and detection. Stochastic Systems, 5(2), 195–238. https://doi.org/10.1287/14-SSY141
  • Das, B., & Resnick, S. I. (2017). Hidden regular variation under full and strong asymptotic dependence. Extremes, 20(4), 873–904. https://doi.org/10.1007/s10687-017-0290-8
  • Davis, R. A., & Mikosch, T. (2009). The extremogram: A correlogram for extreme events. Bernoulli, 15(4), 977–1009. https://doi.org/10.3150/09-BEJ213
  • Erhardt, R., & Sisson, S. A. (2016). Modeling extremes using approximate Bayesian computation. In D. Dey & J. Yan (Eds.), Extreme value modeling and risk analysis: Methods and applications (pp. 281–306). CRC Press.
  • Joe, H. (2005). Asymptotic efficiency of the two-stage estimation method for copula-based models. Journal of Multivariate Analysis, 94(2), 401–419. https://doi.org/10.1016/j.jmva.2004.06.003
  • Larsson, M., & Resnick, S. I. (2012). Extremal dependence measure and extremogram: The regularly varying case. Extremes, 15(2), 231–256. https://doi.org/10.1007/s10687-011-0135-9
  • Ledford, A. W., & Tawn, J. A. (2003). Diagnostics for dependence within time series extremes. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 65(2), 521–543. https://doi.org/10.1111/rssb.2003.65.issue-2
  • Lehtomaa, J., & Resnick, S. I. (2020). Asymptotic independence and support detection techniques for heavy-tailed multivariate data. Insurance: Mathematics and Economics. 93: 262–277. https://doi.org/10.1016/j.insmatheco.2020.05.002.
  • Ljung, G. M., & Box, G. E. P. (1978). On a measure of lack of fit in time series models. Biometrika, 65(2), 297–303. https://doi.org/10.1093/biomet/65.2.297
  • Resnick, S. (2004). The extremal dependence measure and asymptotic independence. Stochastic Models, 20(2), 205–227. https://doi.org/10.1081/STM-120034129
  • Resnick, S. I. (2007). Heavy-tail phenomena: Probabilistic and statistical modeling. Springer Science & Business Media.
  • Sang, H. (2016). Composite likelihood for extreme values. In D. Dey & J. Yan (Eds.), Extreme value modeling and risk analysis: Methods and applications (pp. 239–256). CRC Press.
  • Zhang, Z. (2021). On studying extreme values and systematic risks with nonlinear time series models and tail dependence measures. Statistical Theory and Related Fields. Forthcoming.
  • Zhang, Z., Peng, L., & Idowu, T. (2016). Max-autoregressive and moving maxima models for extremes. In D. Dey & J. Yan (Eds.), Extreme value modeling and risk analysis: Methods and applications (pp. 153–178). CRC Press.

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