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A complete convergence theorem for stationary regularly varying multivariate time series

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Abstract

For a class of stationary regularly varying and weakly dependent multivariate time series (X n ), we prove the so-called complete convergence result for the space–time point processes of the form \(N_{n} = \sum _{i=1}^{n} \delta _{(i/n, \boldsymbol {X}_{i}/a_{n})}.\) As an application of our main theorem, we give a simple proof of the invariance principle for the corresponding partial maximum process.

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References

  • Bartkiewicz, K., Jakubowski, A., Mikosch, T., Winterberger, O.: Stable limits for sums of dependent infinite variance random variables. Probab. Theory Relat. Fields 3-4, 337–372 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  • Basrak, B., Krizmanić, D.: A multivariate functional limit theorem in weak m1 topology. J. Theoret. Probab. 28, 119–136 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  • Basrak, B., Krizmanić, D., Segers, J.: A functional limit theorem for dependent sequences with infinite variance stable limits. Ann. Probab. 40, 2008–2033 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  • Basrak, B., Segers, J.: Regularly varying multivariate time series. Stoch. Process. Appl. 119, 1055–1080 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  • Billingsley, P.: Convergence of Probability Measures, 2nd edn. Wiley, New York (1999)

    Book  MATH  Google Scholar 

  • Davis, R.A., Hsing, T.: Point processes and partial sum convergence for weakly dependent random variables with infinite variance. Ann. Probab. 23, 879–917 (1995)

    Article  MathSciNet  MATH  Google Scholar 

  • Davis, R.A., Mikosch, T.: The sample autocorrelation function of heavy-tailed processes with application to ARCH. Ann. Statist. 26, 2049–2080 (1998)

    Article  MathSciNet  MATH  Google Scholar 

  • Davis, R.A., Resnick, S.I.: Limit theory for moving averages of random variables with regularly varying tail probabilities. Ann. Probab. 13, 179–195 (1985)

    Article  MathSciNet  MATH  Google Scholar 

  • Embrechts, P., Kluppelberg, C., Mikosch, T.: Modelling Extremal Events for Insurance and Finance. Springer-Verlag, Berlin (1997)

    Book  MATH  Google Scholar 

  • Hsing, T., Leadbetter, M.R.: On the excursion random measure of stationary processes. Ann. Probab. 26, 710–742 (1998)

    Article  MathSciNet  MATH  Google Scholar 

  • Krizmanić, D.: Weak convergence of partial maxima processes in the m 1 topology. Extremes 17, 447–465 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  • Leadbetter, M.R., Rootzén, H.: Extremal theory for stochastic processes. Ann. Probab. 16, 431–478 (1988)

    Article  MathSciNet  MATH  Google Scholar 

  • Mikosch, T., Wintenberger, O.: The cluster index of regularly varying sequences with applications to limit theory for functions of multivariate markov chains. Probab. Th. Rel. Fields 159, 157–196 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  • Mikosch, T., Wintenberger, O.: A large deviations approach to limit theory for heavy-tailed time series. Probab. Th. Rel. Fields, 1–37 (2015)

  • Mori, T.: Limit distributions of two–dimensional point processes generated by strong–mixing sequences. Yokohama Math. J. 25, 155–168 (1977)

    MathSciNet  MATH  Google Scholar 

  • Resnick, S.I.: Extreme Values, Regular Variation, and Point Processes. Springer, New York (1987)

    Book  MATH  Google Scholar 

  • Resnick, S.I.: Heavy-Tail Phenomena: Probabilistic and Statistical Modelling. Springer, New York (2007)

    MATH  Google Scholar 

  • Resnick, S.I.: Extreme Values, Regular Variation, and Point Processes. Springer, New York (2008)

    MATH  Google Scholar 

  • Samorodnitsky, G., Taqqu, M.: Stable Non-Gaussian random processes. CRC press (1994)

  • Whitt, W.: Stochastic-Process Limits. Springer-Verlag, New York (2002)

    MATH  Google Scholar 

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Correspondence to Bojan Basrak.

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Basrak, B., Tafro, A. A complete convergence theorem for stationary regularly varying multivariate time series. Extremes 19, 549–560 (2016). https://doi.org/10.1007/s10687-016-0253-5

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  • DOI: https://doi.org/10.1007/s10687-016-0253-5

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