Skorokhod convergence of maxima of multivariate linear processes with heavy-tailed innovations and random coefficients
Pub. online: 28 January 2025
Type: Research Article
Open Access
Received
30 August 2024
30 August 2024
Revised
11 January 2025
11 January 2025
Accepted
11 January 2025
11 January 2025
Published
28 January 2025
28 January 2025
Abstract
In this paper, functional convergence is derived for the partial maxima stochastic processes of multivariate linear processes with weakly dependent heavy-tailed innovations and random coefficients. The convergence takes place in the space of ${\mathbb{R}^{d}}$-valued càdlàg functions on $[0,1]$ endowed with the weak Skorokhod ${M_{1}}$ topology.
References
Avram, F., Taqqu, M.: Weak convergence of sums of moving averages in the α–stable domain of attraction. Ann. Probab. 20, 483–503 (1992) MR1143432
Basrak, B., Segers, J.: Regularly varying multivariate time series. Stoch. Process. Appl. 119, 1055–1080 (2009) MR2508565. https://doi.org/10.1016/j.spa.2008.05.004
Basrak, B., Tafro, A.: A complete convergence theorem for stationary regularly varying multivariate time series. Extremes 19, 549–560 (2016) MR3535966. https://doi.org/10.1007/s10687-016-0253-5
Kallenberg, O.: Foundations of Modern Probability. Springer, New York (1997) MR1464694
Krizmanić, D.: Functional limit theorems for weakly dependent regularly varying time series. Ph.D. dissertation, University of Zagreb, Croatia, https://www.math.uniri.hr/~dkrizmanic/DKthesis.pdf. Accessed 28 June 2024.
Krizmanić, D.: Skorokhod ${M_{1}}$ convergence of maxima of multivariate linear processes with heavy-tailed innovations and random coefficients. arXiv preprint, https://arxiv.org/abs/2208.04054, 2022. Accessed 28 June 2024.
Krizmanić, D.: Functional weak convergence of partial maxima processes. Extremes 19, 7–23 (2016) MR3454028. https://doi.org/10.1007/s10687-015-0236-y
Krizmanić, D.: Functional convergence for moving averages with heavy tails and random coefficients. ALEA Lat. Am. J. Probab. Math. Stat. 16, 729–757 (2019) MR3949276. https://doi.org/10.30757/alea.v16-26
Krizmanić, D.: Maxima of linear processes with heavy-tailed innovations and random coefficients. J. Time Ser. Anal. 43, 238–262 (2022) MR4400293. https://doi.org/10.1111/jtsa.12610
Kulik, R., Soulier, P.: Heavy-Tailed Time Series. Springer, New York (2020) MR4174389. https://doi.org/10.1007/978-1-0716-0737-4
Lamperti, J.: On extreme order statistics. Ann. Math. Stat. 35, 1726–1737 (1964) MR0170371. https://doi.org/10.1214/aoms/1177700395
Mikosch, T., Wintenberger, O.: Extreme Value Theory for Time Series. Models with Power-Law Tails. Springer, New York (2024) MR4823721. https://doi.org/10.1007/978-3-031-59156-3
Resnick, S.I.: Extreme Values, Regular Variation, and Point Processes. Springer, New York (1987) MR0900810. https://doi.org/10.1007/978-0-387-75953-1
Resnick, S.I.: Heavy-Tail Phenomena: Probabilistic and Statistical Modeling. Springer, New York (2007) MR2271424
Skorohod, A.V.: Limit theorems for stochastic processes. Theory Probab. Appl. 1, 261–290 (1956) MR0084897
Tyran-Kamińska, M.: Convergence to Lévy stable processes under some weak dependence conditions. Stoch. Process. Appl. 120, 1629–1650 (2010) MR2673968. https://doi.org/10.1016/j.spa.2010.05.010
Whitt, W.: Stochastic-Process Limits. Springer, New York (2002) MR1876437