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Randomly weighted sums and their maxima with heavy-tailed increments and dependence structure

Author

Listed:
  • Shijie Wang
  • Yiyu Hu
  • Jijiao He
  • Xuejun Wang

Abstract

Consider the randomly weighted sums Sm(θ) = ∑mi = 1θiXi, 1 ⩽ m ⩽ n, and their maxima Mn(θ) = max 1 ⩽ m ⩽ nSm(θ), where Xi, 1 ⩽ i ⩽ n, are real-valued and dependent according to a wide type of dependence structure, and θi, 1 ⩽ i ⩽ n, are non negative and arbitrarily dependent, but independent of Xi, 1 ⩽ i ⩽ n. Under some mild conditions on the right tails of the weights θi, 1 ⩽ i ⩽ n, we establish some asymptotic equivalence formulas for the tail probabilities of Sn(θ) and Mn(θ) in the case where Xi, 1 ⩽ i ⩽ n, are dominatedly varying, long-tailed and subexponential distributions, respectively.

Suggested Citation

  • Shijie Wang & Yiyu Hu & Jijiao He & Xuejun Wang, 2017. "Randomly weighted sums and their maxima with heavy-tailed increments and dependence structure," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(21), pages 10851-10863, November.
  • Handle: RePEc:taf:lstaxx:v:46:y:2017:i:21:p:10851-10863
    DOI: 10.1080/03610926.2016.1248785
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