Necessary and sufficient conditions for moderate deviations of dependent random variables with heavy tails

Science China Mathematics - Tập 53 - Trang 1421-1434 - 2010
Li Liu1
1School of Mathematics and Statistics, Wuhan University, Wuhan, China

Tóm tắt

This paper studies the moderate deviations of real-valued extended negatively dependent (END) random variables with consistently varying tails. The moderate deviations of partial sums are first given. The results are then used to establish the necessary and sufficient conditions for the moderate deviations of random sums under certain circumstances.

Tài liệu tham khảo

Block H W, Savits T H, Shaked M. Some concepts of negative dependence. Ann Probab, 1982, 10: 765–772 Chen Y, Zhang W P. Large deviation for random sums of negatively dependent random variables with consistently varying tails. Statist Probab Lett, 2007, 77: 530–538 Cline D B H, Hsing T. Large deviation probabilities for sums and maxima of random variables with heavy or subexponential tails. Preprint, Texas A&M University, 1991 Cline D B H, Samorodnitsky G. Subexponentiality of the product of independent random variables. Stochastic Process Appl, 1994, 49: 75–98 Embrechts P, Klüppelberg C, Mikosch T. Modelling Extremal Events for Insurance and Finance. Berlin: Springer, 1997 Gao F Q. Moderate deviations for random sums of heavy-tailed random variables. Acta Math Sin (Engl Ser), 2007, 23: 1527–1536 Heyde C C. On large deviation problems for sums of random variables which are not attracted to the normal law. Ann Math Statist, 1967, 38: 1575–1578 Heyde C C. On large deviation probabilities in the case of attraction to a non-normal stable law. Sankhyā Ser A, 1968, 30: 253–258 Jelenković P R, Lazar A A. Asymptotic results for multiplexing subexponential on-off processes. Adv Appl Probab, 1999, 31: 394–421 Klüppelberg C, Mikosch T. Large deviations of heavy-tailed random sums with applications in insurance and finance. J Appl Probab, 1997, 34: 293–308 Lehmann E L. Some concepts of dependence. Ann Math Statist, 1966, 37: 1137–1153 Lin J. The general principle for precise large deviations of heavy-tailed random sums. Statist Probab Lett, 2008, 78: 749–758 Liu L. Precise large deviations for dependent random variables with heavy tails. Statist Probab Lett, 2009, 79: 1290–1298 Meerschaert M M, Scheffler H P. Limit Distributions for Sums of Independent Random Vectors. Heavy Tails in Theory and Practice. New York: Wiley, 2001 Mikosch T, Nagaev A V. Large deviations of heavy-tailed sums with applications in insurance. Extremes, 1998, 1: 81–110 Nagaev A V. Integral limit theorems for large deviations when Cramér’s condition is not fulfilled I,II. Theory Probab Appl, 1969, 14: 51–64 and 193–208 Nagaev S V. Large deviations of sums of independent random variables. Ann Probab, 1979, 7: 745–789 Ng K W, Tang Q, Yan J, et al. Precise large deviations for sums of random variables with consistently varying tails. J Appl Probab, 2004, 41: 93–107 Rozovski L V. Probabilities of large deviations on the whole axis. Theory Probab Appl, 1993, 38: 53–79 Schlegel S. Ruin probabilities in perturbed risk models. Insurance Math Econom, 1998, 22: 93–104 Tang Q. Insensitivity to negative dependence of the asymptotic behavior of precise large deviations. Electron J Probab, 2006, 11: 107–120 Tang Q, Su C, Jiang T, et al. Large deviations for heavy-tailed random sums in compound renewal model. Statist Probab Lett, 2001, 52: 91–100 Tang Q, Tsitsiashvili G. Precise estimates for the ruin probability in finite horizon in a discrete-time model with heavy-tailed insurance and financial risks. Stochastic Process Appl, 2003, 108: 299–325 Wang D, Tang Q. Maxima of sums and random sums for negatively associated random variables with heavy tails. Statist Probab Lett, 2004, 68: 287–295