Modelling extremal events: for insurance and finance
Modelling extremal events: for insurance and finance
Tail Asymptotics for the Supremum of a Random Walk when the Mean Is not Finite
Queueing Systems: Theory and Applications
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Let F be the common distribution function of the increments of a random walk {Sn, n ≥ 0} with S0 = 0 and a negative drift and let {N(t), t ≥ 0} be a general counting process, independent of {Sn, n ≥ 0}. This article investigates the tail probability, denoted by &psgr;(x; t), of the maximum of SN(v) over a finite horizon 0 ≤ v ≤ t. When F is strongly subexponential, some asymptotics for &psgr;(x; t) are derived as x → ∞. The merit is that all of the obtained asymptotics are uniform for t in a finite or infinite time interval.