102 research outputs found

    An optimal stopping problem with finite horizon for sums of I.I.D. random variables

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    AbstractThe problem of selling a commodity optimally at one of n successive time instants leads to the optimal stopping problem for the finite sequence ((n−j)lSj)1⩽j⩽n, where Sj=U1 + … + Uj, U1, U2,… are i.i.d., E(U1) = 0 and E(U21) = 1. The optimal stopping time πn is seen to be of the form τn = inf{j|j = n or j < n, Sj⩾clj,n}, where c1j,1>…>cln−1,n = 0 satisfyn−12 cj,nl → αl(1 − t)11, if n → ∞, j/n →t ṫ[0,1]. αl > 0 is the solution of the equation d2l+2dx2l+2(Ф/φ)(α) = (α + α−1)d2l+2dx2l+2(Ф/φ)(α). For the value vln we have n−32vnl → vl. vl is explicitly computed. In the normal case we also obtain results on the speed of convergence of n−12cj,nl and n−32vnl

    On the small-time behavior of subordinators

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    We prove several results on the behavior near t=0 of Yt−tY_t^{-t} for certain (0,∞)(0,\infty)-valued stochastic processes (Yt)t>0(Y_t)_{t>0}. In particular, we show for L\'{e}vy subordinators that the Pareto law on [1,∞)[1,\infty) is the only possible weak limit and provide necessary and sufficient conditions for the convergence. More generally, we also consider the weak convergence of tL(Yt)tL(Y_t) as t→0t\to0 for a decreasing function LL that is slowly varying at zero. Various examples demonstrating the applicability of the results are presented.Comment: Published in at http://dx.doi.org/10.3150/11-BEJ363 the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm

    Joint Distributions of the Numbers of Visits for Finite-State Markov Chains

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    AbstractFor a discrete-time Markov chain with finite state space {1, …, r} we consider the joint distribution of the numbers of visits in states 1, …, r−1 during the firstNsteps or before theNth visit tor. From the explicit expressions for the corresponding generating functions we obtain the limiting multivariate distributions asN→∞ when staterbecomes asymptotically absorbing and forj=1, …, r−1 the probability of a transition fromrtojis of order 1/N
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