Abstract

We give a combinatorial proof that a random walk attains a unique maximum with probability at least $1/2$. For closed random walks with uniform step size, we recover Dwass's count of the number of length $\ell$ walks attaining the maximum exactly $k$ times. We also show that the probability that there is both a unique maximum and a unique minimum is asymptotically equal to $\frac14$ and that the probability that a Dyck word has a unique minimum is asymptotically $\frac12$.

Highlights

  • A length walk is a sequence w : {1, . . . , } → {±1}

  • We give a combinatorial proof that a random walk attains a unique maximum with probability at least 1/2

  • We show that the probability that there is both a unique maximum and a unique minimum is asymptotically equal to

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Summary

Introduction

A length walk is a sequence w : {1, . . . , } → {±1}. The trajectory of w is the sequence w : {0, . . . , } → Z defined by w(j) =. We define max(w) = sup{w(j) : 0 j }. In [5], this is proven by a method that computes the probabilities of events in finite random walks by relating them to events in infinite random walks for which probabilities are more readily computed This is a general analytic method used to compute a large. 2n−r r−1 length 2n closed walks attaining their maximum exactly r times. 1 2 of attaining a unique maximum This conclusion does not assume that the walks are closed and allows an arbitrary distribution of step sizes.

Dyck Words and Leads
Counting walks of arbitrary rank
Variable step lengths
Estimating the probability of a unique max and a unique min
Dyck words with a unique maximum

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