# Multidimensional random walks conditioned to stay ordered via generalized ladder height functions

## TL;DR

This paper introduces a new approach to construct multidimensional random walks conditioned to stay ordered, using generalized ladder height functions and minimal moment restrictions, extending previous methods with broader applicability.

## Contribution

It develops a novel conditioning method based on geometric stopping times, requiring fewer restrictions and characterizes the harmonic functions associated with ordered multidimensional random walks.

## Key findings

- The new approach requires minimal moment conditions.
- Characterization of when the limit process is Markovian or sub-Markovian.
- Identification of the unique harmonic function under certain conditions.

## Abstract

Random walks conditioned to stay positive are a prominent topic in fluctuation theory. One way to construct them is as a random walk conditioned to stay positive up to time $n$, and let $n$ tend to infinity. A second method is conditioning instead to stay positive up to an independent geometric time, and send its parameter to zero. The multidimensional case (condition the components of a $d$-dimensional random walk to be ordered) was solved in [EK08] using the first approach, but some moment conditions need to be imposed. Our approach is based on the second method, which has the advantage to require a minimal restriction, needed only for the finiteness of the $h$-transform in certain cases. We also characterize when the limit is Markovian or sub-Markovian, and give several reexpresions of the $h$-function. Under some conditions given in [Ign18], it can be proved that our $h$-function is the only harmonic function which is zero outside the Weyl chamber $\{x=(x_1,\ldots, x_d)\in \mathbb{R}^d: x_1<\cdots < x_d\}$.