On $\mathbb{R}^d$-valued multi-self-similar Markov processes

TL;DR

This paper fully characterizes $R^d$-valued multi-self-similar Markov processes, establishing their structure, properties, and a Lamperti-type representation linking them to Markov additive processes, with applications to their asymptotic behavior.

Contribution

It provides a complete description of $R^d$-valued multi-self-similar Markov processes, including their state space, boundary behavior, Feller property, and a Lamperti-type representation.

Findings

State space is a union of open orthants with 0 as the only absorbing state.

No finite entrance law exists at 0 for these processes.

A Lamperti-type representation links these processes to Markov additive processes.

Abstract

An $\mathbb{R}^d$-valued Markov process $X^{(x)}_t=(X^{1,x_1}_t,\dots,X^{d,x_d}_t)$, $t\ge0,x\in\mathbb{R}^d$ is said to be multi-self-similar with index $(\alpha_1,\dots,\alpha_d)\in[0,\infty)^d$ if the identity in law \[(c_iX_t^{i,x_i/c_i};i=1,\dots,d)_{t\ge0}\ed(X_{ct}^{(x)})_{t\ge0}\,,\] where $c=\prod_{i=1}^dc_i^{\alpha_i}$, is satisfied for all $c_1,\dots,c_d>0$ and all starting point $x$. Multi-self-similar Markov processes were introduced by Jacobsen and Yor \cite{jy} in the aim of extending the Lamperti transformation of positive self-similar Markov processes to $\mathbb{R}^d_+$-valued processes. This paper aims at giving a complete description of all $\mathbb{R}^d$-valued multi-self-similar Markov processes. We show that their state space is always a union of open orthants with 0 as the only absorbing state and that there is no finite entrance law at 0 for these processes. We give conditions for these processes to satisfy the Feller property. Then we show that a Lamperti-type representation is also valid for $\mathbb{R}^d$-valued multi-self-similar Markov processes. In particular, we obtain a one-to-one relationship between this set of processes and the set of Markov additive processes with values in $\{-1,1\}^d\times\mathbb{R}^d$. We then apply this representation to study the almost sure asymptotic behavior of multi-self-similar Markov processes.