# On joint weak convergence of partial sum and maxima processes

## TL;DR

This paper establishes joint weak convergence of partial sum and maxima processes for stationary sequences under regular variation and dependence conditions, revealing the limit as a combination of an alpha-stable Lévy process and an extremal process.

## Contribution

It provides the first joint convergence result for partial sums and maxima under regular variation with alpha-stable limits and explores the dependence structure between the two components.

## Key findings

- Limit process is an alpha-stable Lévy process and an extremal process.
- Convergence occurs in the space of cadlag functions with the weak M1 topology.
- The weak M1 topology cannot generally be replaced by the standard M1 topology.

## Abstract

For a strictly stationary sequence of random variables we derive functional convergence of the joint partial sum and partial maxima process under joint regular variation with index $\alpha \in (0,2)$ and weak dependence conditions. The limiting process consists of an $\alpha$--stable L\'{e}vy process and an extremal process. We also describe the dependence between these two components of the limit. The convergence takes place in the space of $\mathbb{R}^{2}$--valued c\`{a}dl\`{a}g functions on $[0,1]$, with the Skorohod weak $M_{1}$ topology. We further show that this topology in general can not be replaced by the stronger (standard) $M_{1}$ topology.