Two explicit Skorokhod embeddings for simple symmetric random walk

TL;DR

This paper introduces two explicit methods for embedding a given centered distribution into a simple symmetric random walk, one Markovian and one inspired by Azéma-Yor, with applications in behavioral finance.

Contribution

It provides novel explicit constructions of randomized stopping times for embedding distributions into symmetric random walks, including a maximum-maximizing solution.

Findings

First construction is Markovian with state-dependent coin bias.

Second construction is a discrete Azéma-Yor analogue maximizing the maximum.

Both methods ensure uniform integrability of the embedding.

Abstract

Motivated by problems in behavioural finance, we provide two explicit constructions of a randomized stopping time which embeds a given centered distribution $\mu$ on integers into a simple symmetric random walk in a uniformly integrable manner. Our first construction has a simple Markovian structure: at each step, we stop if an independent coin with a state-dependent bias returns tails. Our second construction is a discrete analogue of the celebrated Az\'ema-Yor solution and requires independent coin tosses only when excursions away from maximum breach predefined levels. Further, this construction maximizes the distribution of the stopped running maximum among all uniformly integrable embeddings of $\mu$.