Robert Boyce, Martin Herdegen, Leandro Sánchez-Betancourt
{"title":"Market Making with Exogenous Competition","authors":"Robert Boyce, Martin Herdegen, Leandro Sánchez-Betancourt","doi":"arxiv-2407.17393","DOIUrl":null,"url":null,"abstract":"We study liquidity provision in the presence of exogenous competition. We\nconsider a `reference market maker' who monitors her inventory and the\naggregated inventory of the competing market makers. We assume that the\ncompeting market makers use a `rule of thumb' to determine their posted depths,\ndepending linearly on their inventory. By contrast, the reference market maker\noptimises over her posted depths, and we assume that her fill probability\ndepends on the difference between her posted depths and the competition's\ndepths in an exponential way. For a linear-quadratic goal functional, we show\nthat this model admits an approximate closed-form solution. We illustrate the\nfeatures of our model and compare against alternative ways of solving the\nproblem either via an Euler scheme or state-of-the-art reinforcement learning\ntechniques.","PeriodicalId":501084,"journal":{"name":"arXiv - QuantFin - Mathematical Finance","volume":"56 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuantFin - Mathematical Finance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2407.17393","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
We study liquidity provision in the presence of exogenous competition. We
consider a `reference market maker' who monitors her inventory and the
aggregated inventory of the competing market makers. We assume that the
competing market makers use a `rule of thumb' to determine their posted depths,
depending linearly on their inventory. By contrast, the reference market maker
optimises over her posted depths, and we assume that her fill probability
depends on the difference between her posted depths and the competition's
depths in an exponential way. For a linear-quadratic goal functional, we show
that this model admits an approximate closed-form solution. We illustrate the
features of our model and compare against alternative ways of solving the
problem either via an Euler scheme or state-of-the-art reinforcement learning
techniques.