• Media type: E-Book
  • Title: Optimal Trading in Automatic Market Makers with Deep Learning
  • Contributor: Jaimungal, Sebastian [VerfasserIn]; Saporito, Yuri [VerfasserIn]; Souza, Max O. [VerfasserIn]; Thamsten, Yuri [VerfasserIn]
  • imprint: [S.l.]: SSRN, [2023]
  • Extent: 1 Online-Ressource (14 p)
  • Language: English
  • DOI: 10.2139/ssrn.4410089
  • Identifier:
  • Keywords: Cryptocurrency ; Optimal Trading ; Automatic Market Makers ; Decentralized Finance ; Deep learning ; Stochastic Control
  • Origination:
  • Footnote: Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments April 4, 2023 erstellt
  • Description: This article explores the optimisation of trading strategies in Constant Function Market Makers (CFMMs) and centralised exchanges. We develop a model that accounts for the interaction between these two markets, estimating the conditional dependence between variables using the concept of conditional elicibility. Furthermore, we pose an optimal execution problem where the agent hides their orders by controlling the rate at which they trade. We do so without approximating the market dynamics. The resulting dynamic programming equation is not analytically tractable, therefore, we employ the deep Galerkin method to solve it. Finally, we conduct numerical experiments and illustrate that the optimal strategy is not prone to price slippage and outperforms naive strategies
  • Access State: Open Access