In a two-agent Almgren-Chriss liquidation game, deep RL agents given intra-episode history of prices and own actions achieve supra-competitive outcomes more frequently and persistently than agents without such memory.
arXiv preprint arXiv:1911.05892 , year =
2 Pith papers cite this work, alongside 19 external citations. Polarity classification is still indexing.
2
Pith papers citing it
19
external citations · external index
verdicts
UNVERDICTED 2representative citing papers
In a repeated market-maker/taker game with endogenous price impact, projected stochastic gradient ascent by adaptive agents reaches a region of persistent overpricing in finite time.
citing papers explorer
-
Memory-Induced Supra-Competitive Outcomes Between Deep Reinforcement Learning Agents in Optimal Trade Execution
In a two-agent Almgren-Chriss liquidation game, deep RL agents given intra-episode history of prices and own actions achieve supra-competitive outcomes more frequently and persistently than agents without such memory.
-
The Invisible Handshake: Persistent Overpricing by Adaptive Market Agents
In a repeated market-maker/taker game with endogenous price impact, projected stochastic gradient ascent by adaptive agents reaches a region of persistent overpricing in finite time.