4 citations · 5 across the 2 of their papers we have counts for
2 papers
q-fin.TR2020★ 4 cited
Extending Deep Reinforcement Learning Frameworks in Cryptocurrency Market Making
Jonathan Sadighian
There has been a recent surge in interest in the application of artificial intelligence to automated trading. Reinforcement learning has been applied to single- and multi-instrumen…
q-fin.TR2019★ 1 cited
Deep Reinforcement Learning in Cryptocurrency Market Making
Jonathan Sadighian
This paper sets forth a framework for deep reinforcement learning as applied to market making (DRLMM) for cryptocurrencies. Two advanced policy gradient-based algorithms were selec…