Double Deep Q-Learning for optimal execution
Year of publication: |
2021
|
---|---|
Authors: | Ning, Brian ; Lin, Franco Ho Ting ; Jaimungal, Sebastian |
Published in: |
Applied mathematical finance. - London : Routledge, ISSN 1466-4313, ZDB-ID 2004159-7. - Vol. 28.2021, 4, p. 361-380
|
Subject: | algorithmic trading | DDQN | optimal execution | reinforcement learning | Theorie | Theory | Elektronisches Handelssystem | Electronic trading | Lernprozess | Learning process | Wertpapierhandel | Securities trading | Mathematische Optimierung | Mathematical programming | Führungskräfte | Managers |
-
Optimal off-exchange execution with closing price
Kuno, Seiya, (2017)
-
Uncertain execution in order-driven markets
Sánchez-Betancourt, Leandro, (2021)
-
Manahov, Viktor, (2016)
- More ...
-
Deep Q-learning for Nash equilibria : Nash-DQN
Casgrain, Philippe, (2022)
-
Albanese, Claudio, (2003)
-
Valuing guaranteed withdrawal benefits with stochastic interest rates and volatility
Donnelly, Ryan, (2014)
- More ...