Pregled bibliografske jedinice broj: 1192995
Deep Reinforcement Learning for Market Making Under a Hawkes Process-Based Limit Order Book Model
Deep Reinforcement Learning for Market Making Under a Hawkes Process-Based Limit Order Book Model // IEEE Control Systems Letters, 6 (2022), 2485-2490 doi:10.1109/lcsys.2022.3166446 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 1192995 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Deep Reinforcement Learning for Market Making Under
a Hawkes Process-Based Limit Order Book Model
Autori
Gašperov, Bruno ; Kostanjčar, Zvonko
Izvornik
IEEE Control Systems Letters (2475-1456) 6
(2022);
2485-2490
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
finance ; neural networks ; stochastic optimal control
Sažetak
The stochastic control problem of optimal market making is among the central problems in quantitative finance. In this letter, a deep reinforcement learning-based controller is trained on a weakly consistent, multivariate Hawkes process-based limit order book simulator to obtain market making controls. The proposed approach leverages the advantages of Monte Carlo backtesting and contributes to the line of research on market making under weakly consistent limit order book models. The ensuing deep reinforcement learning controller is compared to multiple market making benchmarks, with the results indicating its superior performance with respect to various risk-reward metrics, even under significant transaction costs.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo
POVEZANOST RADA
Projekti:
HRZZ-IP-2019-04-5241 - Algoritmi dubokog podržanog učenja za upravljanje rizicima (DREAM) (Kostanjčar, Zvonko, HRZZ ) ( CroRIS)
--KK.01.1.1.01.009 - Napredne metode i tehnologije u znanosti o podatcima i kooperativnim sustavima (DATACROSS) (Šmuc, Tomislav; Lončarić, Sven; Petrović, Ivan; Jokić, Andrej; Palunko, Ivana) ( CroRIS)
Citiraj ovu publikaciju:
Časopis indeksira:
- Web of Science Core Collection (WoSCC)
- Emerging Sources Citation Index (ESCI)
- Scopus
