Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Jan-Peter Calliess"'
Asynchronous Deep Double Dueling Q-learning for trading-signal execution in limit order book markets
Publikováno v:
Frontiers in Artificial Intelligence, Vol 6 (2023)
We employ deep reinforcement learning (RL) to train an agent to successfully translate a high-frequency trading signal into a trading strategy that places individual limit orders. Based on the ABIDES limit order book simulator, we build a reinforceme
Externí odkaz:
https://doaj.org/article/0f9348e74457474ba9d2f4e4778cb098
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
Abstract In an increasingly connected global market, news sentiment towards one company may not only indicate its own market performance, but can also be associated with a broader movement on the sentiment and performance of other companies from the
Externí odkaz:
https://doaj.org/article/a2278f9569e644e3b01e0f138f0d548b
Publikováno v:
Multi-Agent-Based Simulation XXII ISBN: 9783030945473
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3be948d14618ccdd32765fc3dd19eea9
https://doi.org/10.1007/978-3-030-94548-0_4
https://doi.org/10.1007/978-3-030-94548-0_4
This article presents a novel learning method based on componentwise Holder continuity, which allows one to consider independently the contribution of each input to each output of the function to be learned. The method provides a bounded prediction e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::35fd1bce5263504b05a373ac70aa1493
Autor:
Alessandro Abate, Luca Cardelli, Marta Kwiatkowska, Kyriakos Polymenakos, Stephen J. Roberts, Luca Laurenti, Jan-Peter Calliess, Andrea Patane
Publikováno v:
CDC
2020 59th IEEE Conference on Decision and Control (CDC)
2020 59th IEEE Conference on Decision and Control (CDC)
Gaussian Processes (GPs) are widely employed in control and learning because of their principled treatment of uncertainty. However, tracking uncertainty for iterative, multi-step predictions in general leads to an analytically intractable problem. Wh
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::492343c72d37f7dbc22e0d9677357bfd
https://doi.org/10.1109/cdc42340.2020.9304029
https://doi.org/10.1109/cdc42340.2020.9304029
Publikováno v:
Scientific Reports
Scientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
Scientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
In an increasingly connected global market, news sentiment towards one company may not only indicate its own market performance, but can also be associated with a broader movement on the sentiment and performance of other companies from the same or e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::73789b595641675e205b6eb67ff55d7c
https://pubmed.ncbi.nlm.nih.gov/33542292
https://pubmed.ncbi.nlm.nih.gov/33542292
Sherpa/Romeo: Versión aceptada en repositorios institucionales tras 24 meses de embargo https://v2.sherpa.ac.uk/id/publication/4278 This paper presents a robust learning-based predictive control strategy for nonlinear systems subject to both input a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a3ed58db61d9e96c9502316d155fbd17
Techniques known as Nonlinear Set Membership prediction or Lipschitz Interpolation are approaches to supervised machine learning that utilise presupposed Lipschitz properties to perform inference over unobserved function values. Provided a bound on t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::689983e1ce6df7df0c8eefcaeb319e47
Publikováno v:
SSRN Electronic Journal.
This paper explores the application of machine learning methods to financial statement analysis. We compare a range of models in the machine learning repertoire in their ability to predict the sign and magnitude of abnormal stock returns around earni
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::86f143aaf0b3abb31a9725eb50291e56
https://doi.org/10.2139/ssrn.3520684
https://doi.org/10.2139/ssrn.3520684
Autor:
Dennis Severin Hansen, Stephen J. Roberts, Zhenyu Yang, Mads Valentin Bram, Jan-Peter Calliess
Publikováno v:
Bram, M V, Calliess, J-P, Roberts, S, Hansen, D S & Yang, Z 2020, ' Analysis and Modeling of State-Dependent Delay in Control Valves ', IFAC-PapersOnLine, vol. 53, no. 2, pp. 5777-5782 . https://doi.org/10.1016/j.ifacol.2020.12.1613
Pneumatic control valves are deployed in a wide variety of industrial applications and plants. The plethora of valve applications has a great span in required operational accuracy and time scales, from precise medical dosing valves to large valves us
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7d37c33d7dde28bf67e9b380c4a32669
https://vbn.aau.dk/da/publications/395caa92-f32d-4feb-940e-eac19b17d8cb
https://vbn.aau.dk/da/publications/395caa92-f32d-4feb-940e-eac19b17d8cb