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https://doi.org/10.21256/zhaw-22664| Publikationstyp: | Beitrag in wissenschaftlicher Zeitschrift |
| Art der Begutachtung: | Peer review (Publikation) |
| Titel: | The applicability of self-play algorithms to trading and forecasting financial markets |
| Autor/-in: | Posth, Jan-Alexander Kotlarz, Piotr Kamil Hadji Misheva, Branka Osterrieder, Jörg Schwendner, Peter |
| et. al: | No |
| DOI: | 10.3389/frai.2021.668465 10.21256/zhaw-22664 |
| Erschienen in: | Frontiers in Artificial Intelligence |
| Band(Heft): | 4 |
| Heft: | 668465 |
| Erscheinungsdatum: | 31-Mai-2021 |
| Verlag / Hrsg. Institution: | Frontiers Research Foundation |
| ISSN: | 2624-8212 |
| Sprache: | Englisch |
| Schlagwörter: | Artificial intelligence; Machine learning; Financial market; Trading |
| Fachgebiet (DDC): | 006: Spezielle Computerverfahren 332: Finanzwirtschaft |
| Zusammenfassung: | The central research question to answer in this study is whether the AI methodology of Self-Play can be applied to financial markets. In typical use-cases of Self-Play, two AI agents play against each other in a particular game, e.g., chess or Go. By repeatedly playing the game, they learn its rules as well as possible winning strategies. When considering financial markets, however, we usually have one player—the trader—that does not face one individual adversary but competes against a vast universe of other market participants. Furthermore, the optimal behaviour in financial markets is not described via a winning strategy, but via the objective of maximising profits while managing risks appropriately. Lastly, data issues cause additional challenges, since, in finance, they are quite often incomplete, noisy and difficult to obtain. We will show that academic research using Self-Play has mostly not focused on finance, and if it has, it was usually restricted to stock markets, not considering the large FX, commodities and bond markets. Despite those challenges, we see enormous potential of applying self-play concepts and algorithms to financial markets and economic forecasts. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/22664 |
| Volltext Version: | Publizierte Version |
| Lizenz (gemäss Verlagsvertrag): | CC BY 4.0: Namensnennung 4.0 International |
| Departement: | School of Management and Law School of Engineering |
| Organisationseinheit: | Institut für Wealth & Asset Management (IWA) Institut für Datenanalyse und Prozessdesign (IDP) |
| Enthalten in den Sammlungen: | Publikationen School of Management and Law |
Dateien zu dieser Ressource:
| Datei | Beschreibung | Größe | Format | |
|---|---|---|---|---|
| 2021_Posth-etal_Applicability-of-self-play-algorithms.pdf | 207.82 kB | Adobe PDF |  Öffnen/Anzeigen |
Zur Langanzeige
Posth, J.-A., Kotlarz, P. K., Hadji Misheva, B., Osterrieder, J., & Schwendner, P. (2021). The applicability of self-play algorithms to trading and forecasting financial markets. Frontiers in Artificial Intelligence, 4(668465). https://doi.org/10.3389/frai.2021.668465
Posth, J.-A. et al. (2021) ‘The applicability of self-play algorithms to trading and forecasting financial markets’, Frontiers in Artificial Intelligence, 4(668465). Available at: https://doi.org/10.3389/frai.2021.668465.
J.-A. Posth, P. K. Kotlarz, B. Hadji Misheva, J. Osterrieder, and P. Schwendner, “The applicability of self-play algorithms to trading and forecasting financial markets,” Frontiers in Artificial Intelligence, vol. 4, no. 668465, May 2021, doi: 10.3389/frai.2021.668465.
POSTH, Jan-Alexander, Piotr Kamil KOTLARZ, Branka HADJI MISHEVA, Jörg OSTERRIEDER und Peter SCHWENDNER, 2021. The applicability of self-play algorithms to trading and forecasting financial markets. Frontiers in Artificial Intelligence. 31 Mai 2021. Bd. 4, Nr. 668465. DOI 10.3389/frai.2021.668465
Posth, Jan-Alexander, Piotr Kamil Kotlarz, Branka Hadji Misheva, Jörg Osterrieder, and Peter Schwendner. 2021. “The Applicability of Self-Play Algorithms to Trading and Forecasting Financial Markets.” Frontiers in Artificial Intelligence 4 (668465). https://doi.org/10.3389/frai.2021.668465.
Posth, Jan-Alexander, et al. “The Applicability of Self-Play Algorithms to Trading and Forecasting Financial Markets.” Frontiers in Artificial Intelligence, vol. 4, no. 668465, May 2021, https://doi.org/10.3389/frai.2021.668465.
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