Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-22664
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dc.contributor.authorPosth, Jan-Alexander-
dc.contributor.authorKotlarz, Piotr Kamil-
dc.contributor.authorHadji Misheva, Branka-
dc.contributor.authorOsterrieder, Jörg-
dc.contributor.authorSchwendner, Peter-
dc.date.accessioned2021-06-17T12:21:49Z-
dc.date.available2021-06-17T12:21:49Z-
dc.date.issued2021-05-31-
dc.identifier.issn2624-8212de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/22664-
dc.description.abstractThe 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.de_CH
dc.language.isoende_CH
dc.publisherFrontiers Research Foundationde_CH
dc.relation.ispartofFrontiers in Artificial Intelligencede_CH
dc.rightshttp://creativecommons.org/licenses/by/4.0/de_CH
dc.subjectArtificial intelligencede_CH
dc.subjectMachine learningde_CH
dc.subjectFinancial marketde_CH
dc.subjectTradingde_CH
dc.subject.ddc006: Spezielle Computerverfahrende_CH
dc.subject.ddc332: Finanzwirtschaftde_CH
dc.titleThe applicability of self-play algorithms to trading and forecasting financial marketsde_CH
dc.typeBeitrag in wissenschaftlicher Zeitschriftde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Management and Lawde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitInstitut für Wealth & Asset Management (IWA)de_CH
zhaw.organisationalunitInstitut für Datenanalyse und Prozessdesign (IDP)de_CH
dc.identifier.doi10.3389/frai.2021.668465de_CH
dc.identifier.doi10.21256/zhaw-22664-
zhaw.funding.euNode_CH
zhaw.issue668465de_CH
zhaw.originated.zhawYesde_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.volume4de_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.author.additionalNode_CH
zhaw.display.portraitYesde_CH
zhaw.monitoring.costperiod2021de_CH
Appears in collections:Publikationen School of Management and Law

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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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