Pairs trading with wavelet transform

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dc.authoridEroğlu, Burak Alparslan/0000-0001-6814-747X|Yener, Haluk/0000-0003-2654-5810
dc.authorwosidEroğlu, Burak Alparslan/A-8187-2019
dc.contributor.authorEroglu, Burak Alparslan
dc.contributor.authorYener, Haluk
dc.contributor.authorYigit, Taner
dc.date.accessioned2024-07-18T20:45:25Z
dc.date.available2024-07-18T20:45:25Z
dc.date.issued2023
dc.departmentİstanbul Bilgi Üniversitesien_US
dc.description.abstractWe show that applying the wavelet transform to S & P 500 constituents' prices generates a substantial increase in the returns of the pairs-trading strategy. Pairs trading strategy is based on finding prices that move together, but if there is shared noise in the asset prices, the co-movement, on which one base the trades, might be caused by this common noise. We show that wavelet transform filters away the noise, leading to more profitable trades. The most notable change occurs in the parameter estimation stage, which forms the weights of the assets in the pairs portfolio. Without filtering, the parameters estimated in the training period lose relevance in the trading period. However, when prices are filtered from common noise, the parameters maintain relevance much longer and result in more profitable trades. Particularly, we show that more precise parameter estimation is reflected on a more stationary and conservative spread, meaning more mean reversion in opened pairs trades. We also show that wavelet filtering the prices reduces the downside risk of the trades considerably.en_US
dc.identifier.doi10.1080/14697688.2023.2230249
dc.identifier.endpage1154en_US
dc.identifier.issn1469-7688
dc.identifier.issn1469-7696
dc.identifier.issue7.Ağuen_US
dc.identifier.scopus2-s2.0-85164679905en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage1129en_US
dc.identifier.urihttps://doi.org/10.1080/14697688.2023.2230249
dc.identifier.urihttps://hdl.handle.net/11411/7538
dc.identifier.volume23en_US
dc.identifier.wosWOS:001025799100001en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherRoutledge Journals, Taylor & Francis Ltden_US
dc.relation.ispartofQuantitative Financeen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectPairs Tradingen_US
dc.subjectWavelet Transformen_US
dc.subjectMinimum Distance Methoden_US
dc.subjectCointegration Methoden_US
dc.subjectStatistical Arbitrageen_US
dc.subject>en_US
dc.subjectStatistical Arbitrageen_US
dc.subjectCointegrationen_US
dc.subjectStrategiesen_US
dc.subjectRisken_US
dc.subjectPredictabilityen_US
dc.subjectReturnsen_US
dc.titlePairs trading with wavelet transformen_US
dc.typeArticleen_US

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