Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-21531
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dc.contributor.authorSchmidhuber, Christoph-
dc.date.accessioned2021-02-04T10:21:38Z-
dc.date.available2021-02-04T10:21:38Z-
dc.date.issued2021-
dc.identifier.issn0378-4371de_CH
dc.identifier.issn1873-2119de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/21531-
dc.description.abstractFinancial markets across all asset classes are known to exhibit trends, which have been exploited by traders for decades. However, a closer look at the data reveals that those trends tend to revert when they become too strong. Here, we empirically measure the interplay between trends and reversion in detail, based on 30 years of daily futures prices for equity indices, interest rates, currencies and commodities. We find that trends tend to revert before they become statistically significant. Our key observation is that tomorrow's expected return follows a cubic polynomial of today's trend strength. The positive linear term of this polynomial represents trend persistence, while its negative cubic term represents trend reversal. Their precise coe fficients determine the critical trend strength, beyond which trends tend to revert. These coefficients are small but statistically highly significant, if decades of data for many different markets are combined. We confirm this by bootstrapping and out-of-sample testing. Moreover, we find that these coefficients are universal across asset classes and have a universal scaling behavior, as the trend's time horizon runs from a few days to several years. We also measure the rate, at which trends have become less persistent, as markets have become more effi cient over the decades. Our empirical results point towards a potential deep analogy between financial markets and critical phenomena. In this analogy, the trend strength plays the role of an order parameter, whose dynamics is described by a Langevin equation. The cubic polynomial is the derivative of a quartic potential, which plays the role of the energy. This supports the conjecture that financial markets can be modeled as statistical mechanical systems near criticality, whose microscopic constituents are Buy/Sell orders.de_CH
dc.language.isoende_CH
dc.publisherElsevierde_CH
dc.relation.ispartofPhysica A: Statistical Mechanics and its Applicationsde_CH
dc.rightshttp://creativecommons.org/licenses/by/4.0/de_CH
dc.subjectTrend followingde_CH
dc.subjectMean reversionde_CH
dc.subjectFuture marketde_CH
dc.subjectMarket efficiencyde_CH
dc.subjectCritical phenomenonde_CH
dc.subjectSocial networkde_CH
dc.subject.ddc332: Finanzwirtschaftde_CH
dc.titleTrends, reversion, and critical phenomena in financial marketsde_CH
dc.typeBeitrag in wissenschaftlicher Zeitschriftde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitInstitut für Datenanalyse und Prozessdesign (IDP)de_CH
dc.identifier.doi10.1016/j.physa.2020.125642de_CH
dc.identifier.doi10.21256/zhaw-21531-
zhaw.funding.euNode_CH
zhaw.issue125642de_CH
zhaw.originated.zhawYesde_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.volume566de_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.funding.snf190659de_CH
zhaw.author.additionalNode_CH
zhaw.display.portraitYesde_CH
Appears in collections:Publikationen School of Engineering

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