Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/72975
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dc.date.accessioned2021-04-06T08:07:26Z-
dc.date.available2021-04-06T08:07:26Z-
dc.date.issued2017-
dc.identifier.citationGrech, L. (2017). Testing efficiency of football betting markets using adaptive drift models (Bachelor's dissertation).en_GB
dc.identifier.urihttps://www.um.edu.mt/library/oar/handle/123456789/72975-
dc.descriptionB.SC.(HONS)STATS.&OP.RESEARCHen_GB
dc.description.abstractOver the years, the efficiency of financial markets has been studied extensively in literature, and the interest for investigating notions of efficiency also in the context of sports betting markets has been growing considerably. In its semi-strong form, the efficient market hypothesis holds the concept that a market is efficient if it fully reflects all publicly available information and has the ability to efficiently adapt to new information. Under efficiency, betting strategies based on this information should not be able to generate significant profits and consistent winning patterns. In this study, betting strategies informed by goal difference forecasts obtained from adaptive drift models are used to investigate the efficiency of Asian handicap betting markets for German football games. Findings based on predictions for the 2015/16 and 2016/17 Bundesliga seasons for FC Bayern Munich games suggest that efficiency and the efficient market hypothesis are supported. However, applying similar methodologies for 1. FSV Mainz 05 yields substantial winnings and indicates that inefficiency may be detected among various bookmakers.en_GB
dc.language.isoenen_GB
dc.rightsinfo:eu-repo/semantics/restrictedAccessen_GB
dc.subjectSoccer -- Bettingen_GB
dc.subjectForecasting -- Statistical methodsen_GB
dc.subjectTime-series analysisen_GB
dc.titleTesting efficiency of football betting markets using adaptive drift modelsen_GB
dc.typebachelorThesisen_GB
dc.rights.holderThe copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder.en_GB
dc.publisher.institutionUniversity of Maltaen_GB
dc.publisher.departmentFaculty of Science. Department of Statistics and Operations Researchen_GB
dc.description.reviewedN/Aen_GB
dc.contributor.creatorGrech, Lawrence (2017)-
Appears in Collections:Dissertations - FacSci - 2017
Dissertations - FacSciSOR - 2017

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