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dc.contributor.advisorSirnes, Espen
dc.contributor.authorDinh, Minh Thi Hong
dc.date.accessioned2017-08-16T08:37:02Z
dc.date.available2017-08-16T08:37:02Z
dc.date.issued2017-08-23
dc.description.abstractWhat drives asset prices in the financial market? How can we predict these prices? Finding the relationship between different factors or between different variables could help to answer these questions. First, links between asset pricing models and other market microstructure variables can be used to investigate sources to explain asset prices. Second, rapid changes in the microstructure of the financial market in which investors can trade with high frequency have provided a platform for researchers to examine the relationship between microstructure variables in high frequency trading. Therefore, this thesis first links two theories, asset pricing and market microstructure, and then focuses on the market microstructure area. In the first paper, the relationship between returns, risk and liquidity in high frequency trading is investigated. The results of this research mainly suggest that in high frequency trading idiosyncratic risk plays a more important role than systematic risk in asset pricing. In addition, liquidity has a higher effect on idiosyncratic risk than systematic risk. In the second paper, the relationship between the spread and the quoted volume imbalance is investigated. The results suggest that for the liquidity sample the relationship is negative if the imbalance is higher than 1, and positive if the imbalance is lower than -1. This means that if the imbalance is high enough, it affects the spread. For low liquidity samples, there is no obvious relationship between them. In the third paper, we investigate whether asymmetric information appearing in the financial market affects the order imbalance reversal effect; the main results suggest that it does.en_US
dc.description.doctoraltypeph.d.en_US
dc.description.popularabstractWhat drives asset prices in the financial market? How can we predict these prices? Finding the relationship between different factors or between different variables could help to answer these questions. First, links between asset pricing models and other market microstructure variables can be used to investigate sources to explain asset prices. Second, rapid changes in the microstructure of the financial market in which investors can trade with high frequency have provided a platform for researchers to examine the relationship between microstructure variables in high frequency trading. Using high frequency data from the Oslo stock market, this thesis focuses on empirical research examining variables that could drive asset prices based on asset pricing models and market microstructure variables. The results of the research confirm that a combination of the traditional asset pricing models and market microstructure variables, and the interaction between market microstructure variables, can help to explain asset prices, and it is suggested that the scope of these findings can be expanded to predict these prices. Explaining and predicting asset prices is not only extremely important for investors who wish profit from their investments, but also for policy makers and regulators who contribute to the design of efficient financial markets, and to the stability of the economy as a whole.en_US
dc.descriptionThe paper 3 of this thesis is not available in Munin. <br> Paper 3: Sirne, E., Dinh, M.T.H.: “The OIB-reversal effect and asymmetric information” (Manuscript).
dc.identifier.urihttps://hdl.handle.net/10037/11295
dc.language.isoengen_US
dc.publisherUiT The Arctic University of Norwayen_US
dc.publisherUiT Norges arktiske universiteten_US
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2017 The Author(s)
dc.subject.courseIDDOKTOR-002
dc.subjectVDP::Social science: 200::Economics: 210::Economics: 212en_US
dc.subjectVDP::Samfunnsvitenskap: 200::Økonomi: 210::Samfunnsøkonomi: 212en_US
dc.titleTopics on market microstructure and asset pricing using intraday data from the Oslo stock market.en_US
dc.typeDoctoral thesisen_US
dc.typeDoktorgradsavhandlingen_US


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