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Unit root tests in finance

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dc.contributor.author Jreij, Rima
dc.date.accessioned 2020-09-29T05:49:44Z
dc.date.available 2020-09-29T05:49:44Z
dc.date.issued 2020
dc.identifier.citation Jreij, R. (2020). Unit root tests in finance (Master's thesis, Notre Dame University-Louaize, Zouk Mosbeh, Lebanon). Retrieved from http://ir.ndu.edu.lb/123456789/1214
dc.identifier.uri http://ir.ndu.edu.lb/123456789/1214
dc.description M.S. -- Faculty of Natural and Applied Sciences, Notre Dame University, Louaize, 2020; "A thesis submitted to the Faculty of Natural and Applied Sciences in partial fulfillment of the requirements for the degree of Master of Science in Financial Mathematics"; Includes bibliographical references (pages 60-63).
dc.description.abstract The knowledge of whether a time series contains a unit root or not provides guidance to determine whether the series is stationary or not. This topic is one that covers vast amount of research given to its importance in the analysis of economic and other time series data. To understand the behavior, the properties of the series and the influence of any shock that occur to the series, stationary and unit root tests were constructed. In this thesis, we first present the Box and Jenkins ARMA models, discuss the conditions for station-arity. Then, we display different method to test autocorrelation. And finally, we examine several unit root tests and discuss their power. en_US
dc.format.extent viii, 65 pages : illustrations
dc.language.iso en en_US
dc.publisher Notre Dame University-Louaize en_US
dc.rights Attribution-NonCommercial-NoDerivs 3.0 United States *
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/us/ *
dc.subject.lcsh Box-Jenkins forecasting
dc.subject.lcsh Econometric models
dc.subject.lcsh Economic forecasting--Mathematical models
dc.title Unit root tests in finance en_US
dc.type Thesis en_US
dc.rights.license This work is licensed under a Creative Commons Attribution-NonCommercial 3.0 United States License. (CC BY-NC 3.0 US)
dc.contributor.supervisor Haddad, John, Ph.D. en_US
dc.contributor.department Notre Dame University-Louaize. Department of Mathematics and Statistics en_US


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