Show simple item record

dc.contributor.authorSakouvogui, Kekoura
dc.description.abstractLimitations of Capital Asset Pricing Model (CAPM) continue to present inconsistent empirical results despite its rm mathematical foundations provided in recent studies. In this thesis, we examine how estimation errors of the CAPM could be minimized using the cross-validation technique, a concept that is widely applied in machine learning (CV-CAPM). We apply our approach to test the assumption of CAPM as a well-diversified portfolio model with data from S&P500 and Dow Jones Industrial Average (DJIA). Our results from the CV-CAPM validate that both S&P500 and DJIA are well-diversified market indices with statistically insignificant variation in unsystematic risks during and after the 2007 financial crisis. Furthermore, the CV-CAPM provides the smallest root mean square errors and mean absolute deviations compared to the traditional CAPM.en_US
dc.publisherNorth Dakota State Universityen_US
dc.rightsNDSU policy 190.6.2
dc.titleRobust Capital Asset Pricing Model Estimation through Cross-Validationen_US
dc.typeThesisen_US
dc.date.accessioned2018-12-03T21:49:17Z
dc.date.available2018-12-03T21:49:17Z
dc.date.issued2018en_US
dc.identifier.urihttps://hdl.handle.net/10365/29019
dc.subject.lcshCapital assets pricing model.en_US
dc.subject.lcshFinancial risk management.
dc.subject.lcshPortfolio management.
dc.subject.lcshMachine learning.
dc.rights.urihttps://www.ndsu.edu/fileadmin/policy/190.pdf
ndsu.degreeMaster of Science (MS)en_US
ndsu.collegeAgriculture, Food Systems and Natural Resourcesen_US
ndsu.departmentAgribusiness and Applied Economicsen_US
ndsu.programAgribusiness and Applied Economicsen_US
ndsu.advisorNganje, William Evange, 1966-
ndsu.advisorZhang, Lei


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record