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dc.contributor.advisorYiu-Ming Chung, Richard
dc.contributor.advisorLi, Bin
dc.contributor.authorShi, Qi
dc.date.accessioned2018-03-02T04:49:56Z
dc.date.available2018-03-02T04:49:56Z
dc.date.issued2017-02
dc.identifier.doi10.25904/1912/259
dc.identifier.urihttp://hdl.handle.net/10072/370429
dc.description.abstractMy three essays contain three studies using multi-factor asset pricing models, where all the data are based on the US market. The first study extends intertemporal CAPMs with a few macro pricing factors: inflation or the cycle of industrial production (IP). I regard this specification of such models as a multi-factor pricing model, where this multi-factor linear pricing model can alternatively be derived from a consumption-based model from a theoretical perspective. I find significant evidence that the augmented multi-factor models outperform the original ICAPM. The results show that inflation is a key additional factor in the pricing models for the 25 size/book-to-market portfolios, while the cycle of IP is another vital additional factor in pricing models for the 25 size/momentum portfolios. Moreover, I find that most pricing information contained in the momentum factor is the inclusive information of the IP cycle, where the cycle of IP is generated by using the Hodrick–Prescott filter. The second study extends another two ICAPMs and Hou, Karolyi and Kho's three-factor model with inflation. The evidence shows that inflation significantly aids the original models in pricing 25 size/book-to-market portfolios in cross-sectional tests. Hence, I provide further robust evidence that inflation is the vital factor in the factor pricing models for the 25 size/book-to-market portfolios and a few other portfolios. Inflation provides additional explanatory power beyond Fama-French’s five factors in pricing the cross-sectional variation of 25 size/book-to-market portfolios. The third study investigates the performance of multi-factor asset pricing models in explaining the cross-section variation of the large number of expanding portfolios and a set of different portfolios, where the multi-factor models refer to the Fama-French three-factor model augmented by other pricing factors. I investigate the performance of several well-regarded multi-factor models by using Hansen’s general method of momentum (GMM), which is another alternative and very robust complement/guarantee to the only regression-based procedure in the previous literature. The results continuously support the superiority of the augmented multi-factor models. In general, augmented multi-factor models outperform the original models in a sound portion of different portfolios, where the original model refers to Fama-French’s three-factor model. In conclusion, my essays shed light on a fresh type of linear asset pricing model with sound theoretical background, and my research justifies the superiority of the multi-factor pricing model over Fama-French’s three-factor model in explaining the cross-sectional variation of equity returns with robust evidence.
dc.languageEnglish
dc.language.isoen
dc.publisherGriffith University
dc.publisher.placeBrisbane
dc.titleThree Essays on empirical cross-sectional asset pricing using multi-factor pricing models
dc.typeGriffith thesis
gro.facultyGriffith Business School
gro.rights.copyrightThe author owns the copyright in this thesis, unless stated otherwise.
gro.hasfulltextFull Text
gro.thesis.degreelevelThesis (PhD Doctorate)
gro.thesis.degreeprogramDoctor of Philosophy (PhD)
gro.departmentDept Account,Finance & Econ
gro.griffith.authorShi, Qi


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