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Conditional nonlinear asset pricing kernels and the size and book-to-market effects

We develop and test asset pricing model formulations that are simultaneously conditional
and nonlinear. Formulations based upon five popular asset pricing models are tested against
the widely studied Fama and French (1993) twenty-five size and book-to-market sorted portfolios.
Test results indicate that the conditional nonlinear specification of the Fama and
French (1993) three state variable model (FF3) is the only specification not rejected by the
data and thus capable of pricing the "size" and "book-to-market" effects simultaneously.
The pricing performance of the FF3 conditional nonlinear pricing kernel is corifirmed by
robustness tests on out-of-sample data as well as tests with alternative instrumental and
conditioning variables. While Bansal and Viswanathan (1993) and Chapman (1997) find
unconditional nonlinear pricing kernels sufficient to capture the size effect alone, our results
indicate that similar unconditional nonlinear pricing kernels considered here do not price the
size and book-to-market effects simultaneously. However, nested model tests indicate that,
in isolation, both conditioning information and nonlinearity significantly improve the pricing
kernel performance for all five asset pricing models. The success of the conditional nonlinear
FF3 model also suggests that the combination of conditioning and nonlinearity is critical
to pricing kernel design. Implications for both academic researchers and practitioners are
considered. / Business, Sauder School of / Finance, Division of / Graduate

Identiferoai:union.ndltd.org:UBC/oai:circle.library.ubc.ca:2429/12968
Date05 1900
CreatorsBurke, Stephen Dean
Source SetsUniversity of British Columbia
LanguageEnglish
Detected LanguageEnglish
TypeText, Thesis/Dissertation
Format6962461 bytes, application/pdf
RightsFor non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use.

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