Abstract
This chapter covers the discussions of model selection tests in empirical asset pricing models with the asymptotic properties developed in Chap. 4. In particular, model selection with forward selection for variables in empirical asset pricing models is introduced. The purpose of this chapter is to consider the sequential model search where model selection tests (or criteria) with additional asymptotic properties for common factors of asset returns are used. Differing from the other empirical studies, the emphasis is on the cross-sectional commonality of these presumed variables or factors when the asset returns are projected onto these variables. Given that the underlying intrinsic mechanism of asset returns is unknown, the sequential model search is to pursue the optimality in approximation that the basic requirement for these presumed variables or factors will satisfy the coherence condition where cross-sectional dependence is persistent.
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Notes
- 1.
Likewise, Hansen et al. (2011) provide the bootstrap applications of MCS procedures since they don’t depend on the orders or sequences of hypothesis tests.
- 2.
Notice that this is only one candidate estimator for the long-run variance. Many other estimates can also be applied and the same convergence in distribution still holds.
- 3.
Notice that the forward-selection sequential model search is not identical to the forward search proposed by Atkinson and Riani (2002). Their approach is based on the increasing subsets of all observations to verify the model.
- 4.
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Jeng, JL. (2018). Hypothesis Testing with Model Search. In: Empirical Asset Pricing Models. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-319-74192-5_5
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DOI: https://doi.org/10.1007/978-3-319-74192-5_5
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