Robust q Theory

2020 SFS Cavalcade North America Conference

73 Pages Posted: 24 May 2018 Last revised: 17 Aug 2021

Date Written: May 10, 2018

Abstract

Models of the q theory typically assume that investments are determined by a specific approximating structured q model, hence ruling out perturbations due to a set of statistically nearby unstructured alternatives. This paper formulates a generalized framework, where concern to unstructured q models is admissible. By adopting relative entropy restriction for a set of unstructured alternative models, the model delivers generalized approximation to the ”truth” of the q theory, thereby resolving several puzzles in structured q models. By exploiting polynomial specifications and novel measures of perturbations, I empirically demonstrate the critical importance of the approximation error driven by unstructured models.

Keywords: Perurbations, misspecification, approximation error, relative entropy, unstructured models, Tobin’s q.

JEL Classification: E22, E23, G30, O30

Suggested Citation

Qi, Qian, Robust q Theory (May 10, 2018). 2020 SFS Cavalcade North America Conference, Available at SSRN: https://ssrn.com/abstract=3176532 or http://dx.doi.org/10.2139/ssrn.3176532

Qian Qi (Contact Author)

Peking University ( email )

No. 38 Xueyuan Road
Haidian District
Beijing, Beijing 100871
China

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