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A simple nonlinear predictive model for stock returns

Biqing Cai and Jiti Gao

No 18/17, Monash Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics

Abstract: In this paper, we propose a simple approach to testing and modelling nonlinear predictability of stock returns using Hermite Functions. The proposed test suggests that there exists a kind of nonlinear predictability for the dividend yield. Furthermore, the out-of-sample evaluation results suggest the dividend yield has nonlinear predictive power for stock returns while the book-to-market ratio and earning-price ratio have little predictive power.

Keywords: Hermite functions; out-of-sample forecast; return predictability; series estimator; unit root. (search for similar items in EconPapers)
JEL-codes: C14 C22 G17 (search for similar items in EconPapers)
Pages: 27
Date: 2017
New Economics Papers: this item is included in nep-cfn, nep-ecm, nep-fmk, nep-for and nep-ore
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