A New Test on Asset Return Predictability with Structural Breaks

Zongwu Cai and Seong Yeon Chang

Journal of Financial Econometrics, 2024, vol. 22, issue 4, 1042-1074

Abstract: This article considers predictive regressions in which a structural break is allowed on an unknown date. We establish novel testing procedures for asset return predictability using empirical likelihood (EL) methods based on weighted score equations. The theoretical results are useful in practice because our unified framework does not require distinguishing whether the predictor variables are stationary or non-stationary. Monte Carlo simulation studies show that the EL-based tests perform well in terms of size and power in finite samples. Finally, as an empirical analysis, we test the predictability of the monthly S&P 500 value-weighted log excess return using various predictor variables.

Keywords: autoregressive process; empirical likelihood; structural break; unit root; weighted estimation (search for similar items in EconPapers)
JEL-codes: C12 C14 C32 G12 (search for similar items in EconPapers)
Date: 2024
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