Testing for episodic predictability in stock returns
نویسندگان
چکیده
Standard tests based on predictive regressions estimated over the full available sample data have tended to find little evidence of predictability in stock returns. Recent approaches analysis subsamples suggest fact that where it occurs might exist only within so-called “pockets predictability” rather than across entire sample. However, these methods are prone criticism subsample dates endogenously determined such use standard critical values appropriate for will result incorrectly sized leading spurious findings returns predictability. To avoid problem endogenously-determined splits, we propose new derived from sequences statistics systematically calculated data. Specifically, base maximum forward and backward recursive, rolling, double-recursive regressions. We develop our approach using over-identified instrumental variable-based test Breitung Demetrescu (2015). This is partial-sum asymptotics so, unlike many other popular including, example, those Bonferroni corrections, can be readily adapted implementation subsamples. show limiting null distributions proposed depend general whether putative predictor strongly or weakly persistent any heteroskedasticity present (indeed time-variation unconditional variance matrix innovations), latter even if heteroskedasticity-robust errors. As a consequence, fixed regressor wild bootstrap implementations which demonstrate first-order asymptotically valid. Finite behaviour against variety temporarily predictable processes considered. An empirical application US illustrates usefulness testing propose.
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ژورنال
عنوان ژورنال: Journal of Econometrics
سال: 2022
ISSN: ['1872-6895', '0304-4076']
DOI: https://doi.org/10.1016/j.jeconom.2020.01.001