Tug-of-War: Time-Varying Predictability of Stock Returns and Dividend Growth*

Zhu, Xiaoneng

doi:10.1093/rof/rfu047

Cited by 21 publications

(2 citation statements)

References 46 publications

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“…Compared with a typical predictive regression, which assumes a stable relationship between predictors and expected returns, this specification allows for the time-varying predictability of stock returns. This specification is consistent with theoretical arguments (Menzly, Santos, and Veronesi (2004), Santos and Veronesi (2006)) and supported by empirical evidence reported in previous studies (e.g., Lettau and van Nieuwerburgh (2008), Henkel et al (2011), Dangl and Halling (2012), Pettenuzzo et al (2014), andZhu (2015)).…”

Section: B the Cv-dc Modelsupporting

confidence: 92%

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When Are Stocks Less Volatile in the Long Run?

Jondeau

Zhang

Zhu

2020

J. Financ. Quant. Anal.

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Pástor and Stambaugh (2012) find that from a forward-looking perspective, stocks are more volatile in the long run than they are in the short run. We demonstrate that when the nonnegative equity premium (NEP) condition is imposed on predictive regressions, stocks are in fact less volatile in the long run, even after taking estimation risk and uncertainties into account. The reason is that the NEP provides an additional parameter identification condition and prior information for future returns. Combined with the mean reversion of stock returns, this condition substantially reduces uncertainty on future returns and leads to lower long-run predictive variance.

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Section: B the Cv-dc Modelsupporting

confidence: 92%

“…During recessions, investors are more reluctant to take on risk. Because investors are more risk averse, the equity premium is higher, and the return predictability is stronger, consistent with Dangl and Halling (2012) and Zhu (2015), among others.…”

Section: Out-of-sample Prediction In a Simulated Experimentssupporting

confidence: 66%