Predictable Risks and Predictive Regression in Present-Value Models

Piatti, Ilaria; Trojani, Fabio

doi:10.2139/ssrn.1786897

Cited by 9 publications

(8 citation statements)

References 69 publications

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“…6 In contrast to these studies, our focus is on the joint predictability of returns and cash flows within the context of a "structural" econometric model explicitly designed to accommodate time-varying volatility in an internally consistent fashion. Recent studies by Binsbergen and Koijen (2010) and Piatti and Trojani (2012) have also relied on a latent variable approach with heteroskedastic shocks for incorporating the effect of time-varying volatility within a present-value framework. Importantly, however, we differ from both of these studies by specifying an empirically more realistic two-factor 4 Nakamura, Sergeyev, and Steinsson (2012) have recently shown how the long-run growth factor may also be identified from cross-country aggregate consumption data under additional simplifying assumptions.…”

Section: Introductionmentioning

confidence: 99%

Stock Return and Cash Flow Predictability: The Role of Volatility Risk

Bollerslev

Zhou

2012

SSRN Journal

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We examine the joint predictability of return and cash flow within a present value framework, by imposing the implications from a long-run risk model that allow for both time-varying volatility and volatility uncertainty. We provide new evidence that the expected return variation and the variance risk premium positively forecast both short-horizon returns and dividend growth rates. We also confirm that dividend yield positively forecasts long-horizon returns, but that it cannot forecast dividend growth rates. Our equilibrium-based "structural" factor GARCH model permits much more accurate inference than the reduced form VAR and univariate regression procedures traditionally employed in the literature. The model also allows for the direct estimation of the underlying economic mechanisms, including a new volatility leverage effect, the persistence of the latent long-run growth component and the two latent volatility factors, as well as the contemporaneous impacts of the underlying "structural" shocks. JEL classification: G12, G13, C12, C13. AbstractWe examine the joint predictability of return and cash flow within a present value framework, by imposing the implications from a long-run risk model that allow for both time-varying volatility and volatility uncertainty. We provide new evidence that the expected return variation and the variance risk premium positively forecast both short-horizon returns and dividend growth rates.We also confirm that dividend yield positively forecasts long-horizon returns, but that it cannot forecast dividend growth rates. Our equilibrium-based "structural" factor GARCH model permits much more accurate inference than the reduced form VAR and univariate regression procedures traditionally employed in the literature. The model also allows for the direct estimation of the underlying economic mechanisms, including a new volatility leverage effect, the persistence of the latent long-run growth component and the two latent volatility factors, as well as the contemporaneous impacts of the underlying "structural" shocks. JEL classification: G12, G13, C12, C13.

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Section: Introductionmentioning

confidence: 99%

Stock Return and Cash Flow Predictability: The Role of Volatility Risk

Bollerslev

Zhou

2012

SSRN Journal

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“…Rapach, Strauss, and Zhou (), Henkel, Martin, and Nardari (), Dangl and Halling (), and Piatti and Trojani () find that macro variables, such as the price‐dividend ratio, have better predictive power in recessions. Similarly, Cen, Wei, and Yang () and Loh and Stulz () find that return predictability using investor disagreement, as proxied by the dispersion in analysts' forecasts (Diether, Malloy, and Scherbina ()), concentrates in recessions.…”

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confidence: 99%

Why Does Return Predictability Concentrate in Bad Times?

Cujean¹,

Hasler

2017

The Journal of Finance

149

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We build an equilibrium model to explain why stock return predictability concentrates in bad times. The key feature is that investors use different forecasting models, and hence assess uncertainty differently. As economic conditions deteriorate, uncertainty rises and investors' opinions polarize. Disagreement thus spikes in bad times, causing returns to react to past news. This phenomenon creates a positive relation between disagreement and future returns. It also generates time‐series momentum, which strengthens in bad times, increases with disagreement, and crashes after sharp market rebounds. We provide empirical support for these new predictions.

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“…For comparability with Binsbergen and Koijen (2010) we adopt their identification assumption ρ gd = 0. More general identification assumptions allowing for a non-zero correlation between expected and realized dividends do not affect our predictability findings, see also Piatti and Trojani (2017).…”

Section: Dividend and Return Predictabilitymentioning

confidence: 72%

Dividend Growth Predictability and the Price–Dividend Ratio

Piatti

Trojani

2020

Management Science

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Asymptotic tests over-reject the null of no predictability in present-value models. We develop a nonparametric testing approach in state space models, implying reliable finite sample inference under weak assumptions on price-dividend ratio and dividend shocks. We find sharp evidence of return predictability in postwar US data, but a less consistent evidence of dividend predictability, which is significant only using cash-flow proxies reflecting information from mergers and acquisitions. These findings reconcile the diverging conclusions of present-value models and common predictive regressions, in a way that is robust to the choice of the predictive variables, the sample period and alternative cash-flow proxies.

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Predictable Risks and Predictive Regression in Present-Value Models

Cited by 9 publications

References 69 publications

Stock Return and Cash Flow Predictability: The Role of Volatility Risk

Stock Return and Cash Flow Predictability: The Role of Volatility Risk

Why Does Return Predictability Concentrate in Bad Times?

Dividend Growth Predictability and the Price–Dividend Ratio

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