Stock return and cash flow predictability: The role of volatility risk
股票收益与现金流可预测性:波动率风险的作用AI 解读 ↓
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AI 根据所提供的论文材料归类:摘要直接研究收益预测、波动率风险,以及包含潜在波动率因子的结构因子 GARCH 模型。
股票收益与现金流可预测性:波动率风险的作用AI 解读 ↓
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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 does not help in forecasting dividend growth rates. Our equilibrium-based “structural” factor GARCH model permits much more accurate inference than 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.