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【JFQA】收益可预测性的上界

[发布日期]:2017-05-19  [浏览次数]:

Journal of Financial and Quantitative Analysis · Volume 52, Issue 2 April 2017, pp. 401-425

收益可预测性的上界

作者:Dashan Huang (Singapore Management University), Guofu Zhou (Washington University)

摘要:可以通过现有资产定价模型来解释数据中发现的可预测性程度吗?我们在预测回归的R2上提供两个理论上界。使用市场投资组合和成分投资组合的数据,我们发现实证得到的R2显著大于理论上限。我们的研究结果表明,未来研究的方向应该旨在确定与股票收益高度相关的新状态变量,而不是寻求更精细的随机折现因子。

Institutional Investment Constraints and Stock Prices

Dashan Huang (Singapore Management University), Guofu Zhou (Washington University)

ABSTRACT

Can the degree of predictability found in data be explained by existing asset pricing models? We provide two theoretical upper bounds on the R2 of predictive regressions. Using data on the market portfolio and component portfolios, we find that the empirical R2s are significantly greater than the theoretical upper bounds. Our results suggest that the most promising direction for future research should aim to identify new state variables that are highly correlated with stock returns instead of seeking more elaborate stochastic discount factors.

原文链接:

https://www.cambridge.org/core/journals/journal-of-financial-and-quantitative-analysis/article/upper-bounds-on-return-predictability/BE6998492789B99A40DE24827E03A1BD

翻译:熊进宗



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