英文文献：Predictable return distributions-可预测的回报分布
英文文献作者：Thomas Q. Pedersen
英文文献摘要：
This paper provides detailed insights into predictability of the entire stock and bond return distribution through the use of quantile regression. This allows us to examine speci?c parts of the return distribution such as the tails or the center, and for a suf?ciently ?ne grid of quantiles we can trace out the entire distribution. A univariate quantile regression model is used to examine stock and bond return distributions individually, while a multivariate model is used to capture their joint distribution. An empirical analysis on US data shows that certain parts of the return distributions are predictable as a function of economic state variables. The results are, however, very different for stocks and bonds. The state variables primarily predict only location shifts in the stock return distribution, while they also predict changes in higher-order moments in the bond return distribution. Out-of-sample analyses show that the relative accuracy of the state variables in predicting future returns varies across the distribution. A portfolio study shows that an investor with power utility can obtain economic gains by applying the empirical return distribution in portfolio decisions instead of imposing an assumption of lognormally distributed returns.

本文通过分位数回归的使用，对整个股票和债券收益分布的可预测性提供了详细的见解。这允许我们检查特殊?c部分的回报分布，如尾部或中心，而suf?用精确的分位数网格可以追踪出整个分布。用单变量分位数回归模型分别考察股票和债券的收益分布，用多变量回归模型考察它们的联合分布。对美国数据的实证分析表明，收益分布的某些部分是可预测的经济状态变量的函数。然而，股票和债券的结果却截然不同。状态变量主要预测股票收益分布的位置变化，同时也预测债券收益分布的高阶矩的变化。样本外分析表明，状态变量在预测未来收益方面的相对准确性在分布上各不相同。投资组合研究表明，在投资组合决策中应用经验收益分布，可以使具有电力效用的投资者获得经济收益，而不必强加对数正态分布收益的假设。