In their out-of-sample predictions of stock returns in the presence of structural breaks, Lettau and Van Nieuwerburgh (2008) implicitly assume that economic agents’ perception of the regime-specific mean for the dividend-price ratio is time-invariant within a regime. In this paper, we challenge this assumption and employ least squares learning with constant gain (or constant-gain learning) in estimating economic agents’ time-varying perception for the mean of dividend-price ratio. We obtain better out-of-sample predictions of stock returns than in Lettau and Van Nieuwerburgh (2008) for both the U.S. and Japanese stock markets. Our empirical results suggest that economic agents’ learning plays an important role in the dynamics of stock returns.

Lettau和Van Nieuwerburgh（2008）在存在结构性断裂的情况下对股票收益的样本外预测中，隐含地假设经济主体对特定制度性均价与股息价格比的感知在一定时间内是不变的。政权。在本文中，我们对这一假设提出了挑战，并在估计经济主体对股息价格比均值的时变感知时，采用具有恒定增益（或恒定增益学习）的最小二乘学习。对于美国和日本股市，我们获得的股票收益的样本外预测要比Lettau和Van Nieuwerburgh（2008）更好。我们的经验结果表明，经济主体的学习在股票回报的动态中起着重要作用。