股市可预测性的异质信念模型
Heterogeneous Beliefs Model of Stock Market Predictability
AI总结：
本文构建离散有限时间下的异质信念模型，用投资者对随机供给及信号准确性的信念差异内生解释股价动量、反转，并扩展至多资产下的协同变动与领先—滞后效应。
摘要：
本文基于一个异质信念模型提出了一种关于股市可预测性模式的理论。在离散有限时间框架内，部分智能体通过一个含噪信号接收有关资产基本面价值的消息。投资者具有异质性，因为他们对随机供给持有不同信念。股价动量源于那些错误低估信号准确性的智能体，他们抑制了信号对价格的初始影响。价格之所以出现反转，是因为从长期来看价格会回归基本面价值。将该模型扩展到多资产情形后，除横截面动量和反转外，还预测了协同变动和领先—滞后效应。投资者对消息的异质信念表明，主要的可预测性异象如何在一个有限理性模型中内生地产生。
英文摘要：
This paper proposes a theory of stock market predictability patterns based on a model of heterogeneous beliefs. In a discrete finite time framework, some agents receive news about an asset's fundamental value through a noisy signal. The investors are heterogeneous in that they have different beliefs about the stochastic supply. A momentum in the stock price arises from those agents who incorrectly underestimate the signal accuracy, dampening the initial price impact of the signal. A reversal in price occurs because the price reverts to the fundamental value in the long run. An extension of the model to multiple assets case predicts co-movement and lead-lag effect, in addition to cross-sectional momentum and reversal. The heterogeneous beliefs of investors about news demonstrate how the main predictability anomalies arise endogenously in a model of bounded rationality.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
