Learning about Risk and Return: A Simple Model of Bubbles and Crashes
展示了一个基于最小二乘学习的资产定价模型，其中泡沫和崩盘是基本面驱动价格的内生反应，风险厌恶的代理人需要预测股票回报的条件方差，递归更新导致学习影响股价的多种机制。
This paper demonstrates that an asset pricing model with least-squares learning can lead to bubbles and crashes as endogenous responses to the fundamentals driving asset prices. When agents are risk-averse they need to make forecasts of the conditional variance of a stock's return. Recursive updating of both the conditional variance and the expected return implies several mechanisms through which learning impacts stock prices. Extended periods of excess volatility, bubbles, and crashes arise with a frequency that depends on the extent to which past data is discounted. A central role is played by changes over time in agents' estimates of risk.