Learning about Risk and Return: A Simple Model of Bubbles and Crashes

• 成果类型: Article
• 署名作者: Branch, William A.; Evans, George W.
• 署名单位: University of California System; University of California Irvine; University of Oregon; University of St Andrews
• 刊物名称: AMERICAN ECONOMIC JOURNAL-MACROECONOMICS
• ISSN/ISSBN: 1945-7707
• DOI: 10.1257/mac.3.3.159
• 发表日期: 2011
• 页码: 159-191
• 关键词: stock-prices; Speculative bubbles; Expectations formation; rational-expectations; financial-markets; asset prices; DYNAMICS; STABILITY; CONVERGENCE; inflation

摘要

This paper demonstrates that an asset pricing model with leasts-quares 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. (JEL D81, D83, E32, G01, G12)