Learning, Specification Search and Market Efficiency. With an Application to the Danish Stock Market
提出一种新方法检验半强式市场效率，投资者通过动态显著性准则进行模型搜索并递归预测，应用于丹麦股市（1982-91），发现基于递归预测的投资组合比市场指数有更高平均收益和更低方差。
A new methodology is adopted for testing semistrong efficiency in financial markets where investors do not know the underlying data-generating model. Based on ideas from the literature on learning, it is shown that investors can use a dynamic significance criterion to conduct a specification search and select a model from which predictions can be computed recursively. Applied to the Danish stock market over the period 1982-91, a portfolio based on such recursive predictions is found to provide a higher mean return with a lower variance than the market index. Copyright 1993 by The editors of the Scandinavian Journal of Economics.