| 来源类型 | Discussion paper |
| 规范类型 | 论文 |
| 来源ID | DP6223 |
| DP6223 Asset Pricing with Adaptive Learning | |
| Chryssi Giannitsarou; Eva Carceles-Poveda | |
| 发表日期 | 2007-04-23 |
| 出版年 | 2007 |
| 语种 | 英语 |
| 摘要 | We study the extent to which self-referential adaptive learning can explain stylized asset pricing facts in a general equilibrium framework. In particular, we analyze the effects of recursive least squares and constant gain algorithms in a production economy and a Lucas type endowment economy. We find that recursive least squares learning has almost no effects on asset price behaviour, since the algorithm converges relatively fast to rational expectations. On the other hand, constant gain learning may contribute towards explaining the stock price and return volatility as well as the predictability of excess returns in the endowment economy. In the production economy, however, the effects of constant gain learning are mitigated by the persistence induced by capital accumulation. We conclude that, contrary to popular belief, standard self-referential learning cannot fully resolve the asset pricing puzzles observed in the data. |
| 主题 | Financial Economics ; International Macroeconomics |
| 关键词 | Adaptive learning Asset pricing Excess returns Predictability |
| URL | https://cepr.org/publications/dp6223 |
| 来源智库 | Centre for Economic Policy Research (United Kingdom) |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/535080 |
| 推荐引用方式 GB/T 7714 | Chryssi Giannitsarou,Eva Carceles-Poveda. DP6223 Asset Pricing with Adaptive Learning. 2007. |
| 条目包含的文件 | 条目无相关文件。 | |||||
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