| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w10934 |
| 来源ID | Working Paper 10934 |
| A Simulation Approach to Dynamic Portfolio Choice with an Application to Learning About Return Predictability | |
| Michael W. Brandt; Amit Goyal; Pedro Santa-Clara; Jonathan Storud | |
| 发表日期 | 2004-11-29 |
| 出版年 | 2004 |
| 语种 | 英语 |
| 摘要 | We present a simulation-based method for solving discrete-time portfolio choice problems involving non-standard preferences, a large number of assets with arbitrary return distribution, and, most importantly, a large number of state variables with potentially path-dependent or non-stationary dynamics. The method is flexible enough to accommodate intermediate consumption, portfolio constraints, parameter and model uncertainty, and learning. We first establish the properties of the method for the portfolio choice between a stock index and cash when the stock returns are either iid or predictable by the dividend yield. We then explore the problem of an investor who takes into account the predictability of returns but is uncertain about the parameters of the data generating process. The investor chooses the portfolio anticipating that future data realizations will contain useful information to learn about the true parameter values. |
| 主题 | Financial Economics ; Financial Markets |
| URL | https://www.nber.org/papers/w10934 |
| 来源智库 | National Bureau of Economic Research (United States) |
| 引用统计 | |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/568569 |
| 推荐引用方式 GB/T 7714 | Michael W. Brandt,Amit Goyal,Pedro Santa-Clara,et al. A Simulation Approach to Dynamic Portfolio Choice with an Application to Learning About Return Predictability. 2004. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
| w10934.pdf（377KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。
