| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/t0161 |
| 来源ID | Technical Working Paper 0161 |
| Asymptotically Optimal Smoothing with ARCH Models | |
| Daniel B. Nelson | |
| 发表日期 | 1994-08-01 |
| 出版年 | 1994 |
| 语种 | 英语 |
| 摘要 | Suppose an observed time series is generated by a stochastic volatility model-i.e., there is an unobservable state variable controlling the volatility of the innovations in the series. As shown by Nelson (1992), and Nelson and Foster (1994), a misspecified ARCH model will often be able to consistently (as a continuous time limit is approached) estimate the unobserved volatility process, using information in the lagged residuals. This paper shows how to more efficiently estimate such a volatility process using information in both lagged and led residuals. In particular, this paper expands the optimal filtering results of Nelson and Foster (1994) and Nelson (1994) to smoothing. |
| 主题 | Econometrics ; Estimation Methods |
| URL | https://www.nber.org/papers/t0161 |
| 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/562217 |
| 推荐引用方式 GB/T 7714 | Daniel B. Nelson. Asymptotically Optimal Smoothing with ARCH Models. 1994. |
| 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 | ||
| t0161.pdf（422KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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