| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/t0163 |
| 来源ID | Technical Working Paper 0163 |
| Continuous Record Asymptotics for Rolling Sample Variance Estimators | |
| Dean P. Foster; Daniel B. Nelson | |
| 发表日期 | 1994-08-01 |
| 出版年 | 1994 |
| 语种 | 英语 |
| 摘要 | It is widely known that conditional covariances of asset returns change over time. Researchers adopt many strategies to accommodate conditional heteroskedasticity. Among the most popular are: (a) chopping the data into short blocks of time and assuming homoskedasticity within the blocks, (b) performing one-sided rolling regressions, in which only data from, say, the preceding five year period is used to estimate the conditional covariance of returns at a given date, and (c) two-sided rolling regressions which use, say, five years of leads and five years of lags. GARCH amounts to a one-sided rolling regression with exponentially declining weights. We derive asymptotically optimal window lengths for standard rolling regressions and optimal weights for weighted rolling regressions. An empirical model of the S&P 500 stock index provides an example. |
| 主题 | Econometrics ; Estimation Methods |
| URL | https://www.nber.org/papers/t0163 |
| 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/562219 |
| 推荐引用方式 GB/T 7714 | Dean P. Foster,Daniel B. Nelson. Continuous Record Asymptotics for Rolling Sample Variance Estimators. 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 | ||
| t0163.pdf（2668KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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