| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w8554 |
| 来源ID | Working Paper 8554 |
| Theoretical and Empirical properties of Dynamic Conditional Correlation Multivariate GARCH | |
| Robert F. Engle; Kevin Sheppard | |
| 发表日期 | 2001-10-01 |
| 出版年 | 2001 |
| 语种 | 英语 |
| 摘要 | In this paper, we develop the theoretical and empirical properties of a new class of multi-variate GARCH models capable of estimating large time-varying covariance matrices, Dynamic Conditional Correlation Multivariate GARCH. We show that the problem of multivariate conditional variance estimation can be simplified by estimating univariate GARCH models for each asset, and then, using transformed residuals resulting from the first stage, estimating a conditional correlation estimator. The standard errors for the first stage parameters remain consistent, and only the standard errors for the correlation parameters need be modified. We use the model to estimate the conditional covariance of up to 100 assets using S&P 500 Sector Indices and Dow Jones Industrial Average stocks, and conduct specification tests of the estimator using an industry standard benchmark for volatility models. This new estimator demonstrates very strong performance especially considering ease of implementation of the estimator. |
| 主题 | Econometrics ; Estimation Methods ; Financial Economics |
| URL | https://www.nber.org/papers/w8554 |
| 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/566158 |
| 推荐引用方式 GB/T 7714 | Robert F. Engle,Kevin Sheppard. Theoretical and Empirical properties of Dynamic Conditional Correlation Multivariate GARCH. 2001. |
| 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 | ||
| w8554.pdf（689KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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