| 来源类型 | Discussion paper |
| 规范类型 | 论文 |
| 来源ID | DP10160 |
| DP10160 A Bayesian MIDAS Approach to Modeling First and Second Moment Dynamics | |
| Henry Allan Timmermann; Davide Pettenuzzo | |
| 发表日期 | 2014-09-21 |
| 出版年 | 2014 |
| 语种 | 英语 |
| 摘要 | We propose a new approach to predictive density modeling that allows for MIDAS effects in both the first and second moments of the outcome and develop Gibbs sampling methods for Bayesian estimation in the presence of stochastic volatility dynamics. When applied to quarterly U.S. GDP growth data, we find strong evidence that models that feature MIDAS terms in the conditional volatility generate more accurate forecasts than conventional benchmarks. Finally, we find that forecast combination methods such as the optimal predictive pool of Geweke and Amisano (2011) produce consistent gains in out-of-sample predictive performance. |
| 主题 | Financial Economics |
| 关键词 | Bayesian estimation Gdp growth Midas regressions Out-of-sample forecasts stochastic volatility |
| URL | https://cepr.org/publications/dp10160 |
| 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/538993 |
| 推荐引用方式 GB/T 7714 | Henry Allan Timmermann,Davide Pettenuzzo. DP10160 A Bayesian MIDAS Approach to Modeling First and Second Moment Dynamics. 2014. |
| 条目包含的文件 | 条目无相关文件。 | |||||
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。
