.png){kind=icon}
返回
Average conditional correlation and tree structures for multivariate GARCH models
.png){kind=icon}
OA
AI
DOI：10.1002/for.1014.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
We propose a simple class of multivariate GARCH models, allowing for time-varying conditional correlations. Estimates for time-varying conditional correlations are constructed by means of a convex combination of averaged correlations (across all series) and dynamic realized (historical) correlations. Our model is very parsimonious. Estimation is computationally feasible in very large dimensions without resorting to any variance reduction technique. We back-test the models on a six-dimensional exchange-rate time series using different goodness-of-fit criteria and statistical tests. We collect empirical evidence of their strong predictive power, also in comparison to alternative benchmark procedures. Copyright (C) 2006 John Wiley & Sons, Ltd.
Keyword:
multivariate GARCH models
dynamic conditional correlations
tree-structured GARCH models
model confidence set approach
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
2.7
论文数:
2.3K
被引数:
3.0K
机构
暂无机构信息
引用论文
.png){kind=icon}
分享收藏
查看更多内容