.png){kind=icon}
返回
An asymptotic analysis of likelihood-based diffusion model selection using high frequency data
.png){kind=icon}
PRE
AI
DOI：10.1016/j.jeconom.2013.08.036.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
We provide a new asymptotic analysis of model selection procedure that compares likelihoods of two candidate diffusion models. Our asymptotic analysis relies on two dimensional asymptotic expansions with shrinking sampling interval Delta and increasing sampling span T, and clarifies the different roles of drift and diffusion functions in the selection of diffusion models. In particular, we show that the model with superior diffusion function specification is always preferred to the competing model regardless of their drift specifications if Delta is sufficiently small relative to T. The specifications of drift functions matter only when the models have an identical diffusion specification. (C) 2013 Elsevier B.V. All rights reserved.
Keyword:
Diffusion
Model selection
High frequency observation
Likelihood ratio
Information criterion
Spot interest rate
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:
4
论文数:
5.3K
被引数:
3.0W
机构
引用论文
分享收藏Distribution-Based Entropy Weighting Clustering of Skewed and Heavy Tailed Time Series.png)
Symmetry
OAAI
SymmetryIF0
OAAI分享收藏Maximum likelihood estimation of discretely sampled diffusions:: A closed-form approximation approach离散采样扩散的最大似然估计:: 一种封闭形式的近似方法ECONOMETRICA
ECONOMETRICAIF7.1
PREAI
分享收藏
查看更多内容