Long Term Economic Relationships From Cointegration Maps
物理与社会
2009-11-13 v2 数据分析、统计与概率
统计金融
摘要
We employ the Bayesian framework to define a cointegration measure aimed to represent long term relationships between time series. For visualization of these relationships we introduce a dissimilarity matrix and a map based on the Sorting Points Into Neighborhoods (SPIN) technique, which has been previously used to analyze large data sets from DNA arrays. We exemplify the technique in three data sets: US interest rates, monthly inflation rates and gross domestic product growth rates.
引用
@article{arxiv.physics/0701062,
title = {Long Term Economic Relationships From Cointegration Maps},
author = {Renato Vicente and Carlos de B. Pereira and Vitor B. P. Leite and Nestor Caticha},
journal= {arXiv preprint arXiv:physics/0701062},
year = {2009}
}
备注
13 pages, 8 figures, extended version submitted to Physica A