Analysis of non-stationary dynamics in the financial system

被引：18

作者：

Guharay, Samar K. ^{[1
]}

Thakur, Gaurav S. ^{[1
]}

Goodman, Fred J. ^{[1
]}

Rosen, Scott L. ^{[1
]}

Houser, Daniel ^{[2
]}

机构：

[1] Mitre Corp, Mclean, VA 22102 USA

[2] George Mason Univ, Dept Econ, Fairfax, VA 22030 USA

来源：

ECONOMICS LETTERS | 2013年 / 121卷 / 03期

关键词：

Non-stationary time series; Functional PCA; Synchrosqueezing; Multi-time scale characteristics; Detection of macroeconomic instability; STATISTICAL-INFERENCE; RISK; TIME;

D O I：

10.1016/j.econlet.2013.09.026

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

Novel data-driven analyses, appropriate for detecting economic instability in non-stationary time series, are developed using functional principal component analysis (fPCA) and Synchrosqueezing. fPCA is applied in a new way, aggregating multiple financial time series to identify periods of macroeconomic instability. Synchrosqueezing, a technique which generates a time-series' time-dependent spectral decomposition, is modified to develop a new quantitative measure of local dynamical changes and structural breaks. The merit of this integrated technique is demonstrated by analyzing financial data from 1986 to 2012 that includes equity indices, securities and commodities, and foreign exchange. Both procedures successfully detect key historic periods of instability. Moreover, the results reveal distinctions between periods of long-term gradual change in addition to structural breaks. These tools offer new insights into the analysis of financial instability. (C) 2013 Elsevier B.V. All rights reserved.

引用

页码：454 / 457

页数：4

共 21 条

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