Local normalization: Uncovering correlations in non-stationary financial time series

被引：29

作者：

Schaefer, Rudi ^{[1
]}

Guhr, Thomas ^{[1
]}

机构：

[1] Univ Duisburg Essen, Fak Phys, Duisburg, Germany

来源：

PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS | 2010年 / 389卷 / 18期

关键词：

Econophysics; Financial correlations; Non-stationarity; Time series analysis; PORTFOLIO OPTIMIZATION; CORRELATION-MATRICES; CROSS-CORRELATIONS; NOISE;

D O I：

10.1016/j.physa.2010.05.030

中图分类号：

O4 [物理学];

学科分类号：

0702 ;

摘要：

The measurement of correlations between financial time series is of vital importance for risk management. In this paper we address an estimation error that stems from the non-stationarity of the time series. We put forward a method to rid the time series of local trends and variable volatility, while preserving cross-correlations. We test this method in a Monte Carlo simulation, and apply it to empirical data for the S&P 500 stocks. (C) 2010 Elsevier B.V. All rights reserved.

引用

页码：3856 / 3865

页数：10

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