A new method to estimate the noise in financial correlation matrices
Source: Journal of Physics A: Mathematical and General, Volume 36, Number 12, 2003 , pp. 3009-3032(24)
Publisher: Institute of Physics Publishing
- Free Content
- New Content
- Subscribed Content
- Free Trial Content
Abstract:
Companies belonging to the same industrial branch are subject to similar economical influences. Hence, the time series of their stocks can show similar trends implying a correlation. Financial correlation matrices measure the unsystematic correlations between time series of stocks. Such information is important for risk management. It has been found by Laloux et al that the correlation matrices are 'noise dressed', a major reason being the finiteness of the time series. We present a new and alternative method to estimate this noise. We introduce a power mapping of the elements in the correlation matrix which suppresses the noise and thereby effectively 'prolongs' the time series. Neither further data processing nor additional input is needed. To develop and test our method, we use a model suggested by Noh which can be viewed as a special case of a 'factor model' in economics. We perform numerical simulations for the time series and obtain correlation matrices. We support the numerics by a qualitative analytical discussion. With our approach, different correlation structures buried under this noise can be detected. Our method is general and can be applied to all systems in which time series are measured.
Language: English
Document Type: Miscellaneous
Affiliations: 1: Matematisk Fysik, LTH, Lunds Universitet, Box 118, 22100 Lund, Sweden 2: Max Planck Institut für Kernphysik, Postfach 103980, 69029 Heidelberg, Germany
- Free Content
- New Content
- Subscribed Content
- Free Trial Content
Click here for Page Help