Large dimension forecasting models and random singular value spectra

J.-P. Bouchaud (), L. Laloux, Maria-Augusta Miceli and M. Potters

The European Physical Journal B: Condensed Matter and Complex Systems, 2007, vol. 55, issue 2, 201-207

Abstract: We present a general method to detect and extract from a finite time sample statistically meaningful correlations between input and output variables of large dimensionality. Our central result is derived from the theory of free random matrices, and gives an explicit expression for the interval where singular values are expected in the absence of any true correlations between the variables under study. Our result can be seen as the natural generalization of the Marčenko-Pastur distribution for the case of rectangular correlation matrices. We illustrate the interest of our method on a set of macroeconomic time series. Copyright EDP Sciences/Società Italiana di Fisica/Springer-Verlag 2007

Keywords: 05.45.Tp Time series analysis, 02.10.Yn Matrix theory, 89.65.Gh Economics; econophysics, financial markets, business and management, (search for similar items in EconPapers)
Date: 2007
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Citations: View citations in EconPapers (12)

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Persistent link: https://EconPapers.repec.org/RePEc:spr:eurphb:v:55:y:2007:i:2:p:201-207

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DOI: 10.1140/epjb/e2006-00204-0

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