Large dimension forecasting models and random singular value spectra

Jean-Philippe Bouchaud, Laurent Laloux, M. Augusta Miceli and Marc Potters ()
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Jean-Philippe Bouchaud: Science & Finance, Capital Fund Management
Laurent Laloux: Science & Finance, Capital Fund Management

No 500066, Science & Finance (CFM) working paper archive from Science & Finance, Capital Fund Management

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 Mar?cenko-Pastur distribution for the case of rectangular correlation matrices. We illustrate the interest of our method on a set of macroeconomic time series.

New Economics Papers: this item is included in nep-ecm, nep-ets, nep-for and nep-mac
Date: 2005-12
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Working Paper: Large dimension forecasting models and random singular value spectra (2005)
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