Estimating investors' behavior and errorsin probabilistic forecasts by the Kolmogorov entropy and noise colors of multifractal attractors
AbstractThis paper investigates the impact of the Kolmogorov-Sinai entropy on both the accuracy of probabilistic forecasts and the sluggishness of economic growth. It first posits the Gaussian process Zt (indexed by the Hurst exponent H) as the output of a reflexive dynamic input/output system governed by some type of attractor. It next indexes families of attractors by the Hausdorff measure (D0) and assesses the uncertainty level plaguing probabilistic forecast in each family. The D0 signature of attractors is next applied to the S&P-500 Index The result allows the construction of the dynamic history of the index and establishes robust links between the Hausdorff dimension, investors’ behavior, and economic growth
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 46231.
Date of creation: 13 Apr 2013
Date of revision: 16 Apr 2013
Stochastic processes; Housdorff dimension; forecasts; entrupy; attractors (strange; complex; low dimensional; chaotic); investors’ behavior; economic growth.;
Find related papers by JEL classification:
- G1 - Financial Economics - - General Financial Markets
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- Dominique, C-Rene & Rivera-Solis, Luis Eduardo, 2012. "Short-term Dependence in Time Series as an Index of Complexity: Example from the S&P-500 Index," MPRA Paper 41408, University Library of Munich, Germany.
- Dominique, C-Rene & Rivera-Solis, Luis Eduardo, 2012. "The dynamics of market share’s growth and competition in quadratic mappings," MPRA Paper 43652, University Library of Munich, Germany.
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