Estimating Investors� Behavior and Errors in Probabilistic Forecasts by the Kolmogorov Entropy and Noise Colors of Non-Hyperbolic Attractors

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Author	C-Ren� Dominique
ISSN	2307-2466
On Pages	370-379
Volume No.	2
Issue No.	5
Issue Date	August 01, 2020
Publishing Date	August 01, 2020
Keywords	Stochastic processes, Hausdorff dimension, forecasts, entrupy, chaotic attractors, investors� behavior, economic growth.

Abstract

This 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 whose attractor is non-hyperbolic. 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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