dorsal/arxiv
View SchemaSpectral Analysis of Dow Jones Index and Comparison with Model Predicted Cycles During 1900-2005
| Authors | A. M. Selvam |
|---|---|
| Categories | |
| ArXiv ID | physics/0603065 |
| URL | https://arxiv.org/abs/physics/0603065 |
Abstract
The day-to day fluctuations of Dow Jones Index exhibit fractal fluctuations, namely, a zigzag pattern of successive increases followed by decreases on all space-time scales. Self-similar fractal fluctuations are generic to dynamical systems in nature and imply long-range space-time correlations. The apparently unpredictable (chaotic) fluctuations of dynamical systems exhibit underlying order with the power spectra exhibiting inverse power law form, now identified as self-organized criticality. The physics of self-organized criticality is not yet identified. A general systems theory developed by the author shows that self-similar fractal fluctuations are signatures of quantum-like chaos in dynamical systems of all size scales ranging from the subatomic dynamics of quantum systems to macro-scale fluid flows. The model predicts the universal inverse power-law form of the statistical normal distribution for the power spectra of fractal space-time fluctuations of dynamical systems. In this paper it is shown that the power spectrum of 100 years of normalized month to month fluctuations of Dow Jones index exhibits the universal inverse power law form of the statistical normal distribution consistent with model prediction. It is shown that prediction of times of occurrence of maxima and minima during the two years subsequent to the data period used for the study is possible using the dominant peak periodicities obtained from the continuous periodogram spectral analysis of historic data.
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"abstract": "The day-to day fluctuations of Dow Jones Index exhibit fractal fluctuations,\nnamely, a zigzag pattern of successive increases followed by decreases on all\nspace-time scales. Self-similar fractal fluctuations are generic to dynamical\nsystems in nature and imply long-range space-time correlations. The apparently\nunpredictable (chaotic) fluctuations of dynamical systems exhibit underlying\norder with the power spectra exhibiting inverse power law form, now identified\nas self-organized criticality. The physics of self-organized criticality is not\nyet identified. A general systems theory developed by the author shows that\nself-similar fractal fluctuations are signatures of quantum-like chaos in\ndynamical systems of all size scales ranging from the subatomic dynamics of\nquantum systems to macro-scale fluid flows. The model predicts the universal\ninverse power-law form of the statistical normal distribution for the power\nspectra of fractal space-time fluctuations of dynamical systems. In this paper\nit is shown that the power spectrum of 100 years of normalized month to month\nfluctuations of Dow Jones index exhibits the universal inverse power law form\nof the statistical normal distribution consistent with model prediction. It is\nshown that prediction of times of occurrence of maxima and minima during the\ntwo years subsequent to the data period used for the study is possible using\nthe dominant peak periodicities obtained from the continuous periodogram\nspectral analysis of historic data.",
"arxiv_id": "physics/0603065",
"authors": [
"A. M. Selvam"
],
"categories": [
"physics.gen-ph"
],
"title": "Spectral Analysis of Dow Jones Index and Comparison with Model Predicted Cycles During 1900-2005",
"url": "https://arxiv.org/abs/physics/0603065"
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