By analyzing ] financial time series of exceptional events such as bubbles and crashes, we confirm the existence of nonlinear potential forces in the markets. The shape of the potential function changes rather slowly and smoothly, thereby enabling a statistical prediction of market prices for a limited time range in the mathematical sense. This predictability does not ensure profits, but is expected to be applicable for averting catastrophes .
Basic peculiarities of market price fluctuations are known to be well described by a recently developed random walk model in a temporally deforming quadric potential force whose center is given by a moving average of past price traces Physica A 370, pp91-97, 2006]. By analyzing high-frequency financial time series of exceptional events such as bubbles and crashes, we confirm the appearance of nonlinear potential force in the markets. We show statistical significance of its existence by applying the information criterion. This new time series analysis is expected to be applied widely for detecting a non-stationary symptom in random phenomena .
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By analyzing
Basic peculiarities of market price fluctuations are known to be well described by a recently developed random walk model in a temporally deforming quadric potential force whose center is given by a moving average of past price traces
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Physica A 370, pp91-97, 2006
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. By analyzing high-frequency
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existence
appearance
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forces
force
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The shape of the potential function changes rather slowly and smoothly, thereby enabling a statistical prediction of market prices for a limited time range in the mathematical sense. This predictability does not ensure profits, but
We show statistical significance of its existence by applying the information criterion. This new time series analysis
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applicable for averting catastrophes
applied widely for detecting a non-stationary symptom in random phenomena