On Similarity of Financial Data Series Based on Fractal Dimension
Financial time series show the non-linear and fractal characters in the process of time-space kinetics evolution. Traditional dimension reduction methods for similarity query introduce the smoothness to data series in some degree. In the case of unknowing the fractal dimension of financial non- stationary time series, the process of querying the similarity of curve figure will be affected to a certain degree. In this paper, an evaluation formula of varying-time Hurst index is established and the algorithm of varying-time index is presented, and a new determinant standard of series similarity is also introduced. The similarity of curve basic figure is queried and measured at some resolution ratio level. In the meantime, the fractal dimension in local similarity is matched. The effectiveness of the method is validated by means of the simulation examples.
KeywordsFractal Dimension Wavelet Transformation Financial Time Series Similarity Query Fractal Character
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