We have reported on the scaling properties of long-range correlated stochastic series y(i) as obtained by the computational procedure recently proposed by us. This procedure makes use of the function DMA defined by the Eq.(3) that exhibits the remarkable properties to vary as a power-law, with exponent H. of the amplitude n of the moving average window. The DMA algorithm has been applied to the German Bobl and Dax future data, sampled every minute. The Bobl future is a derivative of a ten years maturity, 5% coupon German Government security. The Dax Future is the derivative of the main German stock index and thereby represents a measure of expectations of both stock market growth and in general of economic growth in German and generally in the European Union area. The DMA technique has revealed high accuracy and speed of execution.
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