English

Detrending Moving Average variance: a derivation of the scaling law

Data Analysis, Statistics and Probability 2009-03-20 v1 Statistical Finance

Abstract

The Hurst exponent HH of long range correlated series can be estimated by means of the Detrending Moving Average (DMA) method. A computational tool defined within the algorithm is the generalized variance σDMA2=1/(Nn)i[y(i)y~n(i)]2 \sigma_{DMA}^2={1}/{(N-n)}\sum_i [y(i)-\widetilde{y}_n(i)]^2\:, with y~n(i)=1/nky(ik)\widetilde{y}_n(i)= {1}/{n}\sum_{k}y(i-k) the moving average, nn the moving average window and NN the dimension of the stochastic series y(i)y(i). This ability relies on the property of σDMA2\sigma_{DMA}^2 to scale as n2Hn^{2H}. Here, we analytically show that σDMA2\sigma_{DMA}^2 is equivalent to CHn2HC_H n^{2H} for n1n\gg 1 and provide an explicit expression for CHC_H.

Keywords

Cite

@article{arxiv.physics/0608313,
  title  = {Detrending Moving Average variance: a derivation of the scaling law},
  author = {Sergio Arianos and Anna Carbone},
  journal= {arXiv preprint arXiv:physics/0608313},
  year   = {2009}
}

Comments

11pages, 3 figures. Presented at Int. Conf. on Application of Physics in Financial Analisys (APFA5), June 29 - July 1, 2006 Torino, Italy