Detrending Moving Average variance: a derivation of the scaling law

dc.creatorArianos, Sergio
dc.creatorCarbone, Anna
dc.date2006-08-31
dc.date.accessioned2026-07-07T12:54:28Z
dc.date.available2026-07-07T12:54:28Z
dc.descriptionThe Hurst exponent $H$ 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 $ σ_{DMA}^2={1}/{(N-n)}\sum_i [y(i)-\widetilde{y}_n(i)]^2\:$, with $\widetilde{y}_n(i)= {1}/{n}\sum_{k}y(i-k)$ the moving average, $n$ the moving average window and $N$ the dimension of the stochastic series $y(i)$. This ability relies on the property of $σ_{DMA}^2$ to scale as $n^{2H}$. Here, we analytically show that $σ_{DMA}^2$ is equivalent to $C_H n^{2H}$ for $n\gg 1$ and provide an explicit expression for $C_H$.
dc.description11pages, 3 figures. Presented at Int. Conf. on Application of Physics in Financial Analisys (APFA5), June 29 - July 1, 2006 Torino, Italy
dc.identifierhttps://arxiv.org/abs/physics/0608313
dc.identifierhttp://arxiv.org/abs/physics/0608313
dc.identifierPhysica A: Statistical Mechanics and its Applications Volume 382, (2007) Pages 9-15
dc.identifierdoi:10.1016/j.physa.2007.02.074
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/223944
dc.subjectData Analysis, Statistics and Probability
dc.subjectStatistical Finance
dc.titleDetrending Moving Average variance: a derivation of the scaling law
dc.typetext

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