Blocks adjustment—reduction of bias and variance of detrended fluctuation analysis using Monte Carlo simulation

Sebastian Michalski

Physica A: Statistical Mechanics and its Applications, 2008, vol. 387, issue 1, 217-242

Abstract: The length of minimal and maximal blocks equally distant on log–log scale versus fluctuation function considerably influences bias and variance of DFA. Through a number of extensive Monte Carlo simulations and different fractional Brownian motion/fractional Gaussian noise generators, we found the pair of minimal and maximal blocks that minimizes the sum of mean-squared error of estimated Hurst exponents for the series of length N=2p,p=7,…,15. Sensitivity of DFA to sort-range correlations was examined using ARFIMA(p,d,q) generator. Due to the bias of the estimator for anti-persistent processes, we narrowed down the range of Hurst exponent to 12⩽H<1.

Keywords: Detrended fluctuation analysis; Scaled windowed variance; Fractional Brownian motion; Hurst exponent; ARFIMA (search for similar items in EconPapers)
Date: 2008
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:387:y:2008:i:1:p:217-242

DOI: 10.1016/j.physa.2007.08.018

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