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On Hurst exponent estimation under heavy-tailed distributions
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SYSNO ASEP 0343525 Druh ASEP J - Článek v odborném periodiku Zařazení RIV J - Článek v odborném periodiku Poddruh J Článek ve WOS Název On Hurst exponent estimation under heavy-tailed distributions Tvůrce(i) Baruník, Jozef (UTIA-B) RID, ORCID
Krištoufek, Ladislav (UTIA-B) RID, ORCIDZdroj.dok. Physica. A : Statistical Mechanics and its Applications. - : Elsevier - ISSN 0378-4371
Roč. 389, č. 18 (2010), s. 3844-3855Poč.str. 20 s. Forma vydání www - www Jazyk dok. eng - angličtina Země vyd. NL - Nizozemsko Klíč. slova high frequency data analysis ; heavy tails ; Hurst exponent Vědní obor RIV AH - Ekonomie CEP GA402/09/0965 GA ČR - Grantová agentura ČR CEZ AV0Z10750506 - UTIA-B (2005-2011) UT WOS 000280385600015 EID SCOPUS 77955303263 DOI 10.1016/j.physa.2010.05.025 Anotace In this paper, we show how the sampling properties of Hurst exponent methods of estimation change with the presence of heavy tails. We run extensive Monte Carlo simulations to find out how rescaled range anal- ysis (R/S), multifractal detrended fluctuation analysis (MF − DFA), detrending moving average (DMA) and generalized Hurst exponent ap- proach (GHE) estimate Hurst exponent on independent series with dif- ferent heavy tails. For this purpose, we generate independent random series from stable distribution with stability exponent α changing from 1.1 (heaviest tails) to 2 (Gaussian normal distribution) and we estimate Hurst exponent using the different methods. R/S and GHE prove to be robust to heavy tails in the underlying process. GHE provides the low- est variance and bias in comparison to the other methods regardless the presence of heavy tails in data and sample size. Pracoviště Ústav teorie informace a automatizace Kontakt Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Rok sběru 2011
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