0533622 20240903190026.720201028235959.9 85092929530 000585454200001 10.3390/math8101767 13 s. E cav_un_epca*04536012227-73908MDPI multifractality tail dependence serial correlation copulas cav_un_auth*0294289 Avdulaj Krenar UTIA-B Ekonometrie Department of Econometrics E E Department of Econometrics CZ 50 Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0256902 Krištoufek Ladislav UTIA-B Ekonometrie Department of Econometrics E E Department of Econometrics CZ 50 K Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2020/E/kristoufek-0533622.pdf https://www.mdpi.com/2227-7390/8/10/1767 GJ17-12386Y GA ČR CZ cav_un_auth*0351447 We study whether, and if yes then how, a varying auto-correlation structure in different parts of distributions is reflected in the multifractal properties of a dynamic process. Utilizing the quantile autoregressive process with Gaussian copula using three popular estimators of the generalized Hurst exponent, our Monte Carlo simulation study shows that such dynamics translate into multifractal dynamics of the generated series. The tail-dependence of the auto-correlations forms strong enough non-linear dependencies to be reflected in the estimated multifractal spectra and separated from the case of the standard auto-regressive process. With a quick empirical example from financial markets, we argue that the interaction is more important for the asymmetric tail dependence. In addition, we discuss and explain the often reported paradox of higher multifractality of shuffled series compared to the original financial series. In short, the quantile-dependent auto-correlation structures qualify as sources of multifractality and they are worth further theoretical examination. WOS AH 50000 50200 50201 2021 2 RVO:67985556 http://hdl.handle.net/11104/0312007 1 S 1767 3+4 Article Mathematics A MATHEMATICS 2.165 0.691 1.4 0.00646 0.354 5424 84 0.495 37.01 2.83 4619 Q2 1.835 2247 Q1 17.45 92.9 Q4 Q2 2.1 Q1 92.879 2020 85092929530 SCOPUS PUBMED 000585454200001 WOS cav_un_epca*0453601 Mathematics 2227-7390 2227-7390 Roč. 8 č. 10 2020 MDPI ONLINE