2014/08/31 by Ladislav Kristoufek, Ladislav Krištoufek
Economics, Econometrics and Finance · Mathematics · Physics and Astronomy · #Applied mathematics #Bandwidth (computing) #Bivariate analysis #Complement (music) #Complex Systems and Time Series Analysis #Computer science #Econometrics #Economics #Estimator #Exponent #Financial Risk and Volatility Modeling #Frequency domain #Hurst exponent #Mathematical analysis #Mathematics #Multivariate statistics #Periodogram #Spectral density #Statistics #Univariate #Variance (accounting) #physics.data-an #q-fin.ST
paper · pdf · doi:10.1103/physreve.90.062802
published as Physical Review E 90, 062802 (2014) · 15 pages, 4 figures
arxiv created 2014/11/21 · openalex publication_date 2014/12/02 · arxiv updated 2014/12/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
We discuss two alternate spectrum-based estimators of the bivariate Hurst exponent in the power-law cross-correlations setting, the cross-periodogram and local X-Whittle estimators, as generalizations of their univariate counterparts. As the spectrum-based estimators are dependent on a part of the spectrum taken into consideration during estimation, a simulation study showing performance of the estimators under varying bandwidth parameter as well as correlation between processes and their specification is provided as well. These estimators are less biased than the already existent averaged periodogram estimator, which, however, has slightly lower variance. The spectrum-based estimators can serve as a good complement to the popular time domain estimators.