2014/09/30 by Ladislav Kristoufek, Ladislav Krištoufek · 18 citations
Economics, Econometrics and Finance · Mathematics · Physics and Astronomy · Psychology · #Bivariate analysis #Cognition #Complex Systems and Time Series Analysis #Econometrics #Exponent #Focus (optics) #Hurst exponent #Mathematics #Physics #Power law #Psychology #Short-term memory #Statistical Mechanics and Entropy #Statistical physics #Statistics #Term (time) #Theoretical and Computational Physics #physics.data-an #q-fin.ST #stat.ME
paper · pdf · doi:10.1016/j.physa.2014.11.040
published in Physica A Statistical Mechanics and its Applications 421, 218-222 (Elsevier BV) · 6 pages
openalex publication_date 2014/11/25 · arxiv created 2014/12/04 · arxiv updated 2014/12/11 · openalex created_date 2016/06/24 · openalex updated_date 2026/08/05
We focus on emergence of the power-law cross-correlations from processes with both short and long term memory properties. In the case of correlated error-terms, the power-law decay of the cross-correlation function comes automatically with the characteristics of separate processes. Bivariate Hurst exponent is then equal to an average of separate Hurst exponents of the analyzed processes. Strength of short term memory has no effect on these asymptotic properties. Implications of these findings for the power-law cross-correlations concept are further discussed.