2003/12/18 by Luigi Palatella, Josep Perelló, Josep Perello +2 · 2 citations
Computer Science · Economics, Econometrics and Finance · Mathematics · Physics and Astronomy · #Arch #Autocorrelation #Complex Systems and Time Series Analysis #Computer science #Econometrics #Economics #Entropy (arrow of time) #Finance #Financial Risk and Volatility Modeling #Financial market #Geography #Mathematics #Nonlinear Dynamics and Pattern Formation #Physics #Statistical physics #Statistics #Stochastic volatility #Thermodynamics #Volatility (finance) #cond-mat.stat-mech #physics.soc-ph #q-fin.ST
paper · pdf · doi:10.1140/epjb/e2004-00161-6
published as European Physical Journal B 38 (2004) 671-677 · 15 pages, 4 figures
arxiv created 2003/12/18 · openalex publication_date 2004/04/01 · arxiv updated 2009/12/01 · openalex created_date 2022/10/01 · openalex updated_date 2026/08/05
We study the activity, i.e., the number of transactions per unit time, of financial markets. Using the diffusion entropy technique we show that the autocorrelation of the activity is caused by the presence of peaks whose time distances are distributed following an asymptotic power law which ultimately recovers the Poissonian behavior. We discuss these results in comparison with ARCH models, stochastic volatility models and multi-agent models showing that ARCH and stochastic volatility models better describe the observed experimental evidences.