The Use of Scaling Properties to Detect Relevant Changes in Financial Time
Highlights The use of scaling properties to detect relevant changes in financial time series: a new visual warning tool Ioannis P. Antoniades 2, Giuseppe Brandi, L. G. Magafas, T. Di Matteo • Visual warning tool for financial time series based on scaling analysis • Application of time-dependent Generalized Hurst Exponent method to financial timeseries arXiv:2010.08890v4 [q-fin.ST] 9 Dec 2020 2020.This manuscript version is made available under the CC-BY-NC-ND 4.0 license The use of scaling properties to detect relevant changes in financial time series: a new visual warning tool Ioannis P. Antoniades 1a,e, Giuseppe Brandib, L. G. Magafasd, T. Di Matteob,c aAristotle University of Thessaloniki, Physics Department, Thessaloniki, bDepartment of Mathematics, King’s College London, The Strand, London, WC2R 2LS, UK cComplexity Science Hub Vienna, Josefstaedter Strasse 39, A 1080 Vienna, Austria dInternational Hellenic University, Physics Department, Complex Systems Laboratory eAmerican College of Thessaloniki, Division of Science & Technology Abstract The dynamical evolution of multiscaling in financial time series is investigated using time-dependent Generalized Hurst Exponents (GHE), Hq, for various values of the parameter q. Using Hq, we introduce a new visual methodol- ogy to algorithmically detect critical changes in the scaling of the underlying complex time-series. The methodology involves the degree of multiscaling at a particular time instance, the multiscaling trend which is calculated by the Change-Point Analysis method, and a rigorous evaluation of the statistical significance of the results. Using this algorithm, we have identified particular patterns in the temporal co-evolution of the different Hq time-series.
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