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Time-dependent scaling patterns in high frequency financial data

Nava, N; Matteo, TD; Aste, T; (2016) Time-dependent scaling patterns in high frequency financial data. European Physical Journal: Special Topics , 225 (10) pp. 1997-2016. 10.1140/epjst/e2015-50328-y. Green open access

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Abstract

We measure the influence of different time-scales on the dynamics of financial market data. This is obtained by decomposing financial time series into simple oscillations associated with distinct time-scales. We propose two new time-varying measures: 1) an amplitude scaling exponent and 2) an entropy-like measure. We apply these measures to intraday, 30-second sampled prices of various stock indices. Our results reveal intraday trends where different time-horizons contribute with variable relative amplitudes over the course of the trading day. Our findings indicate that the time series we analysed have a non-stationary multifractal nature with predominantly persistent behaviour at the middle of the trading session and anti-persistent behaviour at the open and close. We demonstrate that these deviations are statistically significant and robust.

Type: Article
Title: Time-dependent scaling patterns in high frequency financial data
Open access status: An open access version is available from UCL Discovery
DOI: 10.1140/epjst/e2015-50328-y
Publisher version: http://dx.doi.org/10.1140/epjst/e2015-50328-y
Language: English
Additional information: © The Author(s) 2016. Open Access. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Keywords: q-fin.ST, q-fin.ST
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery-pp.ucl.ac.uk/id/eprint/1516110
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