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- W2280474718 endingPage "2016" @default.
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- W2280474718 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." @default.
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- W2280474718 date "2016-10-01" @default.
- W2280474718 modified "2023-10-18" @default.
- W2280474718 title "Time-dependent scaling patterns in high frequency financial data" @default.
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- W2280474718 doi "https://doi.org/10.1140/epjst/e2015-50328-y" @default.
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