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arXiv · 1708.06586

Dynamic correlations at different time-scales with Empirical Mode Decomposition

Noemi Nava·T. Di Matteo·Tomaso Aste
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Abstract

The Empirical Mode Decomposition (EMD) provides a tool to characterize time series in terms of its implicit components oscillating at different time-scales. We apply this decomposition to intraday time series of the following three financial indices: the S\&P 500 (USA), the IPC (Mexico) and the VIX (volatility index USA), obtaining time-varying multidimensional cross-correlations at different time-scales. The correlations computed over a rolling window are compared across the three indices, across the components at different time-scales, at different lags and over time. We uncover a rich heterogeneity of interactions which depends on the time-scale and has important led-lag relations which can have practical use for portfolio management, risk estimation and investments.

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Noemi Nava, T. Di Matteo, Tomaso Aste. 2017-08-22. Dynamic correlations at different time-scales with Empirical Mode Decomposition. https://doi.org/10.1016/j.physa.2018.02.108

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