Volume 138, Number 6, June 2022
|Number of page(s)||7|
|Section||Statistical physics and networks|
|Published online||28 June 2022|
Structure of cross-correlation between stock and oil markets
Business School, University of Shanghai for Science and Technology - Shanghai, 200093, China
(a) email@example.com (corresponding author)
Received: 17 August 2021
Accepted: 19 October 2021
We displayed in this paper the structure of cross-correlation between the S&P 500 stock market and the Brent Oil market and its evolutionary behavior. Technically, the ensemble empirical mode decomposition is adopted to separate the two series into components. Let a window slide along the multi-variate series of the components, generating a series of segments. For each segment, one calculates the mutual entropies between the components to describe the coupling strengths, resulting into a network between/within the two markets. The networks corresponding to the successive segments form a temporal network. It is found that the characteristic period of intrinsic mode for each series grows exponentially from several days to more than ten years. The couplings between long-term components (with periods larger than one year) form the stable backbone of the network. The shocks of short-term events on the long-term components determine mainly the evolutionary behavior, especially the changes of the coupling structure. This method can be extended straightforwardly to display the cross-correlation structures and their evolutions for complex systems composed of multi-subsystems.
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