Abstract.
We develop a stochastic process with two coupled variables where the absolute values of each variable exhibit long-range power-law autocorrelations and are also long-range cross-correlated. We investigate how the scaling exponents characterizing power-law autocorrelation and long-range cross-correlation behavior in the absolute values of the generated variables depend on the two parameters in our model. In particular, if the autocorrelation is stronger, the cross-correlation is also stronger. We test the utility of our approach by comparing the autocorrelation and cross-correlation properties of the time series generated by our model with data on daily returns over ten years for two major financial indices, the Dow Jones and the S&P500, and on daily returns of two well-known company stocks, IBM and Microsoft, over five years.
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Podobnik, B., Fu, D., Stanley, H. et al. Power-law autocorrelated stochastic processes with long-range cross-correlations. Eur. Phys. J. B 56, 47–52 (2007). https://doi.org/10.1140/epjb/e2007-00089-3
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DOI: https://doi.org/10.1140/epjb/e2007-00089-3