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• W2084800543 abstract "Abstract The methodologies and assumptions in financial integration studies are problematic and may lead to spurious empirical results. Using surrogate data analysis and the mutual prediction method of testing for nonlinear interdependence, it is feasible for an analyst, with a scant knowledge of the underlying dynamics of two dynamical systems, to show whether or not the systems are interdependent. This study applies these techniques in testing for nonlinear interdependence of three Chinese stock markets: Shanghai, Shenzhen, and Hong Kong. The empirical results of the present study indicate that the stock market series are nonlinear and that the Chinese stock exchanges are nonlinearly interdependent. Specifically, the evidence indicates that Shanghai and Shenzhen markets are bi-directionally interdependent, while Shanghai and Hong Kong as well as Shenzhen and Hong Kong markets are unidirectionally interdependent, with the direction of interdependence going from the mainland's markets to the Hong Kong market. Keywords: Applied mathematical financeComputational financeContagionEconophysicsEmerging stock marketsEmpirical time series analysisQuantitative financeSignal processing Acknowledgements We are grateful to Lianqyue Cao, Alexander Balanov, and the anonymous referees for their helpful comments on an earlier draft of this paper. This study was partially supported by a grant from The National Natural Science Foundation of China (70773028). Notes †We use synchronization loosely as a matter of common parlance. See section 2.2 for a list of requirements for the occurrence of synchronization. †We are grateful to Alexander Balanov for bringing the points in this paragraph to our attention. †We are grateful to Dr. Liangyue Cao for suggesting this method and also for providing his computer codes for the simultaneous calculation of d and τ. †Note that we unfolded the time series into d-dimensional space. ‡A detailed discussion of how this is done is beyond the scope of this study. Contact the corresponding author for the algorithm." @default.
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• W2084800543 date "2012-03-01" @default.
• W2084800543 modified "2023-10-07" @default.
• W2084800543 title "Nonlinear interdependence of the Chinese stock markets" @default.
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• W2084800543 doi "https://doi.org/10.1080/14697688.2010.541488" @default.
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