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BDS: MATLAB module to calculate Brock, Dechert & Scheinkman test for independence

Author

Listed:
  • Ludwig Kanzler

Programming Language

MATLAB

Abstract

[W, SIG, C, C1, K] = BDS (SERIES, MAXDIM, DISTANCE, METHOD, MAXRAM) uses the time-series vector SERIES (1) and the dimensional distance (either defined as fraction DISTANCE of the standard deviation of SERIES if FLAG = 0, or defined such that the one dimensional correlation integral of SERIES is equal to DISTANCE if FLAG = 1) to compute BDS statistics W for each dimension between 2 and MAXDIM, significance levels SIG at which the null hypotheses of no dependence are rejected against (almost) any type of linear and non-linear dependence, correlation integral estimates C for each dimension M between 2 and MAXDIM, first-order correlation integral estimates C1 computed over the last N-M+1 observations, and parameter estimate K.

Suggested Citation

  • Ludwig Kanzler, 1998. "BDS: MATLAB module to calculate Brock, Dechert & Scheinkman test for independence," Statistical Software Components T871803, Boston College Department of Economics.
    • Handle: RePEc:boc:bocode:t871803
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    File URL: http://fmwww.bc.edu/repec/bocode/b/bds.m
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    Cited by:

    1. Eugenia Sanin, María & Violante, Francesco & Mansanet-Bataller, María, 2015. "Understanding volatility dynamics in the EU-ETS market," Energy Policy, Elsevier, vol. 82(C), pages 321-331.
    2. Swasti R. Khuntia & Jose L. Rueda & Mart A.M.M. Van der Meijden, 2018. "Long-Term Electricity Load Forecasting Considering Volatility Using Multiplicative Error Model," Energies, MDPI, vol. 11(12), pages 1-19, November.

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    Keywords

    MATLAB;

    Statistics

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