Detecting nonlinearity in time series: Surrogate and bootstrap approaches

Melvin J. Hinich, Eduardo M. Mendes, Lewi Stone

Research output: Contribution to journalArticlepeer-review


Detecting nonlinearity in financial time series is a key point when the main interest is to understand the generating process. One of the main tests for testing linearity in time series is the Hinich Bispectrum Nonlinearity Test (HINBIN). Although this test has been succesfully applied to a vast number of time series, further improvement in the size power of the test is possible. A new method that combines the bispectrum and the surrogate method and bootstrap is then presented for detecting nonlinearity, gaussianity and time reversibility. Simulated and real data examples are given to demonstrate the efficacy of the new tests.

Original languageEnglish
Article number3
Pages (from-to)67-81
Number of pages15
JournalStudies in Nonlinear Dynamics and Econometrics
Issue number4
StatePublished - Dec 2005
Externally publishedYes


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