| Content | The Markov property is a fundamental property in time series analysis and is often assumed in economic and
nancial modelling. We develop a new test for the Markov property using the conditional characteristic function embedded in a frequency domain approach, which checks the implication of the Markov property in every conditional moment (if exists) and over many lags. The proposed test is applicable to both univariate and multivariate time series with discrete or continuous distributions. Simulation studies show that with the use of a smoothed nonparametric transition density-based bootstrap procedure, the proposed test has reasonable sizes and all-around power against several popular non-Markov alternatives in
nite samples. We apply the test to a number of
nancial time series and
nd some evidence against the Markov property. |
