Abstract
We develop testing procedures which detect if the observed time series is a martingale difference sequence. Furthermore, tests are developed that detect change-points in the conditional expectation of the series given its past.
The test statistics are formulated following the approach of Fourier-type conditional expectations first proposed by Bierens(1982) and have the advantage of computational simplicity. The limit behavior of the test statistics is investigated under the null hypothesis as well as under alternatives.
Since the asymptotic null distribution contains unknown parameters, a bootstrap procedure is proposed in order to actually perform the test. The performance of the bootstrap version of the test is compared in finite samples with other methods for the same problem.
A real-data application is also included.