Dette, HolgerWieczorek, Gabriele2007-12-042007-12-042007-12-04http://hdl.handle.net/2003/2490310.17877/DE290R-15933In this paper we propose a new test for the hypothesis of a constant coefficient of variation in the common nonparametric regression model. The test is based on an estimate of the L2- distance between the square of the regression function and variance function. We prove asymptotic normality of a standardized estimate of this distance under the null hypothesis and fixed alternatives and the finite sample properties of a corresponding bootstrap test are investigated by means of a simulation study. The results are applicable to stationary processes with the common mixing conditions and are used to construct tests for ARCH assumptions in financial time series.enConstant cofficient of variationGeneralized nonparametric regression modelsMultiplicative error structureNonparametric regressionStationary processes004report