This paper deals with the detection of outliers in multivariate time series models. The different detection methods found in the literature are reviewed and a new one is suggested. It is based on the coefficient of vector autocorrelation. We obtain its influence function which is used in a heuristic for detecting outliers. Then the distribution of the influence function is obtained and used for testing the hypothesis of presence of outliers.