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In this study, we design a monitoring method for the vector autoregressive (VAR) and structural VAR (SVAR) time series using the residual-based cumulative sum (CUSUM) control chart. The residuals are calculated with a sequentially observed testing sample and the parameter estimates obtained from a training sample. Control limits are determined asymptotically when type 1 error probability scheme is used, but average run length (ARL) is also used in our empirical study. For the SVAR time series, independent component analysis (ICA) method is applied. A simulation study and real data analysis are conducted to evaluate our method.

Statistical process monitoring for vector autoregressive time series based on location-scale CUSUM method