In order to describe the co-movements in both conditional mean and conditional variance of high dimensional non-stationary time series by dimension reduction, we introduce the conditional heteroscedasticity with factor structure to the error correction model (ECM). The new model is called the...

The class of generalized autoregressive conditional heteroscedastic (GARCH) models has proved particularly valuable in modelling time series with time varying volatility. These include financial data, which can be particularly heavy tailed. It is well understood now that the tail heaviness of...