Choosing The Frequency Of Volatility Components Within The Double Asymmetric Garch-Midas-X Model

The Double Asymmetric GARCH-MIDAS (DAGM) model has the advantage of modelling volatility as the product of two components: a slow-moving term involving variables sampled at lower frequencies and a short-run part, each with an asymmetric behavior in volatility dynamics. Such a model is extended in three directions: first, by including a market volatility index as a daily lagged variable in the short-run component (the so-called "-X" term); second, by adding the same variable in the long-run component as variations of data aggregated at any desired frequency; third, by proposing a data-driven method to find the optimal number of lags to be included in the positive and negative parts of the long-run component. The resulting model, labelled as DAGM-X-2K, is extensively evaluated under several alternative configurations, producing satisfactory evidence when applied to the S&P 500 and NASDAQ indices. The out-of-sample results show that the "-X" addition significantly improves the performance, making the proposed DAGM-X-2K model enter the Model Confidence Set, even for large forecasting horizons (for 1 to 60 days). Published by Elsevier B.V. on behalf of EcoSta Econometrics and Statistics.