Ricerc@Sapienza

We extend the GARCH–MIDAS model to take into account possible different impacts from positive and negative macroeconomic variations on financial market volatility: a Monte Carlo simulation which shows good properties of the estimator with realistic sample sizes. The empirical application is performed on the daily S&P500 volatility dynamics with the U.S. monthly industrial production and national activity index as additional (signed) determinants. We estimate the Relative Marginal Effect of macro variable movements on volatility at different lags.

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

Il presente lavoro illustra una estensione del modello Double Asymmetric
GARCH–MIDAS (DAGM), recentemente proposto. Nella modellizazione, oltre agli
effetti asimmetrici nelle componenti di lungo e di breve periodo, `e stata introdotta
una misura di volatilit`a realizzata giornaliera come variabile addizionale per la
componente di breve periodo (la cosiddetta parte “–X”). Inoltre, `e stata sviluppata
una procedura per le previsioni multi-step-ahead, valida per tutti i modelli GARCH–