A Time-varying Mixture Memory Multiplicative Error Model
Giovanni De Luca, Giampiero M. Gallo

Abstract
The dynamics of financial volatility shows a behavior characterized by alternating periods of turbulence and relative quiet. We suggest modelling it as a mixture memory model where time-varying mixing weights are a function of some forcing variable capable of sudden changes. In choosing a mixture approach we rely on previous evidence on the presence of a short– and a long–memory component in the observed series. We apply our model to the main Spanish stock index (IBEX) using the spread between the sovereign national and German bond rates as the forcing variable. The results show a good performance in sample, pointing to the fact that fixed weights may be a limitation to an accurate description of volatility behavior.

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