When dealing with market activity, different frequency of observation may reveal relevant information of interest to model financial time series. We embed a MIDAS (MI(xed)–DA(ta) Sampling) component in a multiplicative error model (MEM) context (MEM–MIDAS). The proposed specification considers a low frequency component, say monthly, in the conditional expectation of a daily nonnegative process. The empirical application illustrates the performance of the MEM– MIDAS model on the realized volatility of the NASDAQ index, statistically outperforming the standard MEM model and other popular specifications.
On the Use of Mixed Sampling in Modelling Realized Volatility: The MEM–MIDAS
Alessandra Amendola;Vincenzo Candila;
2021-01-01
Abstract
When dealing with market activity, different frequency of observation may reveal relevant information of interest to model financial time series. We embed a MIDAS (MI(xed)–DA(ta) Sampling) component in a multiplicative error model (MEM) context (MEM–MIDAS). The proposed specification considers a low frequency component, say monthly, in the conditional expectation of a daily nonnegative process. The empirical application illustrates the performance of the MEM– MIDAS model on the realized volatility of the NASDAQ index, statistically outperforming the standard MEM model and other popular specifications.File in questo prodotto:
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