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- W3033862437 abstract "We suggest the Doubly Multiplicative Error class of models (DMEM) for modeling and forecasting realized volatility, which combines two components accommodating low-, respectively, high-frequency features in the data. We derive the theoretical properties of the Maximum Likelihood and Generalized Method of Moments estimators. Two such models are then proposed, the Component-MEM, which uses daily data for both components, and the MEM-MIDAS, which exploits the logic of MIxed-DAta Sampling (MIDAS). The empirical application involves the S&P 500, NASDAQ, FTSE 100 and Hang Seng indices: irrespective of the market, both DMEM's outperform the HAR and other relevant GARCH-type models." @default.
- W3033862437 created "2020-06-12" @default.
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- W3033862437 date "2020-06-05" @default.
- W3033862437 modified "2023-09-27" @default.
- W3033862437 title "Doubly Multiplicative Error Models with Long- and Short-run Components" @default.
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