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Multiple days ahead realized volatility forecasting: Single, combined and average forecasts

Stavros Degiannakis ()

Global Finance Journal, 2018, vol. 36, issue C, 41-61

Abstract: The task of this paper is the enhancement of realized volatility forecasts. We investigate whether a mixture of predictions (either the combination or the averaging of forecasts) can provide more accurate volatility forecasts than the forecasts of a single model. We estimate long-memory and heterogeneous autoregressive models under symmetric and asymmetric distributions for the major European Union stock market indices and the exchange rates of the Euro.

Keywords: Averaging forecasts; Combining forecasts; Heterogeneous autoregressive; Intra-day data; Long memory; Model confidence set; Predictive ability; Realized volatility; Ultra-high frequency (search for similar items in EconPapers)
JEL-codes: C14 C32 C50 G11 G15 (search for similar items in EconPapers)
Date: 2018
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Handle: RePEc:eee:glofin:v:36:y:2018:i:c:p:41-61