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
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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Working Paper: Multiple Days Ahead Realized Volatility Forecasting: Single, Combined and Average Forecasts (2018)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:glofin:v:36:y:2018:i:c:p:41-61

DOI: 10.1016/j.gfj.2017.12.002

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