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Realized variance modeling: decoupling forecasting from estimation

Fabrizio Cipollini (), Giampiero Gallo () and Alessandro Palandri ()
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Fabrizio Cipollini: Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", Università di Firenze, https://www.disia.unifi.it
Alessandro Palandri: Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", Università di Firenze, https://www.disia.unifi.it

No 2019_05, Econometrics Working Papers Archive from Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti"

Abstract: In this paper we evaluate the in-sample fit and out-of-sample forecasts of various combinations of realized variance models and estimation criteria . Our empirical findings highlight that: independently of the econometrician’s forecasting loss function, certain estimation criteria perform significantly better than others; the simple ARMA modeling of the log realized variance generates superior forecasts than the HAR family, for any of the forecasting loss functions considered; the (2,1) parameterizations with negative lag-2 coefficient emerge as the benchmark specifications generating the best forecasts and approximating long-run dependence as well as the HAR family.

Keywords: Variance modeling; Variance forecasting; Heterogeneous Autoregressive (HAR) model; Multiplicative Error Model (MEM); Realized variance space (search for similar items in EconPapers)
JEL-codes: C32 C53 C58 G17 (search for similar items in EconPapers)
Pages: 33 pages
Date: 2019-07
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-for and nep-ore
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