Realized Variance Modeling: Decoupling Forecasting from Estimation*

Fabrizio Cipollini, Giampiero Gallo () and Alessandro Palandri

Journal of Financial Econometrics, vol. 18, issue 3, 532-555

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

Keywords: forecast evaluation; Heterogeneous Autoregressive (HAR) model; realized variance; variance forecasting; variance modeling (search for similar items in EconPapers)
JEL-codes: C22 C52 C53 C58 G17 (search for similar items in EconPapers)
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Related works:
Journal Article: Realized Variance Modeling: Decoupling Forecasting from Estimation* (2020)
Working Paper: Realized variance modeling: decoupling forecasting from estimation (2019)
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