A Simple Model Correction for Modelling and Forecasting (Un)Reliable Realized Volatility

37 Pages Posted: 1 Aug 2020

See all articles by Rodrigo Hizmeri

Rodrigo Hizmeri

Lancaster University

Marwan Izzeldin

Lancaster University Management School

Mike Tsionas

Lancaster University

Date Written: June 24, 2020

Abstract

We propose a dilution bias correction approach to deal with the errors-in-variables problem observed in realized volatility (RV) measures. The absolute difference between daily and monthly RV is shown to be proportional to the relative magnitude of the measurement error. Therefore, in implementing the latter metric, and in allowing the daily auto-regressive parameter to vary as a function of the error term, the result is more responsive forecasts with greater persistence (faster mean-reversion) when the measurement error is low (high). Empirical results indicate that our models outperform some of the most popular HAR and GARCH models across various forecasting horizons.

Keywords: Realized Volatility, Forecasting, Measurement Error, HAR, GARCH, HARQ, DBC-HAR

JEL Classification: C14, C22, C53, C58

Suggested Citation

Hizmeri, Rodrigo and Izzeldin, Marwan and Tsionas, Efthymios G., A Simple Model Correction for Modelling and Forecasting (Un)Reliable Realized Volatility (June 24, 2020). Available at SSRN: https://ssrn.com/abstract=3639116 or http://dx.doi.org/10.2139/ssrn.3639116

Rodrigo Hizmeri (Contact Author)

Lancaster University ( email )

Economics Department,
LUMS,
Bailrigg Lancaster, LA1 4YX
United Kingdom

Marwan Izzeldin

Lancaster University Management School ( email )

Lancaster, LA1 4YX
United Kingdom
01524 594674 (Phone)

HOME PAGE: http://www.lums.lancs.ac.uk/profiles/marwan-izzeldin/

Efthymios G. Tsionas

Lancaster University ( email )

Lancaster LA1 4YX
United Kingdom

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