What Matters When Developing Oil Price Volatility Forecasting Frameworks?

46 Pages Posted: 14 May 2020

See all articles by Panagiotis Delis

Panagiotis Delis

Panteion University of Athens - Department of Economic and Regional Development

Stavros Antonios Degiannakis

Department of Economic and Regional Development, Panteion University of Political and Social Sciences

George Filis

Bournemouth University

Date Written: May 11, 2020

Abstract

Forecasting oil price volatility is considered of major importance for numerous stakeholders, including, policy makers, industries and investors. This paper examines and evaluates the main factors that oil price volatility forecasters should take before constructing their forecasting models. Such factors are related to: i) direct vs iterated forecasts, ii) the incorporation of continuous and jump components, iii) the importance of semi variance volatility measures, and iv) OLS vs time-varying parameter (TVP) estimation procedures. Even more, we evaluate the performance of these factors for both realized and implied volatility measures, based on statistical loss functions, as well
as, their economic use. The results show that depending on whether end-users are interested in forecasting the realized or the implied volatility, the factors influencing the accuracy of forecasts are different. In particular, for the realized volatility, direct forecasting based on TVP estimation procedure, as well as, using the information obtained in the semi variance measures are capable of producing significantly superior forecasts. By contrast, separating the continuous and the jump components of the realized volatility does not provide any added value to these forecasts. Turning to the OVX, based on the economic evaluation of our forecasts, the TVP estimation procedure
seems to performbetter. In addition, we find evidence that the continuous component and the semi variance measures of the realized volatility also yield better OVX forecasts in the longer run horizons.

Keywords: HAR model, realized volatility, Oil price implied volatility index, multi-step ahead forecasts, time-varying parameter model

Suggested Citation

Delis, Panagiotis and Degiannakis, Stavros Antonios and Filis, George, What Matters When Developing Oil Price Volatility Forecasting Frameworks? (May 11, 2020). USAEE Working Paper No. 20-446, Available at SSRN: https://ssrn.com/abstract=3598567 or http://dx.doi.org/10.2139/ssrn.3598567

Panagiotis Delis (Contact Author)

Panteion University of Athens - Department of Economic and Regional Development ( email )

136, Sygrou Avenue
176 71 Athens
Greece

Stavros Antonios Degiannakis

Department of Economic and Regional Development, Panteion University of Political and Social Sciences ( email )

136 Sygrou
Athens
Greece

George Filis

Bournemouth University ( email )

Fern Barrow
Poole BH12 5BB, Dorset BH8 8EB
United Kingdom

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