Coupling high-frequency data with nonlinear models in multiple-step-ahead forecasting of energy markets' volatility

Jozef Baruník and Tomas Krehlik

No 2014/30, Working Papers IES from Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies

Abstract: In the past decade, the popularity of realized measures and various linear models for volatility forecasting has attracted attention in the literature on the price variability of energy markets. However, results that would guide practitioners to a speci c estimator and model when aiming for the best forecasting accuracy are missing. This paper contributes to the ongoing debate with a comprehensive evaluation of multiple-step-ahead volatility forecasts of energy markets using several popular high-frequency measures and forecasting models. To capture the complex patterns hidden to linear models commonly used to forecast realized volatility, this paper also contributes to the literature by coupling realized measures with arti cial neural networks as a forecasting tool. Forecasting performance is compared across models as well as realized measures of crude oil, heating oil, and natural gas volatility during three qualitatively distinct periods covering the precrisis period, recent global turmoil of markets in 2008, and the most recent post-crisis period. We conclude that coupling realized measures with arti cial neural networks results in both statistical and economic gains, reducing the tendency to over-predict volatility uniformly during all tested periods. Our analysis favors the median realized volatility, as it delivers the best performance and is a computationally simple alternative for practitioners.

Keywords: artificial neural networks; realized volatility; multiple-step-ahead forecasts; energy markets (search for similar items in EconPapers)
JEL-codes: C14 C53 G17 (search for similar items in EconPapers)
Pages: 38pages
Date: 2014-09, Revised 2014-09
New Economics Papers: this item is included in nep-cmp, nep-ene, nep-ets and nep-for
References: Add references at CitEc
Citations: View citations in EconPapers (2)

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