Počet záznamů: 1
Combining high frequency data with non-linear models for forecasting energy market volatility
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SYSNO ASEP 0456185 Druh ASEP J - Článek v odborném periodiku Zařazení RIV J - Článek v odborném periodiku Poddruh J Článek ve WOS Název Combining high frequency data with non-linear models for forecasting energy market volatility Tvůrce(i) Baruník, Jozef (UTIA-B) RID, ORCID
Křehlík, Tomáš (UTIA-B)Celkový počet autorů 2 Zdroj.dok. Expert Systems With Applications. - : Elsevier - ISSN 0957-4174
Roč. 55, č. 1 (2016), s. 222-242Poč.str. 36 s. Forma vydání Tištěná - P Jazyk dok. eng - angličtina Země vyd. NL - Nizozemsko Klíč. slova artificial neural networks ; realized volatility ; multiple-step-ahead forecasts ; energy markets Vědní obor RIV AH - Ekonomie CEP GBP402/12/G097 GA ČR - Grantová agentura ČR Institucionální podpora UTIA-B - RVO:67985556 UT WOS 000374811000017 EID SCOPUS 84960075958 DOI 10.1016/j.eswa.2016.02.008 Anotace The popularity of realized measures and various linear models for volatility forecasting has been the focus of attention in the literature addressing energy markets' price variability over the past decade. However, there are no studies to help practitioners achieve optimal forecasting accuracy by guiding them to a specific estimator and model. This paper contributes to this literature in two ways. First, to capture the complex patterns hidden in linear models commonly used to forecast realized volatility, we propose a novel framework that couples realized measures with generalized regression based on artificial neural networks. Our second contribution is to comprehensively evaluate multiple-step-ahead volatility forecasts of energy markets using several popular high frequency measures and forecasting models. We compare forecasting performance across models and across realized measures of crude oil, heating oil, and natural gas volatility during three qualitatively distinct periods: the pre-crisis period, the 2008 global financial crisis, and the post-crisis period. Pracoviště Ústav teorie informace a automatizace Kontakt Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Rok sběru 2017
Počet záznamů: 1