Predicting the volatility of major energy commodity prices: the dynamic persistence model

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F24%3A00600509" target="_blank" >RIV/67985556:_____/24:00600509 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216208:11230/24:10491801

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S014098832400690X?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S014098832400690X?via%3Dihub</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.eneco.2024.107982" target="_blank" >10.1016/j.eneco.2024.107982</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Predicting the volatility of major energy commodity prices: the dynamic persistence model

Popis výsledku v původním jazyce

Time variation and persistence are crucial properties of volatility that are often studied separately in energy volatility forecasting models. Here, we propose a novel approach that allows shocks with heterogeneous persistence to vary smoothly over time, and thus model the two together. We argue that this is important because such dynamics arise naturally from the dynamic nature of shocks in energy commodities. We identify such dynamics from the data using localised regressions and build a model that significantly improves volatility forecasts. Such forecasting models, based on a rich persistence structure that varies smoothly over time, outperform state-of-the-art benchmark models and are particularly useful for forecasting over longer horizons.

Název v anglickém jazyce

Predicting the volatility of major energy commodity prices: the dynamic persistence model

Popis výsledku anglicky

Time variation and persistence are crucial properties of volatility that are often studied separately in energy volatility forecasting models. Here, we propose a novel approach that allows shocks with heterogeneous persistence to vary smoothly over time, and thus model the two together. We argue that this is important because such dynamics arise naturally from the dynamic nature of shocks in energy commodities. We identify such dynamics from the data using localised regressions and build a model that significantly improves volatility forecasts. Such forecasting models, based on a rich persistence structure that varies smoothly over time, outperform state-of-the-art benchmark models and are particularly useful for forecasting over longer horizons.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

50202 - Applied Economics, Econometrics

Projekt

<a href="/cs/project/GX19-28231X" target="_blank" >GX19-28231X: Dynamické modely pro digitální finance</a><br>

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Energy Economics

ISSN

0140-9883

e-ISSN

1873-6181

Svazek periodika

140

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

7

Strana od-do

107982

Kód UT WoS článku

001355240700001

EID výsledku v databázi Scopus

2-s2.0-85208215688