Exploiting dependence: Day-ahead volatility forecasting for crude oil and natural gas exchange-traded funds

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14560%2F18%3A00101156" target="_blank" >RIV/00216224:14560/18:00101156 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1016/j.energy.2018.04.194" target="_blank" >http://dx.doi.org/10.1016/j.energy.2018.04.194</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.energy.2018.04.194" target="_blank" >10.1016/j.energy.2018.04.194</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Exploiting dependence: Day-ahead volatility forecasting for crude oil and natural gas exchange-traded funds

Popis výsledku v původním jazyce

This paper investigates volatility forecasting for crude oil and natural gas. The main objective of our research is to determine whether the heterogeneous autoregressive (HAR) model of Corsi (2009) can be outperformed by harnessing information from a related energy commodity. We find that on average, information from related commodity does not improve volatility forecasts, whether we consider a multivariate model, or various univariate models that include this information. However, superior volatility forecasts are produced by combining forecasts from various models. As a result, information from the related commodity can be still useful, because it allows us to construct wider range of possible models, and averaging across various models improves forecasts. Therefore, for somebody interested in precise volatility forecasts of crude oil or natural gas, we recommend to focus on model averaging instead of just including information from related commodity in a single forecast model.

Název v anglickém jazyce

Exploiting dependence: Day-ahead volatility forecasting for crude oil and natural gas exchange-traded funds

Popis výsledku anglicky

This paper investigates volatility forecasting for crude oil and natural gas. The main objective of our research is to determine whether the heterogeneous autoregressive (HAR) model of Corsi (2009) can be outperformed by harnessing information from a related energy commodity. We find that on average, information from related commodity does not improve volatility forecasts, whether we consider a multivariate model, or various univariate models that include this information. However, superior volatility forecasts are produced by combining forecasts from various models. As a result, information from the related commodity can be still useful, because it allows us to construct wider range of possible models, and averaging across various models improves forecasts. Therefore, for somebody interested in precise volatility forecasts of crude oil or natural gas, we recommend to focus on model averaging instead of just including information from related commodity in a single forecast model.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

50206 - Finance

Projekt

<a href="/cs/project/GA18-05829S" target="_blank" >GA18-05829S: Predikce volatility na rozvijících se finančních trzích</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2018

Kód důvěrnosti údajů

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

Název periodika

Energy

ISSN

0360-5442

e-ISSN

—

Svazek periodika

155

Číslo periodika v rámci svazku

15 July

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

12

Strana od-do

462-473

Kód UT WoS článku

000445303100040

EID výsledku v databázi Scopus

2-s2.0-85048194675