Return and volatility spillovers between Chinese and US clean energy related stocks

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11230%2F22%3A10447670" target="_blank" >RIV/00216208:11230/22:10447670 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/61384399:31110/22:00057781

Výsledek na webu

<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=i4z75w2Pt-" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=i4z75w2Pt-</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.eneco.2022.105911" target="_blank" >10.1016/j.eneco.2022.105911</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Return and volatility spillovers between Chinese and US clean energy related stocks

Popis výsledku v původním jazyce

This paper aims to empirically investigate the dynamic connectedness between oil prices and stock returns of clean energy-related and technology companies in China and U.S. financial markets. We apply three multivariate GARCH model specifications (CCC, DCC and ADCC) to investigate the return and volatility spillovers among price and return series. We use rolling window analysis to forecast out-of-sample one-step-ahead dynamic conditional correlations and time-varying optimal hedge ratios. Our results suggest that Invesco China Technology ETF (CQQQ) is the best asset to hedge Chinese clean energy stocks followed by WTI, ECO, and PSE. Our results are reasonably robust to the choice of different model refits and forecast length of rolling window analysis. Our empirical findings provide investors and policymakers with the systematic understanding of return and volatility connectedness between China and U.S. clean energy stock markets.

Název v anglickém jazyce

Return and volatility spillovers between Chinese and US clean energy related stocks

Popis výsledku anglicky

This paper aims to empirically investigate the dynamic connectedness between oil prices and stock returns of clean energy-related and technology companies in China and U.S. financial markets. We apply three multivariate GARCH model specifications (CCC, DCC and ADCC) to investigate the return and volatility spillovers among price and return series. We use rolling window analysis to forecast out-of-sample one-step-ahead dynamic conditional correlations and time-varying optimal hedge ratios. Our results suggest that Invesco China Technology ETF (CQQQ) is the best asset to hedge Chinese clean energy stocks followed by WTI, ECO, and PSE. Our results are reasonably robust to the choice of different model refits and forecast length of rolling window analysis. Our empirical findings provide investors and policymakers with the systematic understanding of return and volatility connectedness between China and U.S. clean energy stock markets.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

50201 - Economic Theory

Projekt

<a href="/cs/project/GX19-26812X" target="_blank" >GX19-26812X: Excelence v ekonomickém výzkumu energetické efektivity a modelování dopadů - FE3M</a><br>

Návaznosti

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

Rok uplatnění

2022

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

108

Číslo periodika v rámci svazku

April 2022

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

12

Strana od-do

105911

Kód UT WoS článku

000795562300006

EID výsledku v databázi Scopus

2-s2.0-85125677679