{"title":"Dynamic connectedness in the higher moments between clean energy and oil prices","authors":"Wei Hao , Linh Pham","doi":"10.1016/j.eneco.2024.107987","DOIUrl":null,"url":null,"abstract":"<div><div>Focusing on clean energy stocks and oil prices, we find that connectedness between these assets not only exists in volatility, but also at higher-order moments, such as skewness and kurtosis, which have been largely under studied in the existing literature. Estimating the connectedness using intra-day data, our initial static analyses suggest that the connectedness between the clean energy and oil markets is heterogenous across the moments and the shock transmitter/recipient role played by each market varies across moments. Further dynamic analyses indicate that higher-order moment connectedness is also time varying and appears to be stronger during uncertain market conditions. In addition, we identify day-of-the-week patterns of higher-order moment connectedness during high uncertainty periods, but these patterns appear to be reversed during low uncertainty periods. The employment of Markov switching regression models further corroborates the market uncertainties as the determinants of higher-order moment connectedness. As an important extension, we provide empirical evidence that including clean energy stocks in the investment portfolio can effectively hedge oil price risks and considering higher-order moments in constructing investment strategies adds extra value to investors. Our utility-based hedging strategy and minimum connectedness portfolio can offer higher utility gains and better risk-return trade-offs to those investors who are not infinitely risk-averse.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"140 ","pages":"Article 107987"},"PeriodicalIF":13.6000,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy Economics","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0140988324006959","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
Abstract
Focusing on clean energy stocks and oil prices, we find that connectedness between these assets not only exists in volatility, but also at higher-order moments, such as skewness and kurtosis, which have been largely under studied in the existing literature. Estimating the connectedness using intra-day data, our initial static analyses suggest that the connectedness between the clean energy and oil markets is heterogenous across the moments and the shock transmitter/recipient role played by each market varies across moments. Further dynamic analyses indicate that higher-order moment connectedness is also time varying and appears to be stronger during uncertain market conditions. In addition, we identify day-of-the-week patterns of higher-order moment connectedness during high uncertainty periods, but these patterns appear to be reversed during low uncertainty periods. The employment of Markov switching regression models further corroborates the market uncertainties as the determinants of higher-order moment connectedness. As an important extension, we provide empirical evidence that including clean energy stocks in the investment portfolio can effectively hedge oil price risks and considering higher-order moments in constructing investment strategies adds extra value to investors. Our utility-based hedging strategy and minimum connectedness portfolio can offer higher utility gains and better risk-return trade-offs to those investors who are not infinitely risk-averse.
期刊介绍:
Energy Economics is a field journal that focuses on energy economics and energy finance. It covers various themes including the exploitation, conversion, and use of energy, markets for energy commodities and derivatives, regulation and taxation, forecasting, environment and climate, international trade, development, and monetary policy. The journal welcomes contributions that utilize diverse methods such as experiments, surveys, econometrics, decomposition, simulation models, equilibrium models, optimization models, and analytical models. It publishes a combination of papers employing different methods to explore a wide range of topics. The journal's replication policy encourages the submission of replication studies, wherein researchers reproduce and extend the key results of original studies while explaining any differences. Energy Economics is indexed and abstracted in several databases including Environmental Abstracts, Fuel and Energy Abstracts, Social Sciences Citation Index, GEOBASE, Social & Behavioral Sciences, Journal of Economic Literature, INSPEC, and more.