{"title":"Higher moments interaction between the US treasury yields, energy assets, and green cryptos: Dynamic analysis with portfolio implications","authors":"Najaf Iqbal , Zaghum Umar , Zhang Shaoyong , Tatiana Sokolova","doi":"10.1016/j.eneco.2024.108077","DOIUrl":null,"url":null,"abstract":"<div><div>We examine how the US treasury yields are connected with traditional energy and green cryptocurrencies in higher moments. For this purpose, we first compute the US treasury yield curve's Level, Slope, and Curvature based on different maturities from October 2017 to December 2023 and then apply the TVP-VAR model on return, volatility, Skewness, and Kurtosis measures. We find that returns are the most connected compared with the higher moments. The dynamic connectedness represents distinct spikes in each moment's case, sharing patterns during the 2017 crypto rally, the COVID-19 outburst in 2020, and the Russia-Ukraine war eruption in 2022. Despite being the leading shock transmitters, green cryptocurrencies share weak connections in the higher moments, making them suitable diversifiers in turbulent times. We also compute minimum variance, minimum connectedness, and minimum correlation portfolios and their hedging effectiveness. Green cryptos significantly reduce variance in traditional energy portfolios, which is evident from their high hedging effectiveness. The connectedness patterns support the Global Financial Cycle Hypothesis, showing integration in extreme market conditions, partly affected by the US treasury yields. We discuss the important implications of these findings for portfolio managers and policymakers.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"141 ","pages":"Article 108077"},"PeriodicalIF":13.6000,"publicationDate":"2024-11-26","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/S0140988324007862","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
We examine how the US treasury yields are connected with traditional energy and green cryptocurrencies in higher moments. For this purpose, we first compute the US treasury yield curve's Level, Slope, and Curvature based on different maturities from October 2017 to December 2023 and then apply the TVP-VAR model on return, volatility, Skewness, and Kurtosis measures. We find that returns are the most connected compared with the higher moments. The dynamic connectedness represents distinct spikes in each moment's case, sharing patterns during the 2017 crypto rally, the COVID-19 outburst in 2020, and the Russia-Ukraine war eruption in 2022. Despite being the leading shock transmitters, green cryptocurrencies share weak connections in the higher moments, making them suitable diversifiers in turbulent times. We also compute minimum variance, minimum connectedness, and minimum correlation portfolios and their hedging effectiveness. Green cryptos significantly reduce variance in traditional energy portfolios, which is evident from their high hedging effectiveness. The connectedness patterns support the Global Financial Cycle Hypothesis, showing integration in extreme market conditions, partly affected by the US treasury yields. We discuss the important implications of these findings for portfolio managers and policymakers.
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.