https://mail.lifescienceglobal.com/pms/index.php/jrge <p><strong>Journal of Reviews on Global Economics</strong> publishes peer reviewed papers which cover all areas of Economics, Econometrics, and Finance. <a href="https://www.lifescienceglobal.com/pms/index.php/jrge/about">Read complete aims and scope here</a>. </p> en-US <h4>Policy for Journals/Articles with Open Access</h4> <p>Authors who publish with this journal agree to the following terms:</p> <ul> <li>Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a <a href="http://creativecommons.org/licenses/by/3.0/" target="_new">Creative Commons Attribution License</a> that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.<br /><br /></li> <li>Authors are permitted and encouraged to post links to their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work</li> </ul> <h4>Policy for Journals / Manuscript with Paid Access</h4> <p>Authors who publish with this journal agree to the following terms:</p> <ul> <li>Publisher retain copyright .<br /><br /></li> <li>Authors are permitted and encouraged to post links to their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work .</li> </ul> support@lifescienceglobal.com (Support Manager) support@lifescienceglobal.com (Technical Support Manager) Fri, 06 Mar 2026 11:22:24 +0000 OJS 3.3.0.10 http://blogs.law.harvard.edu/tech/rss 60 https://mail.lifescienceglobal.com/pms/index.php/jrge/article/view/10880 <p class="04-abstract">This paper proposes a theoretical framework to model the price volatility transmission between cryptocurrency markets and the renewable energy stock sector. We develop a novel Factor-Augmented Dynamic Conditional Correlation GARCH (FA-DCC-GARCH) model, which extends the standard multivariate GARCH approach by incorporating observable, time-varying factors that represent core transmission mechanisms. This provides a structural blueprint for future empirical investigation. The model posits that volatility transmission is driven by three primary channels: (1) the Energy Consumption link from crypto mining; (2) a shared Investment Sentiment and Diversification channel reflecting investor risk appetite; and (3) a Policy and Regulatory channel for exogenous shocks. Our framework predicts asymmetric volatility transmission, with stronger spillovers from crypto to renewables during periods of high uncertainty.By deconstructing the spillover effects, the model offers a nuanced understanding beyond purely empirical studies and provides a robust set of testable hypotheses for assessing the time-varying risks and diversification benefits between these critical markets.</p> Ahmad Al-Harbi Copyright (c) 2026 https://mail.lifescienceglobal.com/pms/index.php/jrge/article/view/10880 Fri, 06 Mar 2026 00:00:00 +0000