Pinar Evrim-MandaciEfe Caglar CagliDilvin Taşkın2025-10-062020030142070301-420710.1016/j.resourpol.2020.101778https://www.scopus.com/inward/record.uri?eid=2-s2.0-85087919438&doi=10.1016%2Fj.resourpol.2020.101778&partnerID=40&md5=401d59ce4f8ed561240eec0fb2fbd3e9https://gcris.yasar.edu.tr/handle/123456789/9156In this paper we investigate the volatility spillover effect among the global commodity futures (including both energy and metal futures, global stock markets (covering both Developed and Emerging Markets), the US bond market and the US Dollar index by employing the dynamic connectedness approach of (Diebold and Yilmaz 2012 2014) based on the time-varying parameter vector autoregressive (TVP-VAR) model and using daily data for the period from January 3 1992 to December 27 2019. Our results indicate a moderate connectedness among the volatilities changing over time and approaching its peak level during 2007/08 global financial crises. In addition we determine the optimal hedge ratios and portfolio weights for the commodity investors and portfolio managers. Our results indicate that for the equity market volatility investors the highest hedging effectiveness can be reached by taking short positions in energy futures (such as natural gas) on the other hand for both the US bond and US Dollar volatility investors it can be reached by taking short positions in metal futures (such as gold). © 2020 Elsevier B.V. All rights reserved.EnglishCommodity Markets, Connectedness, Hedging, Market Linkage, Volatility Spillover, Commerce, Investments, Global Financial Crisis, Global Stock Markets, Optimal Hedge Ratio, Portfolio Managers, Portfolio Strategies, Time Varying Parameter, Us Dollar Indices, Volatility Spillovers, Financial Markets, Energy Market, Market Conditions, Metal, Spillover Effect, Stock Market, Vector Autoregression, United StatesCommerce, Investments, Global financial crisis, Global stock markets, Optimal hedge ratio, Portfolio managers, Portfolio strategies, Time varying parameter, Us dollar indices, Volatility spillovers, Financial markets, energy market, market conditions, metal, spillover effect, stock market, vector autoregression, United StatesArticle