Akademik Məlumat İdarəetmə Sistemi
Economics, vol.19, no.1, 2025 (SSCI, Scopus)
In recent decades, the rising challenges posed by climate change have prompted investors to take a keen interest in green assets and incorporate them into their portfolios to achieve optimal returns. Therefore, this article explores the static and dynamic connectedness between renewable energy stocks (solar, wind, and geothermal), green cryptocurrencies (Stellar, Nano, Cardona, and IOTA), and agricultural commodities (wheat, cocoa, coffee, corn, cotton, sugar, and soybean) using the TVP-VAR (time-varying parameter vector autoregression) framework offering novel empirical evidence for investors and portfolio managers. The connectedness is examined across two distinct sub-samples: during COVID-19 and post-COVID-19 times. Because the relevant connectedness can have implications for diversification benefits, we proceed with the computation of optimal weights, hedge ratios, and hedge effectiveness using the DCC-GARCH model. The main findings are as follows: We first find that green cryptocurrencies particularly Cardona and Stellar exhibit the highest spillovers to the network and wind energy stock has the least connectedness with the other markets. Second, the dynamic NET spillover indices reveal that cotton, cocoa, and coffee are consistently net receivers over the entire period except in the beginning of the pandemic. Third, renewable energy stocks exhibit diverse positions implying that the impact of the pandemic has varied significantly across the sectors. Finally, agricultural commodity depicts greater weights in the pandemic period under scoring the benefit of a diversified portfolio consisting of agriculture and green assets.