TIME-VARYING CORRELATION BETWEEN SEAFOOD AND MEAT INDEX IN THE PRESENCE OF OCEAN POLLUTION SHOCK (FUDMA JOURNAL OF SCIENCES, 2024)
This study examines the complex relationships between global meat and seafood markets, focusing on the time-varying correlation between the Meat Index Market and the Seafood Index after Japan's nuclear wastewater release. Employing a Bayesian technique combined with the Skewed Multivariate Generalized Error Distribution, the study efficiently captures the time-varying correlations, with causality tests determining directional influences between the indices. The results reveal significant disruptions in seafood markets, highlighting the geopolitical impact on market dynamics. By offering a fresh perspective on market interdependencies during environmental crises, the study aids in risk assessments and effective risk mitigation strategies, introducing a Bayesian perspective into traditional financial econometrics and signifying a methodological shift in advanced model selection. Ultimately, understanding the dynamic relationships between meat and seafood markets can help traders, decision-makers, and market players navigate the financial effects of external shocks on global seafood market dynamics.
Keywords: Seafood index price; Meat-related index price; Bayesian M-Garch Model; Dynamic conditional correlation; Ocean pollution shock