TIME-VARYING CORRELATION BETWEEN SEAFOOD AND MEAT INDEX IN THE PRESENCE OF OCEAN POLLUTION SHOCK
DOI:
https://doi.org/10.33003/fjs-2024-0803-2486Keywords:
Seafood index price, Meat-related index price, Bayesian M-Garch Model, Dynamic conditional correlation, Ocean pollution shockAbstract
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.
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FUDMA Journal of Sciences