Business Review

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This study aims to examine the risk spillover from world energy markets to Pakistan’s agricultural commodities market using a time-varying copulas model. It also analyzes the dependence structure between energy and agricultural markets. The results show commodities such as wheat has less volatile behavior and weak lower tail dependence in energy-agricultural commodity pairs. The world energy volatility index is more volatile as compared to Pakistan’s agricultural commodities markets. Wheat is the least volatile commodity while palmolien is most volatile. The normal copula is best fitted for all energy and commodity pairs at 1% level of significance. Student-t copula is the second best-fitted model, providing significant results for all parameters. Normal copula and student-t copula highlight symmetric dependence among world energy and agricultural commodity markets. However, “student-t copula” has tail dependence and normal copula has no tail dependence. The other copula models have mixed effects in terms of fitness and parameters significance. SJC copula is the least fit copula model for all pairs in this study. The results have inferences for investors with respect to portfolio diversification.


Risk Spillover, Energy Markets, Agricultural Commodities, Copula Model



Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Published Online

December 28, 2023



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