Author ORCID Identifier
Abstract
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.
Keywords
Risk Spillover, Energy Markets, Agricultural Commodities, Copula Model
DOI
10.54784/1990-6587.1524
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Recommended Citation
Saeed, H., Bibi, R., & Tahir, M. (2023). Risk Spillover from World Energy Markets to Pakistan Agricultural Commodity Markets. An application of Dependence switching Copula model. Business Review, 18(2), 70-93. Retrieved from 10.54784/1990-6587.1524
