Time-varying Commodity Portfolio Optimization
(2024) NEKN02 20241Department of Economics
- Abstract
- The commodity market is basically used for hedging against physical products. However, commodity portfolios alone can be an investment choice based on their return and risk characteristics. In order to analyze the interconnectedness among commodities, this study applies multivariate GARCH models of diagonal VECH, diagonal BEKK, and CCC to model the volatility among the selected commodity groups of metal, energy, and agriculture from 1991 to 2023. The empirical results show that the diagonal VECH model with student t distribution is the fittest model. By doing portfolio optimization based on the time-varying conditional statistics of the empirical results, the optimal commodity weights are obtained and then the performance is evaluated over... (More)
- The commodity market is basically used for hedging against physical products. However, commodity portfolios alone can be an investment choice based on their return and risk characteristics. In order to analyze the interconnectedness among commodities, this study applies multivariate GARCH models of diagonal VECH, diagonal BEKK, and CCC to model the volatility among the selected commodity groups of metal, energy, and agriculture from 1991 to 2023. The empirical results show that the diagonal VECH model with student t distribution is the fittest model. By doing portfolio optimization based on the time-varying conditional statistics of the empirical results, the optimal commodity weights are obtained and then the performance is evaluated over time. Diversified portfolios of metal, energy, and agricultural commodities generally outperform portfolios focusing on mitigating extreme risk which allocates the majority of the proportion to energy commodities. This study emphasizes the importance of diversification in the commodity market to balance return and risk, and the need to adjust risk based on hedge ratios. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/9157708
- author
- Yang, Qianqian LU
- supervisor
- organization
- course
- NEKN02 20241
- year
- 2024
- type
- H1 - Master's Degree (One Year)
- subject
- keywords
- Commodity, Portfolio optimization, Time-varying volatility
- language
- English
- id
- 9157708
- date added to LUP
- 2024-08-12 15:59:40
- date last changed
- 2024-08-12 15:59:40
@misc{9157708, abstract = {{The commodity market is basically used for hedging against physical products. However, commodity portfolios alone can be an investment choice based on their return and risk characteristics. In order to analyze the interconnectedness among commodities, this study applies multivariate GARCH models of diagonal VECH, diagonal BEKK, and CCC to model the volatility among the selected commodity groups of metal, energy, and agriculture from 1991 to 2023. The empirical results show that the diagonal VECH model with student t distribution is the fittest model. By doing portfolio optimization based on the time-varying conditional statistics of the empirical results, the optimal commodity weights are obtained and then the performance is evaluated over time. Diversified portfolios of metal, energy, and agricultural commodities generally outperform portfolios focusing on mitigating extreme risk which allocates the majority of the proportion to energy commodities. This study emphasizes the importance of diversification in the commodity market to balance return and risk, and the need to adjust risk based on hedge ratios.}}, author = {{Yang, Qianqian}}, language = {{eng}}, note = {{Student Paper}}, title = {{Time-varying Commodity Portfolio Optimization}}, year = {{2024}}, }