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Time-varying Commodity Portfolio Optimization

Yang, Qianqian LU (2024) NEKN02 20241
Department 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:
author
Yang, Qianqian LU
supervisor
organization
course
NEKN02 20241
year
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}},
}