The economic evaluation of volatility timing on commodity futures using periodic GARCH-Copula model

• Main Authors: Xue Gong, Songsak Sriboonchitta, Jianxu Liu
• Format: Conference Proceeding
• Published: 2018
• Subjects: Computer Science; Mathematics
• Online Access: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84958526181&origin=inward; http://cmuir.cmu.ac.th/jspui/handle/6653943832/54375
• Institution: Chiang Mai University

© Springer International Publishing Switzerland 2015. Corn is rapidly emerging used as an energy crop. As such, it strengthen the corn-ethanol-crude oil price relationship. In addition, both corn price and crude oil price have been shown to have seasonal changes and also exhibit an asymmetric or tail dependence structure. Hence, this paper uses a periodic GARCH Copula model to explore the volatility and dependence structure between the corn and oil price. More importantly, an asset-allocation strategy is adopted to measure the economic value of the periodic GARCH Copula models. The out-of-sample forecasts show that periodic GARCH copula model performs better than other parametric models as well as a non-parametric model. This result is important since the copula-based GARCH not only statistically improved the traditional method, but has economic benefit to its application. The in-sample and out-of-sample results both show that a risk-averse investor should be willing to switch from non-parametric method, DCC model to Copula based Model.