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Modelling Ontario Agricultural Commodity Price Volatility with Mixtures of GARCH Processes

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dc.contributor.advisor Ker, Alan. P.
dc.contributor.author Wang, Jinrui
dc.date.accessioned 2014-09-08T14:18:41Z
dc.date.available 2014-09-08T14:18:41Z
dc.date.copyright 2014-08
dc.date.created 2014-09-04
dc.date.issued 2014-09-08
dc.identifier.uri http://hdl.handle.net/10214/8434
dc.description.abstract Agricultural commodity price volatility is a critical global issue that may affect market participants quite differently. Previous work has studied factors that may affect price changes, such as supply and demand factors, climate change, role of speculation in futures and option trading markets, etc.. Modeling price volatility helps to understand causes, patterns and impacts of price changes, making it possible to mitigate the aforementioned risks and negative effects. To demonstrate the price volatility for future pricing forecasts used in the business risk management program, this thesis estimates price models based on mixture distributions. The price is assumed to follow a normal mixture distribution Generalized Autoregressive Conditional Heteroscedasticity (GARCH) (1,1) with separate GARCH (1,1) processes in each mixture. en_US
dc.language.iso en en_US
dc.subject Price Volatility en_US
dc.subject Risk Analyse en_US
dc.subject GARCH en_US
dc.subject Econometric en_US
dc.title Modelling Ontario Agricultural Commodity Price Volatility with Mixtures of GARCH Processes en_US
dc.type Thesis en_US
dc.degree.programme Food, Agriculture and Resource Economics en_US
dc.degree.name Master of Science en_US
dc.degree.department Department of Food, Agricultural and Resource Economics en_US
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