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Working Paper Series - Forecasting Volatility in Global Food Commodity Prices



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Forecasting Volatility in Global Food Commodity Prices


Volume : 0

No : 0

ISSN : WPS1101

Publisher : Arab Planning Institute - Kuwait

Author (s) : Ibrahim Onour 

Published Date : 1/1/2011


Contents :
To forecast volatility inglobal food commodity prices, in this paper a number of alternative competingmodels are employed, thin tailed normal distribution, and fat-tailed Studentt-distribution GARCH models, beside a simple approach of forecasting volatilitybased on standard deviations over the previous months as a forecast of futurevolatility. Our results indicate the t-distribution model outperforms the othertwo approaches, whereas the simple standard deviation approach outperforms thenormal distribution model, suggesting that the normality assumption of residualswhich often taken for granted for its simplicity may lead to unreliable resultsof conditional volatility estimates. The paper also shows that some of the foodcommodity prices included in the study, such as wheat, rice, and beef exhibitlong memory behavior, implying persistence of the effect of a shock for longerperiods compared to other commodities in the group. The evidence of long memoryprocess supports the view that structural changes in demand and supply sidefactors are more effective than short-term speculative factors. 

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