Thursday, 25 March 2010: 15:10
Objectives: The agricultural softs are very important in the economic of some countries. For this reason, it is necessary to analyze the evolution of these agricultural prices softs and to suggest several models to explain the behaviour of these types of products.
Data/Methods: The data used are the daily returns of average price of different types of agricultural softs, such as: Corn, wheat, cotton, coffee, soya bean, rice and sugar.
The methods used to estimate the behaviour of these agricultural prices softs are based in maximum likelihood.
Results/Expected results: We expect to estimate if the different agricultural softs prices have common stylized facts to use several model to estimate them and to choose the best model.
Conclusion: The autoregressive heteroskedasticity conditional models and the stochastic volatility models are able to reproduce the dynamics of volatility and the stylised facts of average price of agricultural softs. However, some stylised facts, such as, the asymmetric answer of the prices volatility, it has been estimated better with the stochastic volatility models.
Keywords: Stochastic volatility (SV), Heterokedasticity conditional, Agricultural Softs.
Data/Methods: The data used are the daily returns of average price of different types of agricultural softs, such as: Corn, wheat, cotton, coffee, soya bean, rice and sugar.
The methods used to estimate the behaviour of these agricultural prices softs are based in maximum likelihood.
Results/Expected results: We expect to estimate if the different agricultural softs prices have common stylized facts to use several model to estimate them and to choose the best model.
Conclusion: The autoregressive heteroskedasticity conditional models and the stochastic volatility models are able to reproduce the dynamics of volatility and the stylised facts of average price of agricultural softs. However, some stylised facts, such as, the asymmetric answer of the prices volatility, it has been estimated better with the stochastic volatility models.
Keywords: Stochastic volatility (SV), Heterokedasticity conditional, Agricultural Softs.