Abstract
This paper investigated different methods for estimation of parameters of Weibull distribution, using Mean Square Error (MSE) as a criterion for selecting the best model. The result showed that Method of Moments outstripped other methods. In the same vain, the estimated results were logically extended to form a matrix that would help in predicting different commodity price processes, and the result obtained by exploring the properties of the principal component analysis solution and results showed the level of proportion accounted by first Principal Component Analysis (PCA). However, the eigenvectors describe the direction of the stock market prices in terms of changes in short-run and long-run respectively.
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