Business and Economic Forecasting

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This paper uses Rio Tinto price index to estimate an appropriate model that can be used in forecasting future prices and returns. The maximum likelihood technique is used to estimate an appropriate model that can be used for forecasting future prices and returns.


The appropriate model is estimated and a one to four step forecasting is undertaken to determine the appropriateness of the model.
We consider the price index of the Rio Tinto, the 5 day weekly stock price for the period 31st December 1999 to 31st December 2007 is used and the following chart summarizes the price index for the period.
From the above table it is evident that for the period 2000 to 2004 the price remained relatively stable deviating by small margins, however for the period 2005 to 2007 there was an increase in prices by larger margins. The following is an analysis of the Rio Tinto returns.
According to Woodridge (2006) dynamic heteroskedasticity can appear in regressions with no dynamic, in a regression if the Gauss Markov assumption holds then the estimators are BLUE (best linear unbiased estimator). However even when the homoskedasticity assumption that the error terms variance is constant across observations holds there could be still other forms of heteroskedasticity that may arise, heteroskedasticity can be tested using the white test or the Breusch pagan test. The following chart shows a case of homoskedasticity and heteroskedasticity:
From the above diagrams assuming that the 45 degree line is the fitted regression model, then the first diagram shows a case where as x increases the mean of y increases but the variance of y around its mean remains ...
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