Business and Economic Forecasting Essay Example | Topics and Well Written Essays - 3500 words

Business and Economic Forecasting - Essay ExampleThe appropriate model is estimated and a peerless to four step forecasting is on a lower floortaken 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 undermentioned 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 inactive deviating by low margins, however for the period 2005 to 2007 there was an increase in prices by puffyr margins. The next is an analysis of the Rio Tinto returns.According to Woodridge (2006) dynamic heteroskedasticity tooshie appear in fixings 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 hallucination terms mutant is constan t across observations holds there could be still other forms of heteroskedasticity that may arise, heteroskedasticity evoke be tested using the white test or the Breusch pagan test. The following chart shows a case of homoskedasticity and heteroskedasticityFrom the above draws 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 close to its mean remains constant over time, for the second diagram a case where as x increases the mean of y increases and the variance of y around its mean does not remain constant and this shows heteroskedasticity.thither are a number of consequences of heteroskedasticity and they include the fact thatEstimators are still linear functions of the independent versatileThe estimators are not biasedEstimators no longer have minimum variance therefore are not efficientThe estimated variance of the estimators is biased because the formula to e stimate them could over state or under state the true varianceThe hypothesis test of the significance is unreliable given that the estimated variance is biased.As a result Engel (1982) suggested the ARCH model that would consider a conditional error term variance that takes into consideration past error terms and this was the ARCH model. The ARCH and GARSH model are appropriate models that can be used in modeling financial data that exhibit volatility bunch, volatility clustering refers to a trend that shows that small increases or declines are followed by small increases or declines and that large increases or declines are followed by large increases or declines. From our price data chart it is evident that for the period 2000 to 2004 small increases and declines are followed by small increases or declines, however for the period 2005 and 2007 large increases are followed by large increases. This means that the ARCH and GARSH model are appropriate in estimating an appropriate mode l.The following chart summarizes the returns mean, kurtosis and