Given the stationary appearance of the first difference, a constant model is the appropriate model for use in this series. The model forecasts the changes of the Rolls Royce share prices.Application of the constant model for the logged series of the first difference is an equivalent of the estimation of a random walk model for the original series. The data below originates from fitting a geometric randomwalk on DLOG (RR) on the period between 1/03/2000 and 12/31/2007.In this geometric randomwalk with growth, the constant term is 0. This is a representative of the percentage average returns of 0.049% for the sample period between 1/03/2000 and 12/31/2007. This is also an increase in the daily value of the share price by 0.In most financial forecasting series, the geometric randomwalk model is in use, by default. Its usefulness has limits to forecasting the mean of the returns. This is because it only takes into account the first moment of the series during analysis.The trading that takes place between buyers and sellers in the market makes up the financial time series at the financial market. Due to the many exogenous factors that influence the patterns and behaviour of the market, price series are not the preferential variables to work with (Mills 1999). For better analysis, the variables that are in use are the series of returns and the first difference of log price series. In the series of returns, volatility tends to happen in clusters. This is volatility clustering. This occurs due to the tendency of larger changes occurring whether positive or negative, which are always followed by clusters of changes of the complement sign. This observation takes place. Business Forecasting Using eViews.
Brooks, C., 2002. Introductory Econometrics for Finance, Cambridge University Press, Cambridge.
Franses, P.H., 1998. Time Series Models for Business and Economic Forecasting, Cambridge University Press, Cambridge.
Mills, T.C., 1999. The Econometric Modelling of Financial Time Series, Cambridge University Press, Cambridge.