Select two of the stock series from the ‘CAPM.XLS’ Excel file, construct a set of continuously compounded returns, and then perform a time-series analysis of these returns. The analysis should include
(a) An examination of the autocorrelation and partial autocorrelation functions.
(b) An estimation of the information criteria for each ARMA model order from (0,0) to (5,5).
(c) An estimation of the model that you feel most appropriate given the results that you found from the previous two parts of the question.
(d) The construction of a forecasting framework to compare the forecasting accuracy of
i. Your chosen ARMA model
ii. An arbitrary ARMA(1,1)
iii. An single exponential smoothing model
iv. A random walk with drift in the log price levels (hint: this is easiest achieved by treating the returns as an ARMA(0,0) – i.e. simply estimating a model including only a constant).
(e) Then compare the fitted ARMA model with the models that were estimated in chapter 4 based on exogenous variables. Which type of model do you prefer and why?