The question is attached as below:

1. (a) Why, in the recent finance literature, have researchers preferred generalized autoregressive conditional heteroskedasticity (1,1) models to standard autoregressive conditional heteroscedasticity (p)? [10 marks] (b) Describe two extensions to the original generalized autoregressive conditional heteroskedasticity model. What additional characteristics of financial data might they be able to capture? [10 marks] (c) Consider the following generalized autoregressive conditional heteroskedasticity (1,1) model y=NTH, M-N(0, o? ) (1) o? = do + alu + poz (2) where y, is a daily stock return series. What range of values are likely for the coefficients defined in equations (1) and (2)? [10 marks] (d) Suppose that a researcher wanted to test the null hypothesis that a + 8 = 1 in equation (2). Explain how this might be achieved within the maximum likelihood framework. [10 marks]