Table 7: Computational settings for selected forecasting models.


(1) Population size—3000, generated at random from the uniform probability distribution.(1) Input—Lags of cse-all and cse-30 cse-all and cse-30: Fitted GARCH (2,1) and GARCH (1,1) Selection Process: BIC.
(2) Fitness function—RMSE of model (2.2.1-2.2.2); Fitness scaling—Linear ranking process.(2) 2 mfs (type Gaussian) for each of input variables. Thus, 8 if-then fuzzy rules were learned.
(3) Selection-Roulette wheel.
(4) Crossover-fraction: 0.95; Intermediate method.
(5) Mutation-fraction: 0.05; Uniform method.
(6) Reinsertion: The fitness-based reinsertion method.
(7) Termination Criteria—Maximum number of generations, assumed 200.