Table 7: Computational settings for selected forecasting models.

GA ANFIS GARCH (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.