Research Article

A Hybrid Approach by Integrating Brain Storm Optimization Algorithm with Grey Neural Network for Stock Index Forecasting

Table 1

Statistical characteristics of the three stock indices.

IndexVariableNumberMinimumMaximumMeanStd.aSkewnessKurtosis

SSE Composite IndexOP662148.152464.922338.6374.2912−0.466−0.056
CP662148.452460.692342.8170.0056−0.4480.088
HP662132.632444.632322.3674.6363−0.457−0.158
LP662164.322478.382358.2169.0148−0.3850.114
TV6645859524.00179786032.0087257856.1824217788.41451.1392.822

Shenzhen Composite IndexOP66811.141014.16918.7652.33264 −0.288−0.970
CP66813.991010.46921.1751.00838−0.352−0.889
HP66797.17996.81909.9152.98899−0.380−0.938
LP66817.781020.29929.2650.19085−0.272−0.980
TV6631650934.00123093328.0061848462.1817652160.188520.7591.338

HuShen 300 IndexOP662274.352694.482528.5696.66418−0.6060.190
CP662276.392681.072533.8290.90981−0.6040.332
HP662254.572660.962508.5897.34628−0.6130.059
LP662291.892705.752553.9789.09531−0.5720.467
TV6630527144.00108426536.0053832080.7315420163.92291.1992.328

Std. refers to the standard deviation.