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Table 3 Performance of the forecasting models on five stock indices

From: Estimating stock closing indices using a GA-weighted condensed polynomial neural network

Stock Index Error Statistic Forecasting Models
CPNN-GA CPNN-GD RBFNN MLP-GA MLP-DG
BSE MAPE 0.082532 0.087403 0.151002 0.084635 0.761849
ARV 0.011522 0.015524 0.017282 0.013280 0.127503
POCID 92.55 88.98 83.25 94.00 82.86
U of Theil 0.072205 0.090023 0.250044 0.082372 0.388572
DJIA MAPE 0.086603 0.092601 0.550872 0.100535 0.523583
ARV 0.012955 0.015524 0.041224 0.019282 0.075002
POCID 94.35 89.34 85.74 89.23 81.75
U of Theil 0.049713 0.052285 0.277258 0.058302 0.484922
NASDAQ MAPE 0.009263 0.009975 0.013964 0.011765 0.056570
ARV 0.034508 0.081764 0.087792 0.084112 0.272843
POCID 96.57 92.00 88.15 91.33 82.45
U of Theil 0.076244 0.076245 0.100572 0.079990 0.552932
FTSE MAPE 0.025923 0.041221 0.096658 0.027925 0.521705
ARV 0.038155 0.064845 0.500325 0.077359 0.532601
POCID 95.75 94.47 82.35 88.47 80.92
U of Theil 0.080005 0.082545 0.250660 0.105502 0.499725
TAIEX MAPE 0.042113 0.054159 0.083155 0.054211 0.380937
ARV 0.025390 0.062900 0.076225 0.210045 0.278608
POCID 95.55 92.22 85.65 91.73 85.75
U of Theil 0.039577 0.058222 0.448025 0.042275 0.472895