Financial Innovation

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
Stock Index	Error Statistic	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

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