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Página 49
N 1 max W ( A ) = a ; - i = 1 i , j = 1 By defining ( x ; ) · Þ ( x ; ) as K ( xi , xj ) using the Mer- cer's theorem . The training of SVM is then defined as Assets structure Gearing Profit Ratios ( CA - STK ) / CL , PBIT / CL ...
N 1 max W ( A ) = a ; - i = 1 i , j = 1 By defining ( x ; ) · Þ ( x ; ) as K ( xi , xj ) using the Mer- cer's theorem . The training of SVM is then defined as Assets structure Gearing Profit Ratios ( CA - STK ) / CL , PBIT / CL ...
Página 369
Table 3 : Statistics of trades for 1 Layer Neural Network in markets used for tuning : Ĥ = average holding time in hours , P = % profit per trade . Statistics are given for long positions , short positions , winning positions ...
Table 3 : Statistics of trades for 1 Layer Neural Network in markets used for tuning : Ĥ = average holding time in hours , P = % profit per trade . Statistics are given for long positions , short positions , winning positions ...
Página 425
Also , the profit return including transaction cost for the incremental GFETS was better than that for the common Great China stock funds . Although the best Great China fund performed slightly better than the incremental GFETS ...
Also , the profit return including transaction cost for the incremental GFETS was better than that for the common Great China stock funds . Although the best Great China fund performed slightly better than the incremental GFETS ...
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Contenido
BANKRUPTCY PREDICTION WITH LEAST | 1 |
SIMPLE DECISION MAKING CRITERION AS REAL OPTIONS | 17 |
INCLUDING LIFETIME AND OPTIONS IN RESIDUAL INCOME INDICATORS | 31 |
Derechos de autor | |
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Otras ediciones - Ver todas
Proceedings of the IEEE/IAFE 1995 Computational Intelligence for Financial ... Vista de fragmentos - 1995 |
Proceedings of the IEEE/IAFE 1995 Computational Intelligence for Financial ... Vista de fragmentos - 1995 |
Proceedings of the IEEE/IAFE 1995 Computational Intelligence for Financial ... Vista de fragmentos - 1995 |
Términos y frases comunes
agents algorithm analysis applied approach approximation asset assume average bond bound calculated changes compared computed conditional consider correlation corresponding cost currency decision defined denote depends derived deviation distribution dynamics Economics effect equation error estimated example exchange rate expected experiment Figure fitness forecast function future genetic given hedging implied increase indicators input interest investment Journal linear mean measure method moving neural network nonlinear normal Note observations obtained operating optimal option parameters patterns performance period points portfolio positive prediction present probability problem profit Programming random ratio REFERENCES respectively returns risk rules sample selection shows simulation square standard statistical step stochastic stock price strategies Table term tion trading trend University variables vector volatility weights
Información bibliográfica
| Título | Proceedings of the IEEE/IAFE 1995 Computational Intelligence for Financial Engineering (CIFEr): April 9-11, 1995, New York City, Crowne Plaza Manhattan |
| Colaboradores | IEEE Computer Society, IEEE Neural Networks Council, International Association of Financial Engineers |
| Editor | IEEE Service Center, 1995 |
| Procedencia del original | Universidad de Michigan |
| Digitalizado | 11 Ene. 2008 |
| ISBN | 0780321464, 9780780321465 |
| Largo | 192 páginas |
| Exportar cita | BiBTeX EndNote RefMan |