Computerized Trading: Maximizing Day Trading and Overnight ProfitsNew York Institute of Finance, 1999 - 415 páginas Discover the answers to all your computerized trading questions, from basic to advanced, in this ground-breaking new guide to successful day trading. Twenty top experts reveal their techniques and strategies for successful computerized trading in this practical guide. |
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Página 46
... shown in Table 4.1 for comparison , assuming two bins per A. The reader may also want to adjust M and observe changes to the PDF as a basis for selection . PDF EXAMPLES AND INTERPRETATION Tabulation of the input data for the example ...
... shown in Table 4.1 for comparison , assuming two bins per A. The reader may also want to adjust M and observe changes to the PDF as a basis for selection . PDF EXAMPLES AND INTERPRETATION Tabulation of the input data for the example ...
Página 245
... shown in Figure 14.18 . The performance factors of net profit and percent profitable allow for a ready comparison of systems . In this case , profit statistics of $ 408,675 , with 70.77 percent profitable trades , are favorable ...
... shown in Figure 14.18 . The performance factors of net profit and percent profitable allow for a ready comparison of systems . In this case , profit statistics of $ 408,675 , with 70.77 percent profitable trades , are favorable ...
Página 285
... shown under the Network heading . The number of hidden units in the final network is shown under Nodes . The range 1/1/93 through 6/18/93 was set aside as a validation set . It was not used at all for developing the model . A FEW GOOD ...
... shown under the Network heading . The number of hidden units in the final network is shown under Nodes . The range 1/1/93 through 6/18/93 was set aside as a validation set . It was not used at all for developing the model . A FEW GOOD ...
Contenido
Chapter | 3 |
Quantifying a Markets Upside and Downside Potential | 12 |
Exiting a Market | 76 |
Derechos de autor | |
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Términos y frases comunes
apply approach backtesting bars Bollinger Bands breakout buy signal calculated chart coefficient Coefficient of variation congestion contract data mining data vendors datafeed develop DJIA drawdown equity curve evaluation example Exchange exit Exponential Moving Average Figure formula future fuzzy logic genetic algorithms Index input intraday investors linear losing trades loss Louisiana Pacific method momentum money management moving average neural networks nodes nonlinear pricing nontrending number of trades Omega Research optimization options outlier output pattern percent period portfolio position predict problem programs ratio Relative Strength Index risk run-up sell signals simple moving average Statistical Network Steve Fossett stochastic stop T-bond Table Technical Analysis technical indicators techniques tick tion TradeStation trading performance trading strategy trading system trend trendline uptrend variables volatility volume winning trades zone