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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Maximizing Day Trading and Overnight Profits Mark Jurik. FIGURE 17.5 EXAMPLE STATISTICAL NETWORK . INPUT VALUES PROPAGATE THROUGH A SERIES OF FUNCTIONAL NODES THAT ARE RAINED AUTOMATICALLY BY THE DATA MINING ALGORITHM . Input A Input B ...
Maximizing Day Trading and Overnight Profits Mark Jurik. FIGURE 17.5 EXAMPLE STATISTICAL NETWORK . INPUT VALUES PROPAGATE THROUGH A SERIES OF FUNCTIONAL NODES THAT ARE RAINED AUTOMATICALLY BY THE DATA MINING ALGORITHM . Input A Input B ...
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Maximizing Day Trading and Overnight Profits Mark Jurik. FIGURE 17.6 STATISTICAL NETWORK LEARNING ALGORITHM . THIS AUTOMATED PROCESS FINDS THE BEST NETWORK ARCHITECTURE , THE NODE EQUATION , AND GUARDS ... Statistical Network Data Mining 303.
Maximizing Day Trading and Overnight Profits Mark Jurik. FIGURE 17.6 STATISTICAL NETWORK LEARNING ALGORITHM . THIS AUTOMATED PROCESS FINDS THE BEST NETWORK ARCHITECTURE , THE NODE EQUATION , AND GUARDS ... Statistical Network Data Mining 303.
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... statistical networks were synthesized for the buy and sell indicators ; each of the four networks was evaluated on two in- dependent data subsets . Rightmost column shows the network's average absolute error , for each scenario . Table ...
... statistical networks were synthesized for the buy and sell indicators ; each of the four networks was evaluated on two in- dependent data subsets . Rightmost column shows the network's average absolute error , for each scenario . Table ...
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