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 140
... factor : Gross profit divided by gross loss . This calculation represents how much money was made for every dollar lost . Look for a system with a profit factor of 3 or more . Adjusted profit factor : This tool artificially deflates ...
... factor : Gross profit divided by gross loss . This calculation represents how much money was made for every dollar lost . Look for a system with a profit factor of 3 or more . Adjusted profit factor : This tool artificially deflates ...
Página 245
... factor , which is the gross profit divided by the gross loss , shows how much money was made for every dollar lost . A good system has a profit factor of 3 or more . Our example , with a profit factor of 2.85 , approaches that figure ...
... factor , which is the gross profit divided by the gross loss , shows how much money was made for every dollar lost . A good system has a profit factor of 3 or more . Our example , with a profit factor of 2.85 , approaches that figure ...
Página 258
... factor , X ( at ) is the process X ( t ) speeded up by a factor of a When a time series is a Bm , H = 0.5 . When H is greater or less than 0.5 , the time series is persistent or antipersistent , respectively . If a time series ' H = 0.7 ...
... factor , X ( at ) is the process X ( t ) speeded up by a factor of a When a time series is a Bm , H = 0.5 . When H is greater or less than 0.5 , the time series is persistent or antipersistent , respectively . If a time series ' H = 0.7 ...
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