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 10
... frame , the decision - making time is compressed and the stress is increased . As you drop the time frame , the number of decisions increases radically . You have seven times the number of decisions going from daily- to hourly based ...
... frame , the decision - making time is compressed and the stress is increased . As you drop the time frame , the number of decisions increases radically . You have seven times the number of decisions going from daily- to hourly based ...
Página 200
... frame that we normally trade , but may enlarge it provided that our risks are under control . However , in an ... frame . The point here is that price action oscillating in a larger time frame may behave as small trends in a smaller time ...
... frame that we normally trade , but may enlarge it provided that our risks are under control . However , in an ... frame . The point here is that price action oscillating in a larger time frame may behave as small trends in a smaller time ...
Página 204
... FRAME TRADING Since risk is related to the time frame or bar length we trade , then it stands to reason that the lower the bar length , the less the risk . Even if we are willing to trade a longer time frame , the risks associated with ...
... FRAME TRADING Since risk is related to the time frame or bar length we trade , then it stands to reason that the lower the bar length , the less the risk . Even if we are willing to trade a longer time frame , the risks associated with ...
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