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 236
... filter . IMPROVING THE SYSTEM WITH A MEANINGFUL FILTER , OR SETUP Most simple systems are improved by adding a filter to the system , to reduce the number of trades and improve accuracy . This filter can be thought of as a setup , a con ...
... filter . IMPROVING THE SYSTEM WITH A MEANINGFUL FILTER , OR SETUP Most simple systems are improved by adding a filter to the system , to reduce the number of trades and improve accuracy . This filter can be thought of as a setup , a con ...
Página 239
... filter } then Buy { the S & P } on Open , If Y crosses below Close of Datal and Momentum ( Close , Lenl ) of Data2 < 0 and Momentum ( Close , Len2 ) of Datal > 0 { This is the additional filter } then Sell { the S & P } on Open ; Source ...
... filter } then Buy { the S & P } on Open , If Y crosses below Close of Datal and Momentum ( Close , Lenl ) of Data2 < 0 and Momentum ( Close , Len2 ) of Datal > 0 { This is the additional filter } then Sell { the S & P } on Open ; Source ...
Página 374
... filter that catches ticks in error by as little as four ticks . Detection is based on the kinds of errors typically made by the typist at each exchange pit . Questions to Ask Does the data vendor filter out bad quotes ? Does the ...
... filter that catches ticks in error by as little as four ticks . Detection is based on the kinds of errors typically made by the typist at each exchange pit . Questions to Ask Does the data vendor filter out bad quotes ? Does the ...
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