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 36
Maximizing Day Trading and Overnight Profits Mark Jurik. TABLE 3.4 DMI SIGNALS FOR LOUISIANA PACIFIC Buy Date Buy Price Sell Date Sell Price Percent Change 10/16/95 24.625 10/23/95 23.500 -4.569 10/24/95 24.375 11/15/95 23.375 -4.103 11 ...
Maximizing Day Trading and Overnight Profits Mark Jurik. TABLE 3.4 DMI SIGNALS FOR LOUISIANA PACIFIC Buy Date Buy Price Sell Date Sell Price Percent Change 10/16/95 24.625 10/23/95 23.500 -4.569 10/24/95 24.375 11/15/95 23.375 -4.103 11 ...
Página 181
... buy signal , and that signal remains in effect until the indicator meets the condition that it deems to be bearish . A sell signal is then generated and remains in effect until the next buy signal . Since a buy signal is al- ways ...
... buy signal , and that signal remains in effect until the indicator meets the condition that it deems to be bearish . A sell signal is then generated and remains in effect until the next buy signal . Since a buy signal is al- ways ...
Página 188
... signal analysis includes a comparison of per annum gains with the buy - hold statistic . Likewise , the subsequent - performance approach can use an all - period gain statistic as a benchmark . In Figure 11.7 , for instance , the aver ...
... signal analysis includes a comparison of per annum gains with the buy - hold statistic . Likewise , the subsequent - performance approach can use an all - period gain statistic as a benchmark . In Figure 11.7 , for instance , the aver ...
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