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 132
... EXAMPLE Figure 8.4 shows a spreadsheet that contains an example of the Markowitz / Xu data mining correction formula in action . The first 18 columns of the spreadsheet are or- ganized as follows : • Column A. Date . • Column B. The ...
... EXAMPLE Figure 8.4 shows a spreadsheet that contains an example of the Markowitz / Xu data mining correction formula in action . The first 18 columns of the spreadsheet are or- ganized as follows : • Column A. Date . • Column B. The ...
Página 188
... example , one way to address the question would be to list the percentage of cases in which the mar- ket was higher over the subsequent period , and to then compare that with the per- centage of cases in which the market was higher over ...
... example , one way to address the question would be to list the percentage of cases in which the mar- ket was higher over the subsequent period , and to then compare that with the per- centage of cases in which the market was higher over ...
Página 283
... example from it at random . Put the example in the output training set . Proceed to the next bin and continue this process in a round - robin fashion until the desired number of examples have been selected . Use the new data set to do ...
... example from it at random . Put the example in the output training set . Proceed to the next bin and continue this process in a round - robin fashion until the desired number of examples have been selected . Use the new data set to do ...
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