Computerized Trading: Maximizing Day Trading and Overnight ProfitsComplete with explanatory charts, diagrams, and checklists, a detailed discussion of the use of computerized trading systems draws on the expertise of twenty expert traders, and gives step-by-step advice on strategies and reliable data to both beginning and experienced investors. |
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Página 287
A lesson to be learned from this is that you cannot rely on “ theoretical ”
arguments to predict the best way to preprocess data . The only effective method
is to take the time to compare a new approach to other proven methods on real
data sets .
A lesson to be learned from this is that you cannot rely on “ theoretical ”
arguments to predict the best way to preprocess data . The only effective method
is to take the time to compare a new approach to other proven methods on real
data sets .
Página 292
Our goal is to find a way to predict the future so that we can use this prediction to
make money . We have been discussing this approach with the idea that we will
create a model of some process . Figure 17.1 illustrates what it is that we are ...
Our goal is to find a way to predict the future so that we can use this prediction to
make money . We have been discussing this approach with the idea that we will
create a model of some process . Figure 17.1 illustrates what it is that we are ...
Página 294
MODEL OUTPUT : WHAT PARAMETERS SHOULD WE PREDICT ? Another ...
Since we know by intuition that a prediction of something tomorrow is more
accurate than something a month from now , a short prediction is best . However ,
the ...
MODEL OUTPUT : WHAT PARAMETERS SHOULD WE PREDICT ? Another ...
Since we know by intuition that a prediction of something tomorrow is more
accurate than something a month from now , a short prediction is best . However ,
the ...
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Contenido
PART | 1 |
Popular Trading Indicators | 13 |
Combining Trend Analysis with Indicator Readings | 30 |
Derechos de autor | |
Otras 21 secciones no mostradas
Términos y frases comunes
amount analysis apply approach bars better calculated Chapter chart close congestion considered continue contract curve daily designed determine develop direction distribution drawdown effective equity evaluation example Exchange exit expected factor Figure formula function future gain give important Index indicators initial input largest less limit linear look losing loss means measure method moving average NASDAQ neural networks occur offer optimization options oscillator pattern percent performance period position predict problem produce profit question range ratio received represents Research risk selection sell short shown shows signals simple standard statistical stochastic stop strategy Table technical techniques tick tion trading system trend variables vendors volatility volume winning
Información bibliográfica
| Título | Computerized Trading: Maximizing Day Trading and Overnight Profits New York Institute of Finance Series |
| Autor | Mark Jurik |
| Editor | Mark Jurik |
| Edición | ilustrada |
| Editor | New York Institute of Finance, 1999 |
| Procedencia del original | Universidad de Michigan |
| Digitalizado | 2 Sep. 2011 |
| ISBN | 0735200777, 9780735200777 |
| Largo | 415 páginas |
| Exportar cita | BiBTeX EndNote RefMan |