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 226
... linear , and lends itself , as a first approximation , to representation as a linear trend . When we proceed to subtract the trend , a new data stream is created . The trans- formed data stream oscillates around the zero axis , making ...
... linear , and lends itself , as a first approximation , to representation as a linear trend . When we proceed to subtract the trend , a new data stream is created . The trans- formed data stream oscillates around the zero axis , making ...
Página 286
... linear regression inputs with largest coefficients . Selecting the most predictive variables from a particular level ... linear trend . A network was trained on the residual and added to the trend . The result was a 8-5-1 network with a ...
... linear regression inputs with largest coefficients . Selecting the most predictive variables from a particular level ... linear trend . A network was trained on the residual and added to the trend . The result was a 8-5-1 network with a ...
Página 291
... linear statistics to develop strategies to de- termine when to invest and when to divest . Moving averages and variance lines are just some examples of this method . The problem with linear statistics is that the un- derlying market ...
... linear statistics to develop strategies to de- termine when to invest and when to divest . Moving averages and variance lines are just some examples of this method . The problem with linear statistics is that the un- derlying market ...
Contenido
Chapter | 3 |
Quantifying a Markets Upside and Downside Potential | 12 |
Exiting a Market | 76 |
Derechos de autor | |
Otras 16 secciones no mostradas
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