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 27
... period exponential moving average of the first . ) Stochastics ( STOC ) To complete the technical assessment of an issue , it is useful to know where the issue is currently trading relative to its price range over the past x number of ...
... period exponential moving average of the first . ) Stochastics ( STOC ) To complete the technical assessment of an issue , it is useful to know where the issue is currently trading relative to its price range over the past x number of ...
Página 188
... period gain statistic as a benchmark . In Figure 11.7 , for instance , the aver- age 10 - day gain in the Dow Industrials has been 2 percent following a signal , nearly seven times the 0.3 percent mean gain for all 10 - day periods ...
... period gain statistic as a benchmark . In Figure 11.7 , for instance , the aver- age 10 - day gain in the Dow Industrials has been 2 percent following a signal , nearly seven times the 0.3 percent mean gain for all 10 - day periods ...
Página 278
... period EMA is : where -- - EMA ( t ) = k × X ̧ + ( 1 − k ̧ ) × EMA ( t − 1 ) n k = 1 / ( n + 1 ) , the smoothing coefficient n X is the value of the time series at time t t n EMA ( t ) is the value of the n - period EMA at time t n To ...
... period EMA is : where -- - EMA ( t ) = k × X ̧ + ( 1 − k ̧ ) × EMA ( t − 1 ) n k = 1 / ( n + 1 ) , the smoothing coefficient n X is the value of the time series at time t t n EMA ( t ) is the value of the n - period EMA at time t n To ...
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