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Multi momentum indicatorScript contains couple momentum oscillators all in one pane List of indicators: RSI Stochastic RSI MACD CCI WaveTrend by LazyBear MFI Default active indicators are RSI and Stochastic RSI Other indicators are disabled by default RSI, StochRSI and MFI are modified to be bounded to range from 100 to -100. That's why overbought is 40 and 60 instead 70 and 80 while oversold -40 and -60 instead 30 and 20. MACD and CCI as they are not bounded to 100 or 200 range, they are limited to 100 - -100 by default when activated (extras are simply hidden) but there is an option to show full indicator. In settings there are couple more options like show crosses or show only histogram. Default source for all indicators is close (except WaveTrend and MFI which use hlc3) and it could be changed but for all indicators. There is an option for 2nd RSI which can be set for any timeframe and background calculated by Fibonacci levels.
Pine Script®指標
由prela提供
7
ANN MACD Future Forecast (SPY 1D) NOTE : Deep learning was conducted in a narrow sample set for testing purposes. So this script is Experimental . This system is based on the following article and is inspired by an external program: hackernoon.com None of the artificial neural networks in Tradingview work and are not based on completely correct logic. Unlike others in this system: IMPORTANT NOTE: If the tangent activation function is used, the input data must also have tangent values (compared to the previous values of 1 bar). Inputs were prepared according to this judgment. 1. The tangent function which is the activation function is written correctly. (The tangent function in the article: ActivationFunctionTanh (v) => (1 - exp (-2 * v)) / (1 + exp (-2 * v))) 2. Missing bias parts in the formulas were added. 3. The output function is taken from the next day (historical), so that the next bar can be predicted, which is the truth. 4.The forecast value of the next bar is subtracted from the current bar change and the market direction is determined. 5.When the future forecast and the current close are added together, the resulting data is called seed. The seed carries data both from the present and from yesterday and from the future. 6.And this seed was subjected to the MACD method. Thus, due to exponential averages, more importance will be given to recent developments and The acceleration situations will show us the direction. However, a short position should be taken for crossover and a long position for crossunder . Because the predicted values ​​work in reverse.Even though we use the same period (9,12,26) it is much faster! 7. There is no future code that can cause Repaint. However, the color after closing should be checked. The system is completely correct. However, a very narrow sample was selected. 100 data: Tangent diffs ; volume change, bollinger bands values changes (Upband , Midband , Lowband) and LazyBear's Squeeze Momentum Indicator (SQZMOM_LB) change and the next bar data (historical) price change were put into the deep learning test. IMPORTANT NOTE : The larger the sample set and the more effective dependent variables, the higher the hit rate of the deep learning test! EDIT : This code is open source under the MIT License. If you have any improvements or corrections to suggest, please send me a pull request via the github repository github.com Stay tuned. Best regards!
Pine Script®指標
由Noldo提供
15
Babypips: Inside Bar Momentum StrategyThe strategy contained in this post comes courtesy of babypips (.com), an excellent resource for all thing forex related. If you are new to trading, the site is definitely worth checking out! Code commentary and an introduction to Inside Bars are available for this post on the Backtest-Rookies (.com) website. Note: If you are interested in custom development services, please check out our services page on the Backtest-Rookies site. Strategy Overview Inside Bar Momentum Strategy. Inside Bar Detection Position sizing based on stoploss distance ( Note: Based on equity and assumes that the account currency is the counter currency. Stop buys for entries Takeprofit / Stoplosses for exits Control Stopbuy, Takeprofit and Stoploss targets with inputs Control Backtest start/end dates
Pine Script®策略
由BacktestRookies提供
9
ka66: Volatility MomentumThis is a 'monitoring' indicator to see if an instrument is viable enough to be traded, by virtue of volatility (or lack of volatility in context may lead to a break out), or may become so. It shows the following information: Price Range (high - low) averaged across a set of bars: Useful gauging potential trading profits. This was its initial goal, to not measure bars manually! ATR : As a comparison point for the price range above. Divergence between true range (TR) and plain price range might signal volatility changes occurring in the instrument. Signal volatility line : a moving average of the larger of the average price range and ATR. This takes inspiration from other indicators like MACD and Stochastic, and is a way of comparing change in recent volatility --- this achieves the momentum part. The larger was chosen to keep things simple, and not have a signal line per range! avgRange = movingAvg(high - low, avgPeriod) atr = movingAvg(trueRange, avgPeriod) signal = movingAvg(max(avgRange, atr), avgPeriod) Configurable periods and averaging mechanism.
Pine Script®指標
由ka66提供
4
Squeeze Momentum Indicator [LazyBear] Version2 by KıvanÇ fr3762Modified version of Squeeze Momentum Indicator including line graph of the main indicator instead of using a Histogram and a second Signal line (5 bars SMA of the original line) to provide visual BUY/SELL signals BUY when Blue crosses ABOVE the RED signal line SELL when Blue crosses BELOW the RED signal line author: LazyBear modified by: KıvanÇ @fr3762 on twitter (tweets are only in TURKISH) TURKISH EXPLANATION: Orijinal indikatördeki histogram yerine çizgi grafiği alınarak bu grafiğin 5 barlık basit hareketli ortalaması sinyal çizgisi olarak eklendi. Al Koşulu: Mavi çizginin Kırmızıyı yukarı kesmesi Sat koşulu: Kırmızı çizginin Maviyi yukarı kesmesi
Pine Script®指標
由KivancOzbilgic提供
32
Inverse Fisher Transform on SMI (Stochastic Momentum Index)Inverse Fisher Transform on SMI (Stochastic Momentum Index) About John EHLERS: From California, USA, John is a veteran trader. With 35 years trading experience he has seen it all. John has an engineering background that led to his technical approach to trading ignoring fundamental analysis (with one important exception). John strongly believes in cycles. He’d rather exit a trade when the cycle ends or a new one starts. He uses the MESA principle to make predictions about cycles in the market and trades one hundred percent automatically. In the show John reveals: • What is more appropriate than trading individual stocks • The one thing he relies upon in his approach to the market • The detail surrounding his unique trading style • What important thing underpins the market and gives every trader an edge About INVERSE FISHER TRANSFORM: The purpose of technical indicators is to help with your timing decisions to buy or sell. Hopefully, the signals are clear and unequivocal. However, more often than not your decision to pull the trigger is accompanied by crossing your fingers. Even if you have placed only a few trades you know the drill. In this article I will show you a way to make your oscillator-type indicators make clear black-or-white indication of the time to buy or sell. I will do this by using the Inverse Fisher Transform to alter the Probability Distribution Function (PDF) of your indicators. In the past12 I have noted that the PDF of price and indicators do not have a Gaussian, or Normal, probability distribution. A Gaussian PDF is the familiar bell-shaped curve where the long “tails” mean that wide deviations from the mean occur with relatively low probability. The Fisher Transform can be applied to almost any normalized data set to make the resulting PDF nearly Gaussian, with the result that the turning points are sharply peaked and easy to identify. The Fisher Transform is defined by the equation 1) Whereas the Fisher Transform is expansive, the Inverse Fisher Transform is compressive. The Inverse Fisher Transform is found by solving equation 1 for x in terms of y. The Inverse Fisher Transform is: 2) The transfer response of the Inverse Fisher Transform is shown in Figure 1. If the input falls between –0.5 and +0.5, the output is nearly the same as the input. For larger absolute values (say, larger than 2), the output is compressed to be no larger than unity. The result of using the Inverse Fisher Transform is that the output has a very high probability of being either +1 or –1. This bipolar probability distribution makes the Inverse Fisher Transform ideal for generating an indicator that provides clear buy and sell signals.
Pine Script®指標
由KivancOzbilgic提供
10