Level: 2 Background John F. Ehlers introuced the Inverse Fisher Transform of RSI in May, 2004. Function "The Inverse Fisher Transform," describes the calculation and use of the inverse Fisher transform by Dr. Ehlers in 2004. The transform is applied to any indicator with a known probability distribution function, but this script offers a sample transforms:...

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Level: 2 Background John F. Ehlers introuced Zero-Lag Data Smoothers in Jul, 2002. Function John Ehlers introduced "Zero-Lag Data Smoothers", the infinite impulse response (IIR) filter and finite impulse response (FIR) filter. In his article this issue on zero-lag smoothing, John Ehlers notes that his favorite filter is the symmetrically weighted six-bar...

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Level: 2 Background John F. Ehlers introuced Hilbert Channel Breakout Trading System in Nov, 2000. Function This indicator will show how the adaptive filter is being applied to a trading strategy. After the Hilbert Channel Breakout Signal is optimized, set the inputs for this indicator to match the corresponding inputs for the signal. In the March 2000...

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Level: 2 Background John F. Ehlers introuced the squelch indicator in Sep, 2000. Function This the squelch indicator code is identical to the Hilbert period code , with the addition of the squelch threshold and the display being implemented as a paintbar -- that is, a bar on the chart being colored, depending on the squelch threshold value. The Pine v4 code...

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Level: 2 Background John F. Ehlers introuced swiss army knife (SAK)indicator in 2005. Function The swiss army knife (SAK)indicator does all the common functions of the usual indicators, such as smoothing and momentum generation. It also does some unusual things, such as band stop and band reject filtering. Once you program this indicator into your trading...

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Level: 2 Background John F. Ehlers introuced Fractal Adaptive Moving Average (FRAMA) in 2004. Function The objective of using filters is to separate the desired signals from the undesired signals (or noise). The practical application of moving averages often involves a tradeoff between the amount of smoothness required and the amount of lag that can be...

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Level: 2 Background John F. Ehlers introuced SwamiCharts RSI in his "Cycle Analytics for Traders" chapter 16 on 2013. Function SwamiCharts retain the core functionality of the technical indicators with which you're already familiar, while packing much more information into an easy-to interpret heat map chart. With SwamiCharts, you now visualize each...

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Level: 2 Background John F. Ehlers introuced adding the Fisher Transform to the Adaptive RSI in his "Cycle Analytics for Traders" chapter 15 on 2013. Function The purpose of the Fisher transform is to take any indicator having a nominally zero mean and bounded between the limits of −1 to +1 and convert the amplitude so that the transformed indicator has an...

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Level: 2 Background John F. Ehlers introuced Measuring the Dominant Cycle using the HomoDyne Discriminator in his "Cycle Analytics for Traders" chapter 14 on 2013. Function With Hilbert transformer, the third algorithm for computing the dominant cycle is the homodyne approach. Homodyne means the signal is multiplied by itself. More precisely, we want to...

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Level: 2 Background John F. Ehlers introuced Measuring the Dominant Cycle using the Phase Accumulation in his "Cycle Analytics for Traders" chapter 14 on 2013. Function With Hilbert transformer, the next algorithm to compute the dominant cycle is the phase accumulation method. The phase accumulation method of computing the dominant cycle is perhaps the easiest...

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Level: 2 Background John F. Ehlers introuced Measuring the Dominant Cycle using the Dual Differentiator in his "Cycle Analytics for Traders" chapter 14 on 2013. Function With Hilbert transformer, the first algorithm to compute the dominant cycle is called the dual differentiator. In this case, the phase angle is computed from the analytic signal as the...

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Level: 2 Background John F. Ehlers introuced Hilbert Transformer Indicator in his "Cycle Analytics for Traders" chapter 14 on 2013. Function Basically, the real component moves with the general direction of the prices, and the imaginary component is a predictive indicator for the real component in the same sense that a cosine wave is a predictor of a sine...

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Level: 2 Background John F. Ehlers introuced Classic Hilbert Transform in his "Cycle Analytics for Traders" chapter 14 on 2013. The Hilbert Transform is a procedure to create complex signals from the simple chart data familiar to all traders. Once we have the complex signals, we can compute indicators and signals that are more accurate and responsive than those...

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Level: 2 Background John F. Ehlers introduced Convolution Indicator in his "Cycle Analytics for Traders" chapter 13 on 2013. Function Since high correlation exists only at the market turning point, the convolution indicator is dependent on the lookback period used in the calculation. Assuming the two price segments have an equal time duration, the peak...

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Level: 2 Background John F. Ehlers introduced Even Better sinwave Indicator in his "Cycle Analytics for Traders" chapter 12 on 2013. Function The original Sinewave Indicator was created by seeking the dominant cycle phase angle that had the best correlation between the price data and a theoretical dominant cycle sine wave. The Even Better Sinewave Indicator...

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Level: 2 Background John F. Ehlers introduced Adaptive BandPass Filter in his "Cycle Analytics for Traders" chapter 11 on 2013. Function Adaptive band-pass filter was designed. It just makes since to tune that filter to the measured dominant cycle to eliminate all the other frequency components that are of no interest. Here, the adaptive band-pass indicator...

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Level: 2 Background John F. Ehlers introduced Adaptive CCI 2013 in his "Cycle Analytics for Traders" chapter 11 on 2013. Function The time length to be used for the channel in the calculations is widely varied in the literature. In all cases, the length is rather arbitrarily established to fit the indicator to some preconceived event. It seems to me that it...

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Level: 2 Background John F. Ehlers introduced Adaptive RSI 2013 in his "Cycle Analytics for Traders" chapter 11 on 2013. Function The adaptive RSI starts with the computation of the dominant cycle using the autocorrelation periodogram approach. The identification of the RSI indicator itself following the dominant cycle calculation is noted by the comment near...

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